The present study aimed to analyze novel mechanisms underlying Nrf2-mediated anti-apoptosis in periodontal ligament stem cells (PDLSCs) in the periodontitis oxidative microenvironment. We created an oxidative stress model with H2O2-treated PDLSCs. Herein, we used real-time PCR, western blotting, TUNEL staining, fluorogenic assay and transfer genetics to confirm the degree of oxidative stress and apoptosis as well as the Nrf2 function. Surprisingly, we demonstrated that with up-regulated ROS and MDA levels, the effect of oxidative stress was obvious under H2O2 treatment. Anti-oxidative molecules were changed after the H2O2 exposure, whereby the anti-oxidative signaling of Nrf2 was activated with the increase of its downstream effectors, HO-1, NQO1 and γ-GCS. Additionally, the apoptosis levels gradually increased with oxidative stress and changes in the caspase-9, caspase-3, Bax and c-Fos levels, but not with caspase-8 and down-regulated Bcl-2. The enhanced antioxidant effect could not resist the occurrence of apoptosis. Furthermore, Nrf2 overexpression effectively improved the anti-oxidative levels and increased cell proliferation. At the same time, overexpression effectively restrained TUNEL staining and decreased the molecular levels of caspase-9, caspase-3, et al, but not that of caspase-8. By contrast, silencing the expression Nrf2 levels had the opposite effect. Collectively, Nrf2 alleviates PDLSCs via its effects on anti-oxidative and anti-intrinsic apoptosis by the activation of anti-oxidative enzymes.

Applications for Wireless Sensor Networks (WSNs) range from monitoring the environment to automating factories. However, sustained and effective functioning is made more difficult by Sensor Nodes (SNs) limited energy supplies in which optimization is the main issue. So with the aim of increasing the lifespan by decreasing the energy consumption of WSN, Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol with Deep Learning (DL) algorithm is analyzed in this paper. LEACH is a hierarchical mechanism that elects Cluster Heads (CHs) and regularly rotates their positions in order to allocate energy use effectively by using the same amount of energy. However, Deep Learning (DL) method is used to further improve energy optimization. In many applications, the types of Deep Learning methods like Artificial Neural Networks (ANNs) have shown to be very useful. Using this method, WSNs may make more efficient decisions that reduce energy consumption. Data aggregation, duty cycling, and transmission protocols may all be optimized by Deep Learning model's ability to recognize patterns and forecast network behavior. This results in lower energy consumption, a longer lifespan for the network, and better overall performance.

The nature of contemporary Spatial Data Infrastructures lies in the provision of geospatial information in an on-demand fashion. Though recent applications identified the need to react to real-time information in a time-critical way. In particular, research efforts in the field of geospatial Internet of Things have identified substantial gaps in this context, ranging from a lack of standardization for event-based architectures to the meaningful handling of real-time information as ''events''. This manuscript presents work in the field of Event-driven Spatial Data Infrastructures with a particular focus on sensor networks and the devices capturing in-situ measurements. The current landscape of Spatial Data Infrastructures is outlined and used as the basis for identifying existing gaps that retain certain geospatial applications from using real-time information. We present a selection of approaches - developed in different research projects - to overcome these gaps. Being designed for specific application domains, these approaches share commonalities as well as orthogonal solutions and can build the foundation of an overall Event-driven Spatial Data Infrastructure.

The application of the sensors optical fiber in the areas of scientific instrumentation and industrial instrumentation is very attractive due to its numerous advantages. In the industry of civil engineering for example, quasi-distributed sensors made with optical fiber are used for reliable strain and temperature measurements. Here, a quasi-distributed sensor in the frequency domain is discussed. The sensor consists of a series of low-finesse Fabry-Perot interferometers where each Fabry-Perot interferometer acts as a local sensor. Fabry-Perot interferometers are formed by pairs of identical low reflective Bragg gratings imprinted in a single mode fiber. All interferometer sensors have different cavity length, provoking the frequency-domain multiplexing. The optical signal represents the superposition of all interference patterns which can be decomposed using the Fourier transform. The frequency spectrum is analyzed and sensor´s properties were defined. Following, a quasi-distributed sensor was numerically simulated. Our sensor simulation considers sensor properties, signal processing, noise system and instrumentation. The numerical results show the behavior of resolution vs. signal-to-noise ratio. From our results, the Fabry-Perot sensor has high resolution and low resolutions. Both resolutions are conceivable because the FDPA algorithm elaborates two evaluations of Bragg wavelength shift

There are unsolved problems related to inflation, gravity, dark matter, dark energy, missing antimatter, and the birth of the universe. Some of them can be better answered by assuming the existence of aether and hypoatoms. Both were created during the inflation in the very early universe. While aether forms vacuum, hypoatoms, composed of both matter and antimatter and believed to be neutrinos, form all observable matter. In vacuum, aether exists between the particle-antiparticle dark matter form and the dark energy form in a dynamic equilibrium: A + A-bar = gamma + gamma. The same reaction stabilizes hypoatoms and generates a 3-dimensional sink flow of aether that causes gravity. Based on the hypoatom structure, the singularity does not exist inside a black hole; the core of the black hole is a hypoatom star or neutrino star. By gaining enough mass, ca. 3 X 10²² M_sun, to exceed neutrino degeneracy pressure, the black hole collapses or annihilates into the singularity, thus turning itself into a white hole or a Big Bang. The universe is anisotropic. Its center, or where the Big Bang happened, is at 0.66^+0.03_-0.01 times the radius of the observable universe at Galactic coordinates (l, b) = (286⁺¹⁰_-10, -43⁺⁷_-6). If we look from the Local Group to the center of the universe, the universe is rotating clockwise.

This study empirically analyzes the effectiveness of resource optimization utilizing artificial intelligence (AI) within cloud computing environments. It compares systems that have been transitioned from a Monolithic structure to Microservices Architecture (MSA) with those adopting a simple Rehost strategy, to validate the operational efficiency of two systems whose resource efficiency has been enhanced compared to traditional legacy systems. The research is based on systems that determined resource efficiency post-cloud migration using APM tools. It points out the limitations of traditional heuristic operation methods in resource optimization, which lead to issues such as application performance degradation, resource over-allocation, and increased operational costs. This study aims to overcome the conventional resource optimization standards that depended on the average peak usage of CPU and memory infrastructure, by introducing AI-based optimization tools, and applying on-premise standards to cloud and container environments to achieve resource optimization. The paper emphasizes the importance of resource optimization through AI-based automation tools, exploring the possibilities of resolving real-world application performance issues in cloud environments, reducing unnecessary resource usage costs, and cutting down on labor risks and operational expenses. Through this, it presents strategic directions on how AI technology can offer financial and operational advantages in managing cloud resources.

Al has very good corrosion resistance and corrosion properties. The corrosion resistance of Al cast alloys is different because these alloys contain a lot of elements. Especially in secondary alloys which contain more impurity elements from which Fe is the most common. This study deals with secondary AlSi7Mg0.3 cast alloys which contain more Fe and are affected by a chloride corrosion environment. This environment was selected based on the application of castings in the automo-tive industry. The main object was to research the effect of such an environment on basic me-chanical properties and fatigue properties. The results show that a higher Fe content does not lead to a significant reduction in the properties of the casting and the chloride environment is not so harmful. Therefore, can be stated that the investigated secondary sand-cast experimental materials can replace the primary alloys without losing the required corrosion and mechanical properties.

Qualtra, an innovative 10 MW geothermal power plant proposal, employs a closed-loop design to mitigate emissions, ensuring no direct release into the atmosphere. A thorough assessment utilizing energy and exergy analysis, Life Cycle Assessment (LCA), Exergo-economic and Exergo Environmental Analysis (EevA) was conducted. The LCA results, utilizing the ReCiPe 2016 midpoint methodology, encompass all the spectrum of environmental indicators provided. The technology implemented makes it possible to totally avoid direct atmospheric emissions from the Qualtra plant, so the environmental impact is mainly due to indirect emissions over the life cycle. The results obtained for the Global Warming Potential indicator is about 6.6 g CO2/kWh, notably lower compared to other conventional systems. Contribution analysis reveals that the construction phase dominates, accounting for over 90% of the impact in all LCA MidPoint categories. At the component level, a single score calculation incorporating normalization and weighting was executed. The resulting single score is then used into Exergo-Environmental Analysis (EEvA), highlighting the well system as the most impactful contributor, constituting approximately 45% of the total impact. Other substantial contributions to the environmental impact include the condenser (21%), the turbine (17%), and the HEGeo (14%). The Exergo-Economic analysis assesses cost distribution across major plant components, projecting an electricity cost of about 8.3 c€/kWh.

In this article, Planck star and remnant scenario i.e., solution of black hole information paradox in loop quantum gravity (LQG) are elaborated. Since, Black hole is the final fate of collapse scenario in general relativity; firstly, gravitational collapse with two possible final outcomes i.e., black hole and naked singularity, is outlined. Thereafter, black hole thermodynamics along with four laws of black hole thermodynamics, Hawking radiation, brief introduction to information theory and cause of information paradox are given. Then, solution of black hole information paradox outside the LQG are briefly explained. Thereafter, basic concepts of LQG along with loop quantum cosmology (LQC) are described. LQG can solve information paradox by its natural cut off on the value of quantum volume operator. In LQG, a star namely, Planck star is also proposed that is formed at Planck density and resides at so-called singularity point. Since, LQG removes singularity through big bounce and proposes Planck star which provides enough room for information to escape; hence, it can solve information paradox. LQG predicts remnant of black hole of the order of \(10^{-14} m\); which, is under current technological regime. In the remnant scenario, black hole makes quantum transition into white hole and this white hole behaves as a long lived remnants that can solve information paradox. In this quantum transition, a black hole tunnels into a white hole at the end of evaporation.

Background: Maladaptive neuroplasticity related learned response in substance use disorder (SUD) can be ameliorated using non-invasive brain stimulation (NIBS); however, inter-individual variability needs to be addressed for clinical translation. Objective: Our first objective was to develop a hypothesis for NIBS for learned response in SUD based on competing neurobehavioral decision systems model. Next objective was to conduct computational simulation of NIBS of cortico-cerebello-thalamo-cortical (CCTC) loop in cannabis use disorder (CUD) related dysfunctional “cue-reactivity” – a closely related construct of “craving” that is a core symptom. Our third objective was to test the feasibility of our neuroimaging guided rational NIBS approach in healthy humans. Methods: “Cue-reactivity” can be measured using behavioral paradigms and portable neuroimaging, including functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG), metrics of sensorimotor gating. Therefore, we conducted computational simulation of NIBS, including transcranial direct current stimulation(tDCS) and transcranial alternating current stimulation(tACS) of the cerebellar cortex and deep cerebellar nuclei(DCN), of the CCTC loop for its postulated effects on fNIRS and EEG metrics. We also developed a rational neuroimaging guided NIBS approach for cerebellar lobule (VII) and prefrontal cortex based on healthy human study. Results: Simulation study of cerebellar tDCS induced gamma oscillations in the cerebral cortex while tTIS induced gamma-to-beta frequency shift. Experimental fNIRS study found that 2mA cerebellar tDCS evoked similar oxyhemoglobin(HbO) response in-the-range of 5x10-6M across cerebellum and PFC brain regions (=0.01); however, infra-slow (0.01–0.10 Hz) prefrontal cortex HbO driven(phase-amplitude-coupling, PAC) 4Hz, ±2mA (max.) cerebellar tACS evoked HbO in-the-range of 10-7M that was statistically different (=0.01) across those brain regions. Conclusion: Our healthy human study showed the feasibility of fNIRS of cerebellum and PFC as well as fNIRS-driven ctACS at 4Hz that may facilitate cerebellar cognitive function via the frontoparietal network. Future work needs to combine fNIRS with EEG for multi-modal imaging.

The availability of simple SARS-CoV-2 detection methods is crucial to contain the COVID-19 pandemic. This study examined whether a commercial LAMP assay can reliably detect SARS-CoV-2 genomes directly in respiratory samples without having to extract nucleic acids (NA) beforehand. Nasopharyngeal swabs (NPS, n = 220) were tested by real-time reverse transcription (RT)-PCR and with the LAMP assay. For RT-PCR, NA were investigated. For LAMP, NA from 26 NPS in viral transport medium (VTM) were tested. The other 194 NPS were analyzed directly without prior NA extraction [140 samples in VTM; 54 dry swab samples stirred in phosphate buffered saline]. Ten NPS were tested directly by LAMP using a sous-vide cooking unit. The isothermal assay demonstrated excellent specificity (100%) but moderate sensitivity (68.8%), with a positive predictive value of 1 and a negative predictive value of 0.65 for direct testing of NPS in VTM. The use of dry swabs, even without NA extraction, improved the analytical sensitivity; up to 6% of samples showed signs of inhibition. The LAMP could be performed successfully with a sous-vide cooking unit. This technique is very fast, requires little laboratory resources and can replace rapid antigen tests or verify reactive rapid tests on site.

In CNS drug discovery, estimation of brain exposure of lead compounds is critical for their optimization. Compounds need to cross the blood-brain barrier (BBB) to reach the pharmacological targets in the CNS. The BBB is a complex system involving passive and active mechanisms of transport and efflux transporters such as P-glycoproteins (P-gp) and breast cancer resistance protein (BCRP), which play an essential role in CNS penetration of small molecules. Several in vivo, in vitro and in silico methods are available to estimate human brain penetration. Preclinical species are used as in vivo models to understand the unbound brain exposure by deriving the Kp,uu parameter, the brain/plasma ratio of exposure corrected with the plasma and brain free fraction. MDCK-mdr1 (Madin Darby canine kidney cells transfected with the MDR1 gene encoding for the human P-gp) assay is the most commonly used in vitro assay to estimate compound permeability and human efflux. The in silico methods to predict brain exposure, such as CNS MPO, CNS BBB scores and various Machine Learning models, help save costs and speed up compound discovery and optimization at all stages. These methods enable the screening of virtual compounds and building of a CNS penetrable compounds library as well as optimization of lead molecules for CNS penetration. Therefore, it is crucial to understand these methods' reliability and ability to predict CNS penetration. We review the in silico, in vitro and in vivo data and their correlation with each other and assess published in silico approaches to predict the BBB penetrability of compounds.

A variational analysis of dispersion medium (electrolytes and surfactants) was carried out for the best nucleotide interactions with the presence of nanoparticles and the ability to formation of homogeneous coatings upon drying / lyophilization. Using UV-spectroscopy and transmission electron microscopy, the processes of immobilization of nucleotides on the surface of nanoparti-cles of the composition ZrO2-3mol% Y2O3 (YSZ) in the presence of various dispersing agents were investigated. Promising dispersing agents were established, the optimal composition of suspen-sions based on DNA nucleotides and YSZ nanoparticles, which is potentially suitable for adaptive technologies of bionanoelectronics, was selected. The aim of the work is to obtain and study functional media for molecular electronics based on heterojunctions biological molecule – wide-gap dielectric.

A variational analysis of dispersion medium (electrolytes and surfactants) was carried out for the best nucleotide interactions with the presence of nanoparticles and the ability to formation of homogeneous coatings upon drying / lyophilization. Using UV-spectroscopy and transmission electron microscopy, the processes of immobilization of nucleotides on the surface of nanoparti-cles of the composition ZrO2-3mol% Y2O3 (YSZ) in the presence of various dispersing agents were investigated. Promising dispersing agents were established, the optimal composition of suspen-sions based on DNA nucleotides and YSZ nanoparticles, which is potentially suitable for adaptive technologies of bionanoelectronics, was selected. The aim of the work is to obtain and study functional media for molecular electronics based on heterojunctions biological molecule – wide-gap dielectric.

E-tourism is one of the most important modern services to achieve the development of the tourism sector while relying on sophisticated communication technologies. Certainly, these innovations in the field of tourism have disrupted this sector with new and different dimensions of tourism development. This has led various regions and countries to accelerate the search for the tools that are necessary to achieve excellence and sustainable development in tourism. This research aims to study the development factors of e-tourism to achieve excellence and sustainable development in the tourism of the Ha’il region. Therefore, we applied two analyses: in the first one, we used a statistical analysis based on the survey sent to employees from tourism companies. The objective of this analysis is to determine the main factors of e-tourism to achieve excellence in tourism in the Ha’il region. The results of the statistical analysis have given us the following elements: There are only four main factors that allow authorities to achieve excellence in tourism in the Ha’il region, namely ST, CP, HRS, and SC factors. Then we proceed with a second analysis, to determine the main factors of excellence in tourism that drive the achievement of sustainable development in tourism in the Ha’il region. For this reason, we applied an artificial intelligence method based on the unsupervised machine learning technique. The results obtained from the machine learning technique show that five factors determine the excellence in tourism and reveal the sustainable development of Ha’il’s tourism. These factors are ST, CP, FP, HRS, and GC. Consequently, we consider that all the factors found in both analyses are important to realise excellence in tourism and sustainable development in tourism. However, to achieve sustainable development in tourism in Ha’il, Saudi authorities must develop the three common factors found in the two analyses, namely ST, CP, and HRS.

The effect of the melt cooling rate on the atomic ordering of austenite and, as a consequence, on the martensitic transformation of a nonstoichiometric alloy of the Ni-Mn-In system has been studied. In-situ TEM observations revealed differences in the mechanism of phase transformations of the alloy subjected to different cooling conditions. It is shown that during quenching a high density of antiphase boundaries (APB) is formed and the alloy is in the austenite-martensitic (10M and 14M) state up to a temperature of 120K. In a slowly cooled alloy, a lower APB density is observed, and a two-stage transformation L21/B2 → 10M → 14M occurs in the range of 150–120 K.

Purpose: When it comes to improving citizen service delivery standard and processes, or broadly, management in government (MIG), many reform programs and improvement efforts are ongoing across different ministries, departments, and agencies. This paper is part of a larger empirical research where we are interested to know what those programs and projects are, and how they are doing, and what the gaps are. Design/methodology/approach: Analyzing the publicly available data on the government portal and donors’ website, this article provides an overall idea of current reforms in various places of government. In parallel, field research was conducted through visiting agency offices, observing office environment and mechanisms, and interviewing public managers who are working at district and sub-district level offices of directorates or agencies.Findings: As a trend, state-led development process and the traditional mode of administration have moved to New Public Management based quality and performance approach. All donors have their own strategy framework document like ‘Country Assistance strategy’, ‘Country Operations and Business Plan’, Logical Framework Document, Focus or Priority Streams, etc. Many of the projects are sectoral and agency or ministry specific and have an inherent limitations, due to ‘cadre’ based organizational structural arrangement. So, it is common ‘not to own the projects’, rather ‘using the fund as much as possible anyway within the given project duration’. When the fund ends, implementing units, either government or NGOs, abandon the projects. That is why many projects are actually half done without significant and sustained direction.Originality/value: We can conclude that the typical ‘top-down’ or ‘trickle down’ conception is still dominant in design and implementation of reforms programs and service quality efforts. So, how to reach systemically at the bottom where public managers provide services to citizens, needs even more deliberation.

Policies are adopted and implemented to achieve specific goals. In this regard, the Government of Zambia in 2019 adopted the higher education policy with many objectives which include, the expansion of access to higher education; reduction of gender and other forms of inequity in accessing higher education; the improvement of quality of higher education by increasing funding to higher education institutions, construction, and repair of infrastructure in higher and improvement in the provision of learning materials in higher education institutions (HEIs).This paper, therefore, sought to evaluate the higher education policy of 2019. The four criteria were used namely; effectiveness, equity, policy sustainability, and consistency. Other principles such as political and social acceptability of a policy were not used because the policy is already adopted and being implemented. Further, the principle of efficiency was not used because it would have been problematic to gauge the expenditure against the outcomes.The findings have revealed that the policy to some extent has been effective; some of the objectives such as increased access to higher education and reduction of inequality have been partially achieved. It has been established that the number of students pursuing higher education has been increased to 114,049 in 2020 from 91,969 in 2017. Further, in 2021, 48.5% of scholarships in public universities were awarded to female students while 51.5% were awarded to female students. Further, more students are encouraged to pursue science, technology, engineering, and mathematics (STEM); and more women are pursuing studies in STEM-related fields. However, the policy has not helped to achieve the quality of higher education as funding in public HEIs has not improved. Further, infrastructure remains very poor and inadequate; and access to update and relevant learning materials also remains a challenge in HEIs. However, the policy seems to be duplicated by the recent re-launched Technical Education Vocation Entrepreneurship Training (TEVET) national policy.Given the above findings, it has been recommended that the government among other things improve funding and build infrastructure in public HEIs. There is also a need to harmonise the TEVET national policy with the higher education policy.

Malassezia is a lipid-dependent genus of yeasts known for being an important part of the skin mycobiota. These yeasts have been associated in the development of skin disorders and cataloged as a causal agent of systemic infections under specific conditions, making them opportunistic pathogens. Little is known about the host-microbe interaction of Malassezia spp., and unraveling this implies the implementation of infection models. In this mini review we present different models that have been implemented in the fungal infections study with greater attention in Malassezia spp. infections. These models range from in vitro (cell cultures and ex vivo tissue), to in vivo (murine models, rabbits, guinea pigs, insects, nematodes, and amoebas). We additionally highlight the alternative models that reduce the use of mammals as model organisms, which have been gaining importance in the study of fungal host-microbe interactions. This is due to the fact that these systems have shown to have reliable results, which correlate with those obtained from mammalian models. Example of alternative models are Caenorhabditis elegans, Drosophila melanogaster, Tenebrio molitor, and Galleria mellonella. These are invertebrates that have been implemented in the study of Malassezia spp. infections in order to identify differences in virulence between Malassezia species.

Academic entrepreneurship focuses on commercialization of research. Even though it is practiced worldwide for decades, Bangladesh is a newcomer in this segment. In Bangladesh only 2 Universities have Technology Transfer Offices or TTOs which are established with the sole focus of commercialization of researches of the students and the faculty members of the Universities. This article focuses on worldwide practices of technology transfer and academic entrepreneurial activities and also explores the opportunities and challenges of such entrepreneurs through detail investigation of the existing body of knowledge. Apart from exploring the problems and prospect of academic entrepreneurship in Bangladesh, this article also introduces the concept of Full-Service Knowledge Transfer Office (KTO), which existing literatures do not offer. The authors believe that by establishing such KTOs as a self-sustaining body, it is possible for an academic entrepreneur to stimulate, support and sustain their activities in Bangladesh. The concept of full service KTOs can also become models for other nations, specially the developing ones, to establish and nurture a culture of academic entrepreneurship.

Far-red fluorescent reporter genes can be used for tracking cells non-invasively in vivo using fluorescence imaging. Here, we investigate the effectiveness of the far-red fluorescent protein, E2-Crimson (E2C), for tracking mouse embryonic cells (mESCs) in vivo following subcutaneous administration into mice. Using a knock-in strategy, we introduced E2C into the Rosa26 locus of an E14-Bra-GFP mESC line, and after confirming that the E2C had no obvious effect on the phenotype of the mESCs, we injected them into mice and imaged them over 9 days. The results showed that fluorescence intensity was weak, and cells could only be detected when injected at high densities. Furthermore, intensity peaked on day 4 and then started to decrease, despite the fact that tumour volume continued to increase beyond day 4. Histopathological analysis showed that although E2C fluorescence could barely be detected in vivo at day 9, analysis of frozen sections indicated that all mESCs within the tumours continued to express E2C. We hypothesise that the decrease in fluorescence intensity in vivo was probably due to the fact that the mESC tumours became more vascular with time, thus leading to increased absorbance of E2C fluorescence by haemoglobin. We conclude that the E2C reporter has limited use for tracking cells in vivo, at least when introduced as a single copy into the Rosa26 locus.

The development of sustainability, the improvement of the quality of life, and the protection of future generations have become of prime importance in light of climate changes and carbon emissions. Universities are at the top of institutions that should participate in creating an environmentally friendly infrastructure. This study thus aimed to explore the extent to which Saudi universities achieve sustainability in the light of the Saudi Green Initiative from the faculty members’ perspective. Surely, this investigation would produce a proposal to promote sustainability in Saudi universities. A questionnaire consisting of five dimensions, namely academic sustainability, community partnership, resource management, planning and administration, and innovation and leadership was developed and administered to 120 faculty members from five Saudi universities. The participants’ ratings of Saudi universities’ achievement of sustainability dimensions ranged from high to moderate. Based on the results, a proposal was offered to take sustainability in Saudi universities to a higher level.

Patients with cancer experience insomnia or sleep disturbances. This study aimed to explore whether the discrepancy between a patient's desired time in bed and total sleep time (DBST) index is a measurement tool for insomnia severity or sleep onset latency [SOL] in patients with cancer. This retrospective medical records review study gathered clinical information and rating scale scores including Insomnia Severity Scale (ISI), Cancer-related Dysfunctional Beliefs about Sleep scale (C-DBS), Patient Health Questionnaire-9 items (PHQ-9), State subcategory of State and Trait Anxiety Inventory, and Short form of Fear of Progression Questionnaire. Sleep indices of time variables (bedtime, sleep onset time, and wake-up time), duration variables [SOL, time in bed (TIB), time in bed for 24 hours (TIB/d), and duration from wake-up time to bedtime (WTB)], and the DBST index were calculated. The ISI score was predicted by PHQ-9 (β=0.34, P<0.001), C-DBS (β=0.17, P=0.034), and DBST index (β=0.22, P=0.004) with a significant correlation with the DBST index (r=0.19, p=0.020). The DBST index was significantly correlated with long SOL (r=0.23, P=0.005). Long SOL was predicted by early bedtime (β=0.18, P=0.045), short WTB (β=-0.26, P=0.004), and high DBST index (β=0.19, P=0.013). The DBST index was significantly correlated with a predicting variable each for insomnia severity and SOL in patients with cancer.

Character education is essential for the current millennial generation and must be applied in everyday life in the surrounding community. The character of the millennial generation is different from the previous generation, which requires us to pay more attention to character education which is starting to erode along with the times. The Millennial generation is a generation that in everyday life can never be separated from science and technology. In this digital era, the millennial generation has a social function of strength in technology. In this study, there are research questions that will be discussed in this article, namely the first regarding what problems occur in the millennial generation who occupy the digital era?. Second, what is the important role and influence of the digital era on character education for the millennial generation in Indonesia?. Writing this article uses a qualitative research method, namely a literature review study, where researchers use or look for references from journals or books. Samples of respondents were taken randomly from each region, and there were ten respondents. From this research, it is found that the millennial generation in the digital era chooses to use social media to access the latest news and information rather than reading print media that contains education. This article aims to find out the importance of character education for the millennial generation, which is starting to erode with the times in the digital era. Many people underestimate character education, especially for the current millennial generation. Therefore, we must implement educational programs at any level, especially in Indonesia, because the character shows the national identity. This article will discuss the vital role and influence of character education for millennials who live in the digital era to be aware of the importance of character education in citizenship.

This paper explores the application of fisheries management theories to broader environmental issues, including climate change and biodiversity conservation. It underscores the inherent trade-off in fisheries between yield and resource conservation, identifying harvesting as a significant environmental burden. Early recognition of the sustainability concept aimed to address challenges like economic discounts and the tragedy of the commons, contributing to the issue of overfishing. These insights extend beyond fisries to other environmental concerns, particularly climate change. The development of adaptive management, initially tailored to address uncertainties and non-stationarity in fisheries, has found application in diverse environmental issues. Recognizing humans as integral parts of ecosystems highlights the impossibility of achieving zero environmental impact when utilizing natural resources. The paper advocates for passive restoration to prevent overfishing, leveraging nature's resilience. While goals like complete biodiversity restoration are inherent in fisheries, their relevance may not be immediately apparent to other environmentalists. Despite ongoing discussions on the sustainability of ecosystem services, legislation often tends to favor the long-term maximization of fisheries yield. The paper calls for mutual understanding of theories and experiences across various environmental fields, including fisheries, to enhance collaborative efforts in each field.

Запропонована методика спрямована на визначення та прогнозування технічного стану елементів мосту, що може слугувати прогресивним інженерним інструментом для оцінки надійності та довговічності. Розроблено на основі фундаментальних досліджень, які узагальнюють досвід вивчення фізико-механічних і фізико-хімічних властивостей матеріалів мостових конструкцій, що експлуатуються в реальних умовах. Теоретичною основою методики є модель надійності та прогнозування залишкового ресурсу елементів мосту на основі теорії Маркова. Розроблена методика призначена для оцінки технічного стану окремих елементів мосту з подальшою комплексною оцінкою всієї конструкції. За показник технічного стану прийнята надійність при експлуатації. Цей кількісний показник надійності в моделі є критерієм для: оцінки рівня безпеки елементів мосту; ранжування елементів мосту за необхідністю для конкретних видів ремонту, реконструкції або заміни; стратегічне планування витрат на ремонт або реконструкцію в умовах обмеженого фінансування; прогнозування залишкового ресурсу елементів. Для застосування розробленої методики запропоновано алгоритм оцінки та прогнозування технічного стану мостів. Було проведено математичний експеримент розробленої методики, який підтвердив адекватність висунутої гіпотези, тобто використання моделі надійності та прогнозування залишкового ресурсу елементів мосту. По-перше, запропоновано триступеневий механізм уточнення технічного стану мосту, суттєво підвищення точності розрахунків. Тому розроблена методика має практичне значення і може слугувати основою для інформаційно-аналітичних систем управління станом мостів.

The survey findings reveal that rivers worldwide carry an annual sediment load of 15 billion tons into the sea, and the Yellow River basin alone contributes 1.6 billion tons of sand. Therefore, understanding the science of wind and sand in the Yellow River is crucial to ensuring the safe development of similar basins across China and the world. This study examines the midstream wind and sand area of the Xiliugou tributary, a part of the upper Yellow River. The researchers used a stepped sand collector combined with an anemometer to measure the sand transport flux at 0-50 cm height on various underlying surfaces of the basin. Then, they estimated the amount of wind and sand entering the Yellow River using a function model based on the measured factors. Furthermore, the team analyzed the particle size composition of wind-eroded sand to better understand the principles of wind and sand erosion and accumulation in the basin. The results of the study show that the sand transport flux per unit area varies significantly across different underlying surfaces. Moreover, the contribution of moving sandy land, semi-fixed sand, and fixed sand to wind and sand deposition in the Yellow River basin was 77.08%, 15.30%, and 7.62%, respectively. The vertical change of sand transport rate on the basin's surface demonstrates that the total sand transport rate is an exponential function of wind speed. Based on this relationship, the researchers estimated that the total annual average wind and sand entering the Yellow River basin via the Xiliugou tributary is approximately 8.09×105t. Due to the basin's unique geography and sand source, the particle size composition of wind-eroded sand differs between the east and west sides of the river channel. On the west side, desert sand, mainly fine sand, and very fine sand constitutes the sand source. Conversely, on the east side, sand collected in the riverbed by secondary wind erosion is the primary sand source. Furthermore, human activities have disturbed the grain composition, mainly comprising powder and clay particles. This phenomenon, known as "wind-blown mud and water-washed sand," is evident in this geographical unit. In conclusion, the Yellow River basin still faces significant ecological security hazards. Understanding the coupling relationship between desert-basin-sand and wind is the foundation for effectively controlling wind and sand flow into the Yellow River basin.

We suggest progress regarding the following six physics opportunities. List all elementary particles. Describe dark matter. Explain ratios of dark matter to ordinary matter. Explain eras in the history of the universe. Link properties of objects. Interrelate physics models. We use models based on Diophantine equations.

Local Productive Systems (hereinafter LPS) based on agro-food industries constitute alternative models of development in peripheral rural areas that are subject to internal and external dynamics and processes. The main objective of the research is to investigate the processes and their consequences on four SPLs based on the Iberian Pig Transformation Industry (hereinafter LPS-IPTI) in SW Spain: Fregenal de la Sierra, Higuera la Real, Cumbres Mayores and Jabugo. Using secondary data, a comparison is made between 2002 and 2020 to establish the changes, causes and consequences on the LPS-IPTI studied. The results obtained indicate (1) business and territorial concentration of LPS-IPTI; (2) productive and territorial specialisation in standardised products and quality products; (3) simplification of industrial processes; (4) loss of employment, especially female; (5) external control of companies in the sector which, accordingly, results in the loss of prominence of local actors in favour of foreign companies, reduced social capital and the progressive loss of ownership of the LPS.

The importance and near ubiquity of the Golden Ratio in disciplines like chemistry and biology is well known, but only recently has it come to light in areas pertaining to the Quantum domain. By using a modified tool-kit of hyper-complex numbers (known as Dimensional Gate Operators) and numerical analysis, we uncover a connection between hyper-dimensional objects, the Fibonacci sequence and that of quasiparticles and excitations. The results show that dimensionality increases in step with the Fibonacci sequence.

In the upper charged layers of the atmosphere, the plasma is very rarefied. The collisions between its molecules are almost non-existent, and the driving forces behind them are the Lorentz forces resulting from the electric and magnetic fields. For this reason, we are interested in studying the behavior of non-collision plasmas because of its essential applications, such as the movement of satellites in the charged atmosphere. In this paper, the flow problem of collisionless gaseous plasma is examined. For that propose, we solve the unsteady Vlasov-Maxwell system of non-linear partial differential equations analytically. Methods of moments and traveling wave parameters are used to acquire an exact solution. Specific macroscopic properties of collisionless gaseous plasma are calculated along with electrical and magnetic fields. Further, thermodynamic estimation, such as entropy and entropy production, is presented. Those calculations allow us to measure the consistency with the laws of non-equilibrium thermodynamics. Relations between internal energy modification participations are predicted using Gibbs' equation for collisionless plasma. The modification effect of internal energies due to electro-magnetic fields is found to be small compared with the internal energy change due to the effect of entropy. That is because these fields are self-induced by plasma particles due to the sudden movement of the rigid plane plate. The results are accomplished according to the typical argon gaseous plasma model. Three-dimensional diagrams showing the measured variables are drawn to investigate and discuss their behavior. The problem has many commercial applications for the movement of objects in the charged atmosphere.

The fundamental question in the field of sensor research is new directions of scientific fields, which play a vital role in the progress of science and technology. This study confronts this question here by developing a bibliometric analysis, which endeavors to explain the evolution of sensor research and new technologies that are critical to science and society. The database of Scopus concerning scientific documents and patents is used for statistical and computational analyses in these topics. Results suggest that emerging technological trajectories in sensors are wireless sensor networks, wearable sensors and biosensors. Main characteristics of these growing research fields and technologies in sensors are described for fruitful implications of research and innovation policy directed to science advances and technological change in society.

The purpose of this article is to review a two year long implementation of an electronic health record (EHR) system at the outpatient department of a private hospital in Kathmandu, possibly a first implementation of its kind in Nepal. Procedures: The strategy designed for EHR implementation was based on Professor John P. Kotter's work on successful change management. Main findings: We found that keeping a close watch on the social dynamics affecting adoption decisions among users of the system was crucial for implementing the EHR; this was partly because the project received limited support from an erratically changing hospital leadership and lacked an EHR system suited to the needs of the users. Conclusions: The implementation described in this article is a good lesson on moving from control to drift in information systems implementation, and we hope this work will be useful to health IT professionals working in the space of digital transformation in resource-constrained environments.

In this research paper, we implement the theory of the primorial function, to develop the Supremum and Infimum bounds for the sum of (log(p))². There are, however, considerable computational difficulties related to these bounds. Therefore, from a pragmatic point of view, a set of Upper and Lower bounds had been developed to bypass this issue. Despite the increased estimation error, the Upper and Lower bounds are still considered sufficiently accurate, while facilitating an easy and fast computation of the estimate of the sum.

In the paper, by virtue of a Lévy–Khintchine representation and an alternative integral representation for the weighted geometric mean, the authors establish a Lévy–Khintchine representation and an alternative integral representation for the Toader–Qi mean. Moreover, the authors also collect an probabilistic interpretation and applications in engineering of the Toader–Qi mean.

Understanding pollen and ovule fertility as factors influencing fruit and seed set is important in cassava breeding. Red light (RL) and plant growth regulators (PGRs) have been used to induce or enhance flowering and fruit set in cassava without any reference to effects on pollen viability or ovule fertilizability. This study investigated effects of field-applied RL and PGR on pollen viability and ovule fertilizability. Panels of cassava genotypes, with early or moderate flowering responses were used. RL was administered from dusk to dawn. Two PGRs, a cytokinin (6-benzyl adenine, BA) and an anti‑ethylene (silver thiosulphate, STS) were applied. Pollen viability was assessed basing on pollen grain diameter, in vitro stainability, in vivo germinability, ovule fertilizability and ploidy level. Treating flowers with RL led to increased pollen diameter from 143.6 to 148.5µm, stainability from 82.9 to 93.0%, ovule fertilizability from 52.0 to 56.9% in treated female flowers and 47.7 to 64.3% on using pollen from treated male flowers. Fruit set increased from 51.5 to 71.8% in RL-treated female flowers and from 53.7 to 71.1% when pollen from RL-treated male flowers was used. Seed set followed a trend similar to that of fruit set. Ploidy level of pollen from RL-treated flowers increased slightly and positively correlated with pollen diameter (R2 = 0.09*), ovule fertilization (R2 = 0.20*), fruit (R2 = 0.59*) and seed set (R2 = 0.60*); but negatively correlated with pollen stainability. Treating flowers with PGR did not affect pollen diameter and stainability, but increased ovule fertilizability from 42.9 to 64.9% and fruit set from 23.2 to 51.9% in treated female flowers and 31.3 to 54.7% when pollen from treated male flowers was used. Application of combined BA+STS on male flowers caused the highest ovule fertilizability, fruit and seed set efficiency, though this varied among study genotypes. These results show that RL and PGR treatment of flowers increases pollen viability and ovule fertilizability. This is important for planning pollination strategies in cassava breeding programmes.

The United Nations Sustainable Development Goals call for the eradication of poverty, and China has proposed the Rural Revitalization Strategy based on the achievements of its poverty alleviation efforts in 2020. As a vital component of this strategy, the impact of land transfer on farmers' income growth has become a hot topic in both theoretical and practical sectors. This paper utilizes data from the CFPS database for the years 2010-2018 to construct OLS regression models and a Heckman two-stage model to analyze the effects of land transfers on the incomes of different types and sources among farmers. The empirical results show: First, land transfers do promote income growth among farmers, but the effect is primarily positive for those transferring out land, with negligible impact on those acquiring land. Second, the impact of land transfers varies between different types of income for transferees and transferors. Wage income contributes up to 88.26% to the income growth of transferors, a significantly higher rate than the decrease in business income; however, the increase in business income for transferees does not offset the decline in wage income, leading to no significant change in overall income. Further sensitivity analysis using the Heckman two-stage model confirms the robustness of these findings. The conclusions of this study provide theoretical and empirical evidence to optimize land transfer policies, enhance participation in land transfers, and ultimately achieve the mission of rural revitalization.

Ovariectomy appears to be the best method to control the density of wild ungulate populations. The aim of the present study was to compare two surgical approaches, via the flank and midline, in mouflon’s ovariectomy in field conditions. Twenty female mouflons were enrolled in the study. The animals were divided randomly in two groups, Group F animals were gonadectomized via flank approach, while Group A animals were sterilized via linea alba access. The parameters evaluated were duration of surgery, duration of anaesthesia, recovery time, intra- and post-operative complications, intra-operative nociception and pain in the post-operative period. There were no intra- and post-operative complications. The evaluated parameters showed a very similar trend in both groups. Both techniques are found to be effective and safe in execution.

Recently, the indications for Cochlear Implant (CI) have also been extended to subjects with Single Sided Deafness (SSD) in order to restore binaural hearing. The primary objective of this study was to investigate the advantages of CI following one year of usage in SSD subjects. Secondarily we want to assess the long-term stability of the CI. 57 participants performed a complete audiological assessment (speech audiometry in quiet and in noise and localization test). For each was also evaluated subjective hearing profile (with Speech Spatial and Qualities_SSQ questionnaire) and the impact of tinnitus (with the use of Tinnitus Handicap Inventory_THI questionnaire) After one year of CI usage, we observed a significant improvement in speech-to-noise ratio, in sound localization abilities, in the Speech (p-value 0.001) and Spatial (p-value 0.001) subscales of the SSQ questionnaire and in THI questionnaire (p-value 0.001). The improvements in speech in noise and localization abilities and the reduction of the SSQ and THI questionnaires scores were maintained over time (6th to 60th month follow-up). Only eight participants did not fully utilize the CI. CI in SSD represents an effective method for improving speech recognition in noisy environments, restoring sound localization abilities, reducing tinnitus and improve subjective listening skills.

Malignant melanoma is one of the most aggressive and resistant tumor types which is often accompanied by poor prognosis when spread to nearby or distant tissues. Even though an increasing number of second-line therapies are available for cancer patients, the 5-year survival rate of melanoma patients with regional and distant metastases is still rather low. Therefore, there is an urgent need to develop new, highly efficient treatments. Melanocortin-1-receptor (MC1R) is a cell surface receptor for α-MSH. It is responsible for melanogenesis and is shown to be overexpressed on the surface of cancer cells in a subset of melanoma patients. Here, we designed and synthesized α-MSH analogs and conjugated them to daunomycin through oxime linkage. Using our peptide-drug conjugates (Dau-α-MSHs), we performed comparative in vitro and in vivo evaluations to reveal their suitability for tumor targeting. Firstly, the expression level of MC1R was determined in various melanoma cell lines via RT-qPCR. Then, we examined the antiproliferative effect of our Dau-α-MSHs, moreover we determined the cellular uptake profile and intracellular localization of Dau-α-MSHs. The most efficient Dau-α-MSHs were investigated in vivo using a murine xenograft melanoma model. We found that various cell lines show differential expression on the mRNA levels. We also showed that healthy primary cells have lower expression of MC1R compared to tumor cell lines. Moreover, the concentration-dependent cellular uptake profile of Dau-α-MSHs was detected and the compounds exhibited a great antiproliferative effect on melanoma cell lines. We also provided evidence that our novel Dau-α-MSHs can inhibit tumor expansion significantly and are suitable for targeted tumor therapy.

The non-structural protein (NS) and nucleoprotein (NP) of the severe fever with thrombocytopenia syndrome virus (SFTSV) encoded by the S segment are crucial for viral pathogenesis. They reside in viroplasm-like structures (VLS), but their interaction and their significance in viral propagation remain unclear. Here, we investigated the significance of the association between NS and NP during viral infection through in-silico and in-vitro analyses. Through in-silico analysis, three possible binding sites were predicted, at NSs1-32, NSs56-82, and NSs207-237. Rationally, three mutant NSs were developed by site-directed mutagenesis and tested for NP interaction by co-immunoprecipitation. NSsW61Y failed to interact with the nucleoprotein, which was substantiated by the conformational changes observed in the structural analyses. Additionally, molecular docking analysis corroborated that the NSW61Y mutant protein does not interact well compared to wild-type NS. Over-expression of wild-type NS in HeLa cells increased the SFTSV replication by five folds, but NSsW61Y exhibited 1.9-folds less viral replication than wild-type. We demonstrated that the W61Y alteration was implicated in the reduction of NS-NP interaction and viral replication. Thus, the present study identified a critical NS site, which could be targeted for development of therapeutic regimens against SFTSV.

Parkinson's Disease (PD) is a neurodegenerative disorder that affects the motor system of the human body. Currently, the available treatments are limited and often have undesirable side effects. In this context, the aim of this study was to develop a novel combinational formulation of Apomorphine and Quetiapine and evaluate its efficacy in a rat model of PD. The formulation was prepared using the solvent evaporation technique and characterized for its physicochemical properties. The in-vitro drug release was evaluated using the Franz diffusion cell method, and the pharmacokinetics of the combination was studied in rats. The behavioural and biochemical parameters were evaluated in the rats using the Rotarod, pole test, and biochemical assays. The results showed that the developed formulation had satisfactory physicochemical properties and exhibited sustained drug release. The pharmacokinetic studies showed that the combination exhibited a longer residence time than the individual drugs. The behavioural and biochemical parameters showed that the combination was effective in improving motor function and reducing oxidative stress. In conclusion, the developed Apomorphine and Quetiapine combination formulation showed promising results in improving motor function and reducing oxidative stress in rat model of PD. Further studies are required to evaluate the safety and efficacy of the developed formulation in humans.

The use of nanomaterials has been increasing in recent times, and they are widely used in industries such as cosmetics, drug, food, water treatment and agriculture. The rapid development of new nanomaterials demands a set of approaches to evaluate the potential toxicity and risks related to them. In this regard, nanosafety has been using and adapting already existing methods (toxicological approach), but the unique characteristics of nanomaterials demand new approaches (nanotoxicology) to fully understand the potential toxicity, immunotoxicity and (epi)genotoxicity. Also, new technologies, such as organ-on-chip and sophisticated sensors, are under development and/or adaptation. All the information generated is used to develop new in silico approaches trying to predict the potential effects of newly developed materials. The overall evaluation of how from the production to final disposition chain of nanomaterials is evaluated under Life Cycle Assessment (LCA), which is becoming an important element of nanosafety considering sustainability and environmental impact. In this review we give an overview of all these elements of nanosafety.

Biofouling is the unwanted adsorption of cells, proteins, or intracellular and extracellular bio-molecules that can spontaneously occur on the surface of metal nanocomplexes. It represents a major issue in bioinorganic chemistry because it leads to the creation of a protein corona, which can destabilize a colloidal solution and result in undesired macrophage-driven clearance, consequently causing failed delivery of a targeted drug-cargo. Hyaluronic acid (HA) is a bioactive, natural mucopolysaccharide with excellent antifouling properties, arising from its hydrophilic and polyanionic characteristics in physiological environments which prevent opsonization. In this study, hyaluronate-thiol (HA-SH) (MW 10 kDa) was used to surface-passivate gold nanoparticles (GNPs) synthesized using a citrate reduction method. HA functionalized GNP complexes (HA-GNPs) were characterized using absorption spectroscopy, scanning electron microscopy, zeta potential, and dynamic light scattering. GNP cellular uptake and potential dose-dependent cytotoxic effects due to treatment were evaluated in vitro in HeLa cells using ICP-OES and Trypan blue and MTT assays. Further, we quantified the in vivo biodistribution of intratumorally injected HA functionalized GNPs in Lewis Lung carcinoma (LLC) solid tumors grown on the flank of C57BL/6 mice and compared localization and retention with nascent particles. Our results reveal that HA-GNPs show overall greater peritumoral distribution (**p<0.005, 3 days post-intratumoral injection) than citrate-GNPs with reduced biodistribution in off-target organs. This property represents an advantageous step forward in localized delivery of metal nano-complexes to the infiltrative region of a tumor, which may improve the application of nanomedicine in the diagnosis and treatment of cancer.

To mitigate the COVID-19 infection, many world governments endorsed the cessation of non-essential activities, such as the school attendance. Thereby, forcing the evolution of the teaching model to the virtual classroom. In the present work we show the application of a modified version of the adapted COVID-19 stress scales (ACSS) which also included teaching anxiety and preparedness, and resilience for academic professionals in Mexico, during the unprecedented transformation of the education system undergone in the COVID-19 quarantine. Most of the studied variables: gender, age, academic degree, household occupants, having a disease, teaching level, teaching mode, work hours, resilience, teaching anxiety and preparedness, and fear of being an asymptomatic patient (FOBAP), showed significant statistical correlation between each other (p<0.050) and to the 6 areas of the ACSS (danger, contamination, social economical, xenophobia, traumatic stress and compulsive checking). Our results further showed that the perceived stress and anxiety, fell into the category of absent to mild with only the danger section of the ACSS falling into the moderate category. Finally, resilience generated throughout the quarantine, seems to be a predictor of the adaptation the academic professional has undergone to cope with stress.

Based on the geochemical analysis of the volcanic material from the sediment core AMK-340, central zone of the Reykjanes Ridge, we could detect two ash-bearing sediment units accumulated during the Termination I. They correlate to the Ash Zone I in the North Atlantic Late Quaternary sediments having an age of 12170-12840, within the Younger Dryas cold chronozone, and 13600-14540 years, within and Bølling-Allerød warm chronozone. The ash of the Younger Dryas unit is presented mostly by the mafic and persilicic material originated from the Icelandic volcanoes; Vedde Ash is presented in one sediment sample from this unit. The ash of the Bølling-Allerød unit is presented mostly by the mafic shards which are related to the basalts of the rift zone on the Reykjanes Ridge, having presumably the local origin. A detection of Vedde Ash helped to specify the timing of the previously reconstructed paleoceanographic changes for the Termination I in the point of study: a significant warming in the area could occur as early as 300 years prior to the end of the conventional Younger Dryas cold chronozone.

Microencapsulation of polyherbal formulation (PHF) extract was carried out by freeze drying method, by employing gum arabic (GA), gelatin (GE), and maltodextrin (MD) with their designated different combinations as encapsulating wall materials. Antioxidant components (i.e total phenolic contents (TPC),Total flavonoids contents (TFC), and total condensed contents (TCT)), antioxidant activity (i.e. DPPH, β-carotene & ABTS⁺ assays), moisture contents, water activity (aw), solubility, hygroscopicity, glass transition temperature (T_g), particle size, morphology, in vitro alpha-amylase and alpha-glucosidase inhibition and bioavailability ratios of the powders were investigated. Amongst all encapsulated products, T_B (5% GA and 5% MD) and T_C (10% GA) has proven to be the best treatments with respect to the highest preservation of antioxidant components and their antioxidant potential by DPPH and β-carotene assays and noteworthy for an ABTS⁺ assays, in addition, the aforesaid treatments also demonstrated lower moisture content, aw, particle size and higher solubility, hygroscopicity and glass transition temperature (T_g). All freeze dried samples showed irregular (asymmetrical) microcrystalline structures. Furthermore, T_B and T_C also illustrated the highest in vitro anti-diabetic potential due to great potency for inhibiting alpha-amylase and alpha-glucosidase activities. In the perspective of bioavailability, T_A, T_B and T_C demonstrated the excellent bioavailability ratios (%).Futhermore, the phytochemo-profiling of ethanolic extract of PHF was also revealed to find out the bioactive compounds.

The focus of this work lies in the construction of monitoring system designed in the form of a patch using a long-lasting potentiometric electrolyte concentration sensor from metal electrodes, in a galvanic cell configuration Mg(s)|NaCl(aq)|Cu(s). Initially, a mathematical analysis was conducted on the expected sensor output through the Nernst equation. The experimental phase involved conducting controlled tests in the laboratory using various molar concentrations of sodium chloride (NaCl) in aqueous solution. Results showed that the electrolyte sensor allows for monitoring electrolyte levels in NaCl in the range of 0.02 to 1 M/L, with electrode lifespan exceeding 10 days. On the other hand, when patch is using human sweat during controlled exercise routines, it showed the sensor's capability for monitoring changes in the subjects' hydration levels in real time. The sensor output potential is greater than 1.7 volts when the sensor electrodes are in contact with human sweat, which is equivalent to measuring molar concentrations at normal hydration and moderately high hydration levels. Sensor results indicate that the system can function in a self-powered manner without external batteries. Additionally, the extended lifespan of its electrodes allows for continuous monitoring of imbalances in the human body, showcasing the system capability for long-term health assessment.

Plastic contamination of small dimensions (

This paper introduces PatchFusion, an innovative approach for nonrigid tracking and reconstruction of deformable objects using a single RGB-D sensor. Existing methods face challenges in accurately capturing the rapid deformations of soft and flexible objects, thereby limiting their utility in diverse scenarios. Our approach overcomes this challenge by employing a dynamic patch-based framework that adapts to rapid inter-frame motions. Firstly, patch-wise rigid transformation fields for non-overlapping patches are solved via Iterative Closest Point (ICP) by incorporating geometric features as additional similarity constraints, thereby enhancing robustness and accuracy. Secondly, deformation optimization based on a nonrigid solver is applied to refine the coarse transformation fields. In order to enable simultaneous tracking and reconstruction of deformable objects, the patch-based rigid solver is designed to run in parallel with the nonrigid solver, serving as a plug-and-play module requiring minimal modifications for integration while enabling real-time performance. Following a comprehensive evaluation, PatchFusion showcases superior performance in effectively dealing with rapid inter-frame deformations when compared to existing techniques, rendering it a promising solution with broad applicability across domains such as robotics, computer vision, and human-computer interaction.

The satellite Earth observation (EO) sector is burgeoning with hundreds of commercial satellites being launched each year, delivering a rich source of data that could be exploited for societal benefit. Data streams from the growing constellation of commercial satellites are of variable quality, limiting the potential for their combined use in science applications that need long time-series data from multiple sources. The quality of calibration performed on optical sensors onboard many satellite systems is highly variable due to calibration methods, sensor design, mission objective, budget, or other operational constraints. A small number of currently operating well-characterised satellite systems with onboard calibration, such as Landsat-8/9, Sentinel-2, and planned future missions like the NASA Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder, the European Space Agency (ESA) Traceable Radiometry Underpinning Terrestrial and Helio Studies (TRUTHS), and LIBRA from China, are considered benchmarks for optical data quality due to their traceability to international measurement standards. This paper describes the concept of a space-based transfer calibration radiometer called the Satellite Cross-Calibration Radiometer (SCR) that would enable the calibration parameters from satellites such as Landsat-8/9, Sentinel-2, or other benchmark systems to be transferred to a range of commercial optical EO satellite systems while in orbit. A description of the key characteristics of the SCR to successfully operate in orbit and transfer calibration from Reference systems to Client systems is presented. A system like the SCR in orbit could complement SI-Traceable satellites (SITSats) to improve data quality and consistency and facilitate the interoperable use of data from multiple optical sensor systems for delivering higher returns on the global investment in EO.

Automation is the key aspect of science and technology field and refers to controlling the systems for efficient output requirements. The development of robotics and similar, technologies in 21st century is a vast topic of research and significant progress has been made on this field. This research study focuses on building a ribbon-cutting robot with a Bluetooth interface for event inaugurations. The entire system hinges on constructing a prototype that is mounted on a robotic car frame with four wheels and an Arduino controller. In this case, ribbons are cut using a nickel wire, and it may be paired with an Android device via Bluetooth or an application. The robot is one of the first steps toward the development of autonomous, cognitive robots and can be used in a variety of events. Efficient temperature monitoring is done with help of LM35 sensor and Bluetooth based communication in order to monitor the conditions and effectively control the actions for which robot is designed. The robot has significantly allowed authors for desired tests on ribbon cutting and final results obtained were very exciting for its desired application target. Ribbon-cutting robots find applications in various events, including inaugurations, exhibitions, and ceremonies. Their precision and novelty add value to such occasions.

A system to evaluate several facets of hand function for neuroprostheses-mediated tasks is proposed. It includes a platform that serves as a test bench, sensors for dynamometry, electromyography, sensorized glove, and interactive objects. The system methodically locates and assesses the motor points along the forearm, evaluates stimulation-induced fatigue, measures digit motion and forces exerted during ADL grasps, and evaluates nerve excitability to advance electrode designs. While the system is exclusively designed for neuroprostheses-mediated grasp, it can also be extended to generic grasp and object manipulation-based research.

Optical current sensors have been developed and improved in recent decades, and their use has been widespread in power systems, including smart grids. Like any measuring instrument or system, the result of its measurements is associated with a measurement uncertainty, which quantifies its precision. This article presents a review of the main uncertainty contributions that affect the quality and performance of optical current sensors.

We simulated the glass-blowing process to model a shell resonator, which is a key component in MRIG (Micro Rate Integrating Gyroscope), using the finite elements method to solve a non-isothermal problem. We also calculated the mechanical characteristics of the modeled resonator, including effective mass, eigenfrequencies, angular gain, and energy loss, to predict the resonator's performance as a gyroscope. One key aspect we addressed is the bending of the resonator's rim toward the stem during glass-blowing process. This phenomenon occurs due to increased heat loss at the mold's edge and reduced heat flux at the side of the Gaussian heat source. To mitigate rim bending and the subsequent reduction in capacitance between the rim and 3D electrodes, which can degrade performance in micro glass-blown shell resonators for gyroscopes, we propose two potential mold solutions. The first is using a short-stem mold, which requires extensive polishing to eliminate the bent rim. The second solution is using a mold with a suitable chamfer at the edge, resulting in a straight rim. To quantitatively compare resonators created by these two types of molds, we calculated the noise factor for predicting its gyroscope performance. From these calculations, we find out that using the chamfered mold enables us to increase in the resonator's effective mass, eigenfrequency, angular gain, and quality factor, consequently reducing the noise factor compared to using the short-stem mold. This simulation process will assist us in getting insight into understanding a shell resonator as a gyroscope, designing a mold and determining experimental conditions.

Millions of people worldwide experience visual problems nowadays. According to the recent WHO survey, approximately…… million people are blind. They become reliant on others because of this issue. According to recent studies, 108 various techniques are utilized to help the moment of people who are visually impaired. In this research we will employ infrasonic sound to improve the ability of blind persons to identify obstacles that comes in its way at the distance ranging from 2 to 3.5 maters. The concept was created by drawing inspiration from a mammal termed certain animals inherent navigational system. The infrasonic detection for the visually impaired people is a complicated procedures ,now we will simply discuss the obstacle finding mechanism in this article. The project uses an Arduino UNO microcontroller, infrasonic sensors, a buzzer powered by 5 volts , a vibrator, burning Arduino cable and a few connecting wires. On a cap that the blind people will wear all of this arrangement will be placed. High frequency sound is emitted by the infrasonic emitter picked up by the infrasonic receiver after reflecting off of the obstruction and then transmitted to the processor for additional required activity in the form of sound and vibration.

To facilitate wireless communication, ocean exploration, and various environmental and research applications, the underwater Internet of Things has been developed with an infrastructure of acoustic sensor networks. There has been a significant increase in failures and a decrease in the efficiency of the network due to the fluid and challenging underwater environment. Consequently, achieving quality of service (QoS) in underwater networks remains a research area. Supporting QoS in underwater sensor networks is challenging due to resource limitations such as processing power, memory, bandwidth, and power sources. The purpose of this study was to examine the service quality requirements as well as protocols that have been implemented in recent years. Finally, based on quality criteria, we have presented a routing solution based on fuzzy logic, which is more efficient than other recent methods regarding energy consumption rate, JFI, efficiency, and reliability.

Precision agriculture including camera-guided row detection and hydraulic steering are often used as an alternative because crop damage can be decreased and driving speed can be increased comparable to herbicide applications.The effects of different approaches as uncontrolled (UC), mechanical weed control (MWC), herbicide weed control (HWC) and mechanical + herbicide control (MWC+HWC) on weed density and yield of sugar beet were tested and evaluated in two trials (2021 and 2022) in South Transylvania at the tested intervals BBCH 19 and 31. Weed control efficacy (WCE) depends on the emergence of the weeds and a good timing of weed controls in all the trials and methods, though the highest yield of sugar beet roots was recorded in the treatment MWC+HWC, with an increase up to 12-15% (56.48 t ha-1) yield from HWC (50.22 t ha-1) and a yield increase of more than 35- 40% than MWC (42.34 t ha-1). Our trials show that is possible to increase yield and have less chemical applications with the introduction of the new precision technologies in agriculture included here the sensor-guided mechanical controls.

We report a simple and high-performance flexible strain sensor based on liquid metal nanoparticles (LMNPs) on polyimide substrate by laser induced deposition. The LMNPs were prepared by ultrasonic method, and then the femtosecond laser direct writing technology was used to induce the assembly and deposition of the LMNPs to form liquid metal microwires. Laser local sintering enhances the connection between particles, and a wearable strain sensor was fabricated with the high sensitivity as high as 76.18, the good linearity (a correlation coefficient of 0.999) in a wide sensing rage, the fast response/recovery time of 159 ms/120 ms. Attributed to these extraordinary strain sensing performances, the sensor can sense various dynamic strains in real time, monitor both subtle physiological activities and large human motions. It can be adhered to human skin, and well reflect the change of facial expression and realize real-time monitoring of facial expression. And the vocal cord vibration can be detected for speech recognition while the sensor attached to the outside of the throat.

Real-time multi-axis distributed tactile sensing is a critical capability if robots are to perform stable gripping and dexterous manipulation, as it provides crucial information about the sensor-object interface. In this paper, we present an optical-based 6-axis tactile sensor designed in a fingertip shape for robotic dexterous manipulation. The distributed sensor can precisely estimate local XYZ force and displacement at ten distinct locations, and provide global XYZ force and torque measurements. Its compact size, comparable to that of a human thumb, and minimal thickness allow seamless integration onto existing robotic fingers, eliminating the need for complex modifications to the gripper. The proposed sensor design uses a simple, low-cost fabrication method. Moreover, the optical transduction approach uses light angle and intensity sensing to infer force and displacement from deformations of individual sensing units that form the overall sensor, providing distributed 6-axis sensing. The local force precision at each sensing unit in the X, Y, and Z axes is 20.89 mN, 19.19 mN, and 43.22 mN, respectively, over an local force range of approximately ±1.5 N in X and Y and 0 to -2 N in Z. The local displacement precision in the X, Y and Z axes is 56.70 μm, 50.18 μm and 13.83 μm, respectively, over a local displacement range of ±2 mm in the XY directions and 0 to -1.5mm in Z (i.e., compression). Additionally, the sensor can measure global torques, Tx, Ty and Tz, with a precision of of 1.90 N-mm, 1.54 N-mm and 1.26 N-mm, respectively. The fabricated design is showcased by integrating it with an OnRobot RG2 gripper and illustrating real-time measurements during in simple demonstration task which generate changing global forces and torques.

Flood disasters have become an annual occurrence along the East Coast of North Sumatra (ECNS) and Medan City. Numerous studies have examined the causal factors flood disasters in this area, such as changes in land use, drainage issues, and population growth, but the intensity of flood disasters continues to rise. In this research, we focused on evaluating the unexplored factors of land subsidence and rising sea levels in this region. Our investigation uses multi-sensor satellite data and field surveys to conduct an assessment of the rate of land subsidence and sea level rise and assess their implications on flood disasters. This study highlights the potential of multi-sensor satellite data as a primary resource for assessing flood disasters in coastal areas and densely populated large cities. Furthermore, we propose a solution to reduce the negative impact of flood disasters by by engaging local communities and environmental enthusiasts in mangrove reforestation along the coastline.

Brushless Synchronous Machines (BSM) are replacing conventional synchronous machines with static excitation in generation facilities due to the absence of sparking and lower maintenance. However, this excitation system makes challenging measuring electric parameters in the rotor. This fact highly difficult the detection of ground faults, which are the most common type of electrical fault in electric machines. In this paper, a ground fault detection method for BSM is proposed. It is based on an inductive AC/DC rotating current sensor installed in the shaft. In case of a ground fault in the rotating parts of the BSM, a fault current will flow through the rotor’s sensor, inducing voltage in its stator. Analyzing the frequency components of the induced voltage the detection of a ground fault in the rotating elements is possible. The ground faults detection method proposed covers the whole rotor and discern between DC and AC sides. To corroborate the detection method, experimental tests have been performed using a prototype of this sensor connected to laboratory synchronous machines achieving satisfactory results.

Wireless sensor networks (WSN) are widely used in various fields such as military, industrial and transportation for real-time monitoring, sensing and data collection of different environments or objects. However, the development of WSN is hindered by several limitations, including energy, storage space, computing power and data transmission rate. Among these, the availability of power energy plays a crucial role as it directly determines the lifespan of WSN. To extend the life cycle of WSN, two key approaches are power supply improvement and energy conservation. Therefor, we proposed an energy harvesting system and a low energy consumption mechanism for WSN. Firstly, we delved into the energy harvesting technology of WSN, explored the utilization of solar energy and mechanical vibration energy to ensure a continuous and dependable power supply to the sensor nodes, and analyzed the voltage output characteristics of bistable piezoelectric cantilever. Secondly, we proposed a neighbor discovery mechanism that utilizes a separation beacon, is based on reply to ACK, and can facilitate the identification of neighboring nodes. This mechanism operates at a certain duty cycle ratio, significantly reduces idle listening time and results in substantial energy savings. In comparison to the Disco and U-connect protocols, our proposed mechanism achieves a remarkable reduction of 66.67% and 75% in the worst discovery delay, respectively. Furthermore, we introduced a data fusion mechanism based on integer wavelet transform. This mechanism effectively eliminates data redundancy caused by spatio-temporal correlation, results in a data compression rate of 5.42. Additionally, it significantly reduces energy consumption associated with data transmission by the nodes.

Fused silica glass is a material with outstanding mechanical, thermal and optical properties. Being a brittle material, it is challenging to shape. In the last decade, the manufacturing of monolithic flexible mechanisms in fused silica has evolved with the femtosecond laser-assisted etching process. However, instrumenting those structures is demanding. To address this obstacle, this article proposes to inscribe a Bragg Grating sensor inside a flexure and interface it with an optical fibre to record the strain using a spectrum analyzer. The strain sensitivity of this Bragg Grating sensor is characterized at 1.2 pm/μϵ (1 μϵ = 1 microstrain). Among other applications, deformation sensing can be used to record a force. Its use as a micro-force sensor is estimated. The sensor resolution is limited by our recording equipment to 30 μN over a measurement range above 10 mN. This technology can offer opportunities for surgery applications or others where precision and stability in harsh environments are required.

Millions of people worldwide are affected by diabetes, a chronic disease that continuously grows due to abnormal glucose concentration levels present in the blood. Monitoring blood glucose concentrations is therefore an essential diabetes indicator to aid in the management of the disease. Enzymatic electrochemical glucose sensors presently account for the bulk of glucose sensors in the market. However, their disadvantages are that they are expensive and are dependent on environmental conditions, hence affecting their performance and sensitivity. To meet the increasing demand, non-enzymatic glucose sensors based on chemically modified electrodes for the direct electrocatalytic oxidation of glucose are a good alternative to the costly enzymatic-based sensors currently on the market, and the research thereof continues to grow. Nanotechnology-based biosensors have been explored for their electronic and mechanical properties, resulting in enhanced biological signalling through the direct oxidation of glucose. Copper oxide and copper sulfide exhibit attractive attributes for sensor application, due to their non-toxic nature, abundance, and their unique properties. Thus, in this review, copper oxide and copper sulfide-based materials, are evaluated based on their chemical structure, morphology, and fast electron mobility as suitable electrode materials for non-enzymatic glucose sensors. The review highlights the present challenges of non-enzymatic glucose sensors that have limited their deployment into the market.

High-precision inertial sensors or accelerometers can provide us references of free-falling motions in gravitational field in space, and serve as the key payloads for gravity recovery missions. In this work, a systematic method of electrostatic inertial sensor calibrations for gravity recovery satellites is introduced, which is applied to and verified with the Taiji-1 mission. Taiji-1 is the first technology demonstration satellite of the ``Taiji Program in Space'', which, in its final extended phase in 2022, could be viewed as a gravity recovery satellite operating in the high-low satellite-to-satellite tracking mode. Based on the calibration principles, swing maneuvers with time span about 200 s and rolling maneuvers for 19 days were conducted by Taiji-1 in 2022. The inertial sensor's operating parameters including the scale factors, the center of mass offset vector and the intrinsic biased acceleration are precisely re-calibrated and are updated to the Taiji-1 science team. Data from one of the sensitive axis is re-processed with the updated operating parameters, and the performance is found to be slightly improved compared with former results. This approach could be of high reference value for the accelerometer or inertial sensor calibrations of the GFO, the Chinese GRACE-type mission, and the planned Next Generation Gravity Missions. This could also shed some light on the in-orbit calibrations of the ultra-precision inertial sensors for future GW space antennas because of the technological inheritance between these two generations of inertial sensors.

This paper presents for the first time the design of a microwave sensing setup for the potential monitoring and identification of red palm weevil (RPW) gender type. The microwave sensor consists of a planar two-port transmission line (TL) with a single complementary split-ring resonant (CSRR) inclusion etched from the bottom metallic layer. The CSRR sensor is placed on top of a customized non-conductive container. The microwave sensing setup has been designed, numerically demonstrated, fabricated and tested experimentally. Simulated results correlate quite well with the experimental data. Moreover, the sensitivity of the CSRR sensor when in close proximity to different RPW gender has been evaluated both numerically and experimentally. Based on the measured results from 15 RPW collected samples with different body sizes, different RPW gender types showed unique microwave signatures. Notable shift to the sensor's resonance frequency has been achieved, where on average a resonant frequency shift of 10% for adult RPWs was achieved, while 2.4% frequency change was obtained for larvae (young) RPWs. Hence, the proposed microwave sensing setup can be adopted in field trials to examine and differentiate between various RPW genders at various development stages.

Recently, new semantic segmentation and object detection methods have been proposed for direct processing of three-dimensional (3D) LiDAR sensor point clouds. LiDAR can produce highly accurate and detailed 3D maps of natural and man-made environments and is used for sensing in many contexts due to its ability to capture more information and its robustness to dynamic changes in the environment. In addition, the cost of LiDAR sensors has decreased in recent years, which is an important factor for many application scenarios. The challenge with 3D LiDAR sensors like the Velodyne HDL-64E S2 is that they can output large 3D data at up to 1,300,000 points per second, which is difficult to process in real time when applying complex algorithms and models for efficient semantic segmentation. Most existing approaches are either only suitable for relatively small point clouds or rely on computationally intensive sampling techniques to reduce their size. As a result, most of these methods do not work in real-time in realistic field robotics application scenarios, making them unsuitable for practical applications. Systematic point selection is a possible solution to reduce the amount of data to be processed, but although it is memory and computationally efficient, it selects only a small subset of points, which may result in important features being missed. To address this problem, we propose a new approach to semantic segmentation in forestry that uses a systematic sampling method in which the local neighbors of each point are retained to preserve geometric details. Our approach has been shown to process up to 1 million points in a single pass. It outperforms the state of the art in efficient semantic segmentation in large datasets such as Semantic3D. We also present a preliminary study on the performance of LiDAR-only data, i.e., intensity values from LiDAR sensors without RGB values for semi-autonomous robot perception.

Abstract: This work is presenting a water level control and monitoring system in a tank, by using the development boards Arduino Uno, NodeMCU ESP8266 and the ultrasonic sensor HC-SR04. The water tank is supplied through a pump controlled by the development board Arduino Uno by means of a relay. The author has issued a control algorithm for controlling the water level and a program in the development environment Arduino IDE that has been implemented and validated on the experimental stand. For monitoring the development board NodeMCU ESP8266 has been used that takes the information from the ultrasonic sensor HC-SR04 and sends it through Wi-Fi to the platform ThingSpeak. Based on the experimental results it has been found out that the water level control system in the tank provides the performances imposed through the designing stage, and the pump running has been automatically stopped when the limit, settled through the program for the water maximum level in the tank, has been reached. The measured value of the water level is shown on the LCD 1602 display. In the water circuit of the home consumers or irrigation systems supplied from the tank a pump controlled by means of a mobile phone has been installed. In order to implement this control system, the author has issued a program for another development board Arduino Uno, whilst for the mobile phone he used the application Arduino Bluetooth Control. The advantage of this water level control and monitoring system in the tank is given by the very low costs in comparison to the cost of an industrial type control system.

Vehicle safety promises to be one of the Advanced Driver Assistance System (ADAS) biggest benefits. Higher levels of automation remove the human driver from the chain of events that can lead to a crash. Sensors play an influential role in vehicle driving as well as in ADAS by helping the driver to watch the vehicle’s surroundings for safe driving. Thus, the driving load is drastically reduced from steering as well as accelerating and braking for long-term driving. The baseline for the development of future intelligent vehicles relies even more on the fusion of data from surrounding sensors such as Camera, Lidar and Radar. These sensors not only need to perceive in clear weather but also need to detect accurately adverse weather and illumination conditions. Otherwise, a small error could have an incalculable impact on ADAS. As most of the current study is based on indoor or static testing. In order to solve this problem, this paper designs a series of dynamic test cases with the help of outdoor rain and intelligent lightning simulation facilities to make the sensor application scenarios more realistic. As a result, the effect of rainfall and illumination on sensor perception performance is investigated. As speculated, the performance of all automotive sensors is degraded by adverse environmental factors, but their behaviour is not identical. Future work on sensor model development and sensor information fusion should therefore take this into account.

A novel flexible humidity sensor, incorporating gold nanoparticles (Au NPs) and a trifunctional organosilica compound, has been developed through the integration of sol-gel processing, free radical polymerization, and self-assembly techniques. The trifunctional organosilica was initially synthesized by modifying (3-mercaptopropyl)trimethoxysilane (thiol-MPTMS) with 3-(trimethoxysilyl)propyl methacrylate (vinyl-TMSPMA). Subsequently, a hydrophilic polyelectrolyte, [3(methacryloylamino)propyl]trimethyl ammonium chloride (MAPTAC), was grafted onto the MPTMS-TMSPMA gel. The Au NPs were assembled onto the thiol groups present in the MPTMS-TMSPMA-MAPTAC gel network. The compositional and microstructural properties of the Au NPs/MPTMS-TMSPMA-MAPTAC composite film were investigated utilizing Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM). The presence of thiol groups and mesoporous silica skeletons ensured the stability of the humidity-sensing film on the substrate under highly humid conditions, while the hydrophilic groups functioned as humidity-sensitive sites. This innovative humidity sensor demonstrated high sensitivity, acceptable linearity, minimal hysteresis, and rapid response time across a broad range of working humidity levels. Based on the complex impedance spectra analysis, hydronium ions (H₃O⁺) were determined to govern the conductance process of the flexible humidity sensor.

Melanoma is a type of highly malignant and metastatic skin cancer. In situ molecular imaging of endogenous levels of the melanoma biomarker tyrosinase (TYR) may decrease the likelihood of mortality. In this study we proposed the weakly fluorescent probe 1-(4-(2-(4-(dicyanomethylene)-4H-chromen-2-yl)vinyl)phenyl)-3-(4-hydroxybenzyl)urea (DCM-HBU), which releases a strong red-shifted fluorescent signal after a TYR-mediated oxidation followed by hydrolysis of the urea linkage. The large Stokes shift of the dye is owed to the recovery of the intramolecular charge transfer (ICT) effect. The resulting probe derivate shows a highly ratiometric fluorescence output. Furthermore, the simultaneous excitation by two near-infrared (NIR) photons of the released DCM-NH2 fluorophore could avoid the usual drawbacks, such as cellular absorption, autofluorescence and light scattering, due to an usually short wavelength of the excitation light on biological systems, resulting in images with deeper tissue penetration. In addition, the probe is useful for the quantitative sensing of TYR activity in vivo, as demonstrated in zebrafish larvae. This new ratiometric two photon NIR fluorescent probe is expected to be useful for the accurate detection of TYR in complex biosystems at greater depths than other one-photon excited fluorescent probes.

Recent deep learning frameworks draw a strong research interest in the application of ego-motion estimation as they demonstrate a superior result compared to geometric approaches. However, due to the lack of multimodal datasets, most of these studies primarily focused on a single sensor-based estimation. To overcome this challenge, we collect a unique multimodal dataset named LboroAV2, using multiple sensors including camera, Light Detecting And Ranging (LiDAR), ultrasound, e-compass and rotary encoder. We also propose an end-to-end deep learning architecture for fusion of RGB images and LiDAR laser scan data for odometry application. The proposed method contains a convolutional encoder, a compressed representation and a recurrent neural network. Besides feature extraction and outlier rejection, the convolutional encoder produces a compressed representation which is used to visualise the network's learning process and to pass useful sequential information. The recurrent neural network uses this compressed sequential data to learn the relation between consecutive time steps. We use the LboroAV2 and KITTI VO datasets to experiment and evaluate our results. In addition to visualising the network's learning process, our approach gives superior results compared to other similar methods. The code for the proposed architecture is released in GitHub and accessible publicly.

Desktop fused filament fabrication (FFF) 3D printers have been growing in popularity among hobbyist and professional users as a prototyping and low-volume manufacturing tool. One issue these printers face is the inability to determine when a defect has occurred rendering the print unusable. Several techniques have been proposed to detect such defects but many of these approaches are tailored to one specific fault (e.g., filament runout/jam), use expensive hardware such as laser distance sensors, and/or use machine vision algorithms which are sensitive to ambient conditions, and hence can be unreliable. This paper proposes a versatile, reliable, and low-cost system, named MTouch, to detect millimeter-scale defects that tend to make prints unusable. At the core of MTouch is an actuated contact probe designed using a low-power solenoid, magnet, and hall effect sensor. This sensor is used to check for the presence, or absence, of the printed object at specific locations. The MTouch probe demonstrated 100% reliability, which was significantly higher than the 74% reliability achieved using a commercially available contact probe (the BLTouch). Additionally, an algorithm was developed to automatically detect common print failures such as layer shifting, bed separation, and filament runout using the MTouch probe. The algorithm was implemented on a Raspberry Pi mini-computer via an Octoprint plug-in. In head-to-head testing against a commercially available print defect detection system (The Spaghetti Detective), the MTouch was able to detect faults 44% faster on average while only increasing the print time by 8.49%. In addition, MTouch was able to detect faults The Spaghetti Detective was unable to identify such as layer shifting and filament runout/jam.

Often, engineers with machining experience often judge machining state and tool life according to chips’ features. Engineers' experience is digitized in this study. During the cutting process, the cutting tool coming in contact with the workpiece produces a shear zone, which causes plastic deformation and shear slip. The chips closest to the shear zone can directly show the state of the tool and workpiece when the material is SKD61. This study used chip color, vibration, and current signal integration for prediction of machining state and cutting tool life. When the cutting tool wears increased, the chip surface color changed in the following way: purpleè purple blueè blue ècyan, or even green and yellow. When the cutting tool was in the accelerating wear phase, the color change was particularly obvious. The Back-Propagation Levenberg–Marquardt (BP-LM) predictive methodology was used to compare the predictive ability of voltage, vibration signal, and chip color. The Mean Absolute Percentage Error (MAPE) for the voltage signal was 12.28%, for the vibration signal it was 11.38%, and for the chip color combined with multi-sensor characteristics it was 7.85%. The MAPE of the chip color was the smallest. Using the General Regression Neural Network (GRNN) methodology, the MAPE for the voltage signal was 10.74%, for the vibration signal 7.96%, and for the chip color combined with multi-sensor characteristics was 6.59%. The MAPE of the chip color was the smallest. Obviously, the chip color combined with multi-sensor signals provided better predictive results than the vibration signal or voltage signal alone. There is currently no research on the usefulness of monitoring chip color for tool life prediction.

We propose the physical proof-of-concept of a new simple miniature pressure sensor based on the whispering gallery modes (WGMs) optically excited in a dielectric microsphere placed near a flexible reflective membrane, which acts as an ambient pressure sensing element. WGMs excitation is carried out by free-space coupling of optical radiation to a microsphere. The distinctive feature of proposed sensor design is double excitation of optical eigenmodes by forward and backward propagating radiation reflected from a membrane that causes WGMs interference in particle volume. The optical intensity of resulting resonant field established in the microsphere carries information about the exact position of the pressure-loaded reflecting membrane. The sensitivity of the proposed sensor strongly depends on the quality factor of the excited resonant mode, as well as geometrical and mechanical parameters of the flexible membrane. We propose to register not the displacement of the position of the WGM resonance, but the change in its amplitude under the influence of the change in the distance between the sphere and the mirror under the influence of pressure. Important advantages of the proposed sensor are miniature design (linear sensor dimensions depends only on the membrane diameter) and the absence of a mechanical contact of pressure-sensitive element with WGM resonator.

Herein, a novel cavity design of racetrack integrated circular cavity established on metal-insulator-metal (MIM) waveguide is suggested for refractive index sensing application. Over the past few years, we have witnessed several unique cavity designs to improve the sensing performance of the plasmonic sensors created on the MIM waveguide. The optimized cavity design can provide the best sensing performance. In this work, we have numerically analyzed the device design by utilizing the finite element method (FEM). The small variations in the geometric parameter of the device can bring a significant shift in the sensitivity and FOM of the device. The best sensitivity and FOM of the anticipated device are 1400 nm/RIU and ~12.01, respectively. We believe that the sensor design analyzed in this work can be utilized in the on-chip detection of biochemical analytes.

In the mold machining process, the cutting tool is worn with machining time, thereby affecting the surface accuracy, leading to poor workpiece dimensions, even fracture. At present, many studies have used multiple sensors to detect the machining conditions of cutting tool and workpiece, including indirect measurement method and direct measurement method. The indirect measurement method, which has been studied widely, mainly uses sensors to capture signals for subsequent data analysis; the direct measurement method mainly analyzes the state of cutting shear zone. Due to the cut-in of cutting tool in the machining process, the workpiece is dislocated rapidly, generating considerable amount of heat, which is transferred to the chips, inducing color change on the surface of chips. Many engineers with machining experience often judge the machining state and tool life according to the chips. The engineers' experience is digitized in this study, and indirect measuring sensors are used to predict the tool life, so as to attain the objective for smart manufacturing, the average percentage error of MAPE using single vibration and voltage eigenvalues as input features is 10%, the voltage signal characteristic values and vibration signal characteristic values are combined. Finally, the chip surface chromaticity eigenvalue is combined with signal characteristic value. The average prediction error of BP-LM method is 7.85%, the average prediction error of GRNN method is 6.59%. Therefore, when the eigenvalue of chip surface chromaticity is added to the prediction result, it can enhance the accuracy of cutting tool wear value prediction more effectively than single sensor signal characteristic value.

An 18.8–33.9-GHz, 2.26-mW current-reuse (CR) injection-locked frequency divider (ILFD) for radar sensor applications is presented in this paper. A fourth-order resonator is designed using a transformer with a distributed inductor for wideband operating of the ILFD. The CR core is employed to reduce the power consumption compared to conventional cross-coupled pair ILFDs. The targeted input center frequency is 24 GHz for radar application. The self-oscillated frequency of the proposed CR-ILFD is 14.08 GHz. The input frequency locking range is from 18.8 to 33.8 GHz (57%) at an injection power of 0 dBm without a capacitor bank or varactors. The proposed CR-ILFD consumes 2.26 mW of power from a 1-V supply voltage. The entire die size is 0.75 mm ´ 0.45 mm. This CR-ILFD is implemented in a 65-nm CMOS technology.

We characterize the performance of a system based on a magnetoresistor array. This instrument is developed to map the magnetic field, and to track a dipolar magnetic source in the presence of a static homogeneous field. The position and orientation of the magnetic source with respect to the sensor frame is retrieved together with the orientation of the frame with respect to the environmental field. A nonlinear best-fit procedure is used, and its precision, time performance, and reliability are analyzed. This analysis is performed in view of the practical application for which the system is designed that is an eye-tracking diagnostics and rehabilitative tool for medical purposes, which require high speed ($\ge 100$~Sa/s) and sub-millimetric spatial resolution. A throughout investigation on the results makes it possible to list several observations, suggestions, and hints, which will be useful in the design of similar setups.

Abundant of preparatory works have recognized that fluorescent sensors based on 8-aminoquinoline are popular tools to detect Zn2+ ions in environmental and biological applications. Along with these studies, researchers started to introduce a variety of carboxamido group into an 8-aminoquinoline molecule in forming 8-amidoquinoline derivatives. Therefore, this systematic review aims to introduce a general overview of the fluorophore 8-aminoquinoline as Zn2+ receptors and to provide comparisons of collected studies that related to 8-amidoquinoline derivatives as fluorophore probe of the sensor. According to PRISMA systematic searches strategy, 13 articles were analyzed for trends, research designs, results and discussion, subject samples, and remarks or conclusions. We found cross-sectional studies with four aspects in zinc sensing that have been targeted; binding studies via titration, detection's limit, interferences studies, and validation of the study. Hence, this paper also included assessments of those criteria and the trends of development of 8-amidoquinoline derivatives based-zinc fluorescent chemosensor. It also showed that most of the researches conducted in China. In conclusion, this study identified various research designs of fluorescent chemosensors based on 8-amidoquinoline prolong with the effectiveness and potential as a recognition probe to assist the detection of zinc. Hence, elucidation of those derivatives essential to be explored because more studies are needed to improve the sensing criteria of the zinc sensor

As the global human population increases, animal agriculture must adapt to provide more animal products while also addressing concerns about animal welfare, environmental sustainability, and public health. The purpose of this review is to discuss the digitalization of animal farming with Precision Livestock Farming (PLF) technologies, specifically biosensors, big data, and block chain technology. Biosensors are noninvasive or invasive sensors that monitor an animal’s health and behavior in real time, allowing farmers to monitor individual animals and integrate this data for population-level analyses. The data from the sensors is processed using big data-processing techniques such as data modelling. These technologies use algorithms to sort through large, complex data sets to provide farmers with biologically relevant and usable data. Blockchain technology allows for traceability of animal products from farm to table, a key advantage in monitoring disease outbreaks and preventing related economic losses and food-related health pandemics. With these PLF technologies, animal agriculture can become more transparent and regain consumer trust. While the digitalization of animal farming has the potential to address a number of pressing concerns, these technologies are relatively new. The implementation of PLF technologies on farms will require increased collaboration between farmers, animal scientists, and engineers to ensure that technologies can be used in realistic, on-farm conditions. These technologies will call for data models that can sort through large amounts of data while accounting for specific variables and ensuring automation, accessibility, and accuracy of data. Issues with data privacy, security, and integration will need to be addressed before there can be multi-farm databases. Lastly, the usage of blockchain technology in animal agriculture is still in its infancy; blockchain technology has the potential to improve the traceability and transparency of animal products, but more research is needed to realize its full potential. The digitalization of animal farming can supply the necessary tools to provide sustainable animal products on a global scale.

In this paper, we study the sensing performance of metasurfaces comprised by spiral-disk-shaped metallic elements patterned on polypropylene substrates, which exhibit localized surface plasmon resonances in the low-frequency region of the THz spectrum (0.2-0.5 THz). Optimal designs of spiral disks with C-shaped resonators placed near the disks were determined and fabricated. The experimentally measured transmittance spectra of samples coated with very thin photoresistive layers (d ~ 10^-4-10^-3 λ) showed good agreement with simulations. The resonance frequency shift Δf increases with increasing d, while saturating near d = 50 µm. The narrow-band magnetic dark modes excited on symmetrical spiral disks with a 90⁰-C-resonator demonstrated very high FOM values reaching 1670 [RIU·mm]^-1 at 0.3μm-thick analyte. The hybrid high order resonances excited on asymmetrical densely packed spiral disks showed about two times larger FOM values (up to 2950 [RIU·mm]^-1) as compared to symmetrical distantly spaced spirals that resembles the best FOM results found in literature for metasurfaces fabricated with a similar technique. The demonstrated high sensing performance of spiral disks is evaluated to be promising for bio-sensing applications in the THz range.

This research paper presents a new application of electroactive polyimide doped with gold nanoparticles (PI/AuNPs) as a chemiresistor sensor for detecting hydrogen sulfide gas. The synthesis of PI/AuNPs was done in a simple 3-step process of polymerization using the as prepared amine-capped aniline trimer (ACAT), followed by imidization, and doping. Spectral analyses via FTIR, LC-MS and ¹H-NMR confirmed the formation of amine-capped aniline trimer with a MW of 288 g mol^-1. Comparison of ACAT, BSAA, and PI FTIR spectra showed successful polymerization of the last, while XRD validated the incorporation of metal nanoparticles onto the polymer matrix showing characteristic diffraction peaks corresponding to gold. Furthermore, TEM, and FE-SEM revealed the presence of well-dispersed Au nanoparticles with an average diameter of about 60nm. The electroactive PI/AuNPs-based sensor showed a sensitivity of 0.29% ppm^-1 H₂S at a linear concentration range of 50 to 300 ppm H₂S (r = 0.9777). The theoretical limit of detection was found at 0.142 ppm or 142 ppb H₂S gas. The sensor provided a stable response reading at an average response time of 43±5 seconds, which was easily recovered after an average time of 99±5 seconds. The sensor response was highly repeatable and reversible with RSD values of 8.88%, and 8.60%, respectively. Compared with the performance of the conventional conducting polyaniline also doped with gold nanoparticles (PANI/AuNPs), the fabricated electroactive PI/AuNPs exhibited improved sensing performance making it a potential candidate in monitoring H₂S in the environment and for work-related safety.

Scanning magnetic microscopy is a new tool that has recently been used to map magnetic fields with good spatial resolution and field sensitivity. This technology has great advantages over other instruments; for example, its operation does not require cryogenic technology, which reduces its operational cost and complexity. Here, we describe the construction of a customizing scanning magnetic microscope based on commercial Hall-effect sensors at room temperature that achieves a spatial resolution of 200 µm. Two scanning stages on the x- and y-axes of precision, consisting of two coupled actuators, control the position of the sample, and this microscope can operate inside or outside a magnetic shield. We obtained magnetic field sensitivities better than 521 nT_rms/√Hz between 1 and 10 Hz, which correspond to a magnetic momentum sensitivity of 9.20 × 10^–10 Am². In order to demonstrate the capability of the microscopy, polished thin sections of geological samples, samples containing microparticles and magnetic nanoparticles were measured. For the geological samples, a theoretical model was adapted from the magnetic maps obtained by the equipment. Vector field maps are valuable tools for the magnetic interpretation of samples with a high spatial variability of magnetization. These maps can provide comprehensive information regarding the spatial distribution of magnetic carriers. In addition, this model may be useful for characterizing isolated areas over samples or investigating the spatial magnetization distribution of bulk samples at the micro and millimeter scales. As an auxiliary technique, a magnetic sweep map was created using Raman spectroscopy; this map allowed the verification of different minerals in the samples. This equipment can be useful for many applications that require samples that need to be mapped without a magnetic field at room temperature, including rock magnetism, the nondestructive testing of steel materials and the testing of biological samples. The equipment can not only be used in cutting-edge research but also serve as a teaching tool to introduce undergraduate, master's and Ph.D. students to the measurement methods and processing techniques used in scanning magnetic microscopy.

Volatile organic compounds (VOCs) are among the most abundant air pollutants. Their high concentrations can adversely affect the human body and therefore, early detection of VOCs is of outmost importance. Among the different VOCs, in this review paper, we have focused our attention on the monitoring of acetaldehyde by chemiresistive gas sensors using nanostructured semiconducting metal oxides. These sensors not only can provide a high sensing signal for detection of acetaldehyde, but also high thermal and mechanical stability and low price. This review paper is divided into three major sections. First, we will introduce acetaldehyde as the target gas and the importance of its detection. Then, the fundamentals of chemiresistive gas sensors will be briefly presented and, in the last section, a survey of literature on acetaldehyde gas sensors will be discussed. Acetaldehyde sensors working mechanism, their structures and configurations are reviewed. Finally, the future development outlook and potential applications are discussed, giving a complete panoramic view for researcher working and interested in acetaldehyde detection for different purposes in many fundamentals and applicative fields.

Background: medical devices are designed, tested and placed on the market in a highly regulated environment. Wearable sensors are crucial components of various medical devices: design and validation of wearable sensors, if managed according to international standards, can foster innovation while respecting regulatory requirements. Material and methods: the purpose of this paper is to take into consideration the upcoming EU Medical Device Regulation 2017/245 and the current and future IEC and ISO standards that set methods for design and validation of medical devices, with a focus on wearable sensors. Risk classification according to the regulation is described. The international standards IEC 62304, IEC 60601, ISO 14971 and ISO 13485 are reviewed to define regulatory restrictions during design, pre-clinical validation and clinical validation of devices that include wearable sensors as crucial components. Results: current and future regulatory restrictions are described, and an integrated method for design planning, validation and clinical testing is described Discussion: application of this method to design wearable sensors should be evaluated in the future in order to assess its potentially positive impact to fostering innovation and to the time-to-market of the device.

We improved a magnetic scanning microscope for measuring the magnetic properties of minerals in thin sections of geological samples at submillimeter scales. The microscope is comprised of a 200 µm diameter Hall sensor that is 142 µm from the sample; an electromagnet capable of applying to the sample up to 500 mT dc magnetic fields over a 40 mm diameter region; a second Hall sensor arranged in a gradiometric configuration to cancel the background signal applied by the electromagnet and reduce overall noise in the system; a custom-designed electronics to bias the sensors and provide adjustment for background signal cancelation; and a scanning XY stage with micrometer resolution. Our system achieves a spatial resolution of 220 µm with noise at 6.0 Hz of »300 nT_rms/(Hz)^1/2 in an unshielded environment. The magnetic moment sensitivity is 1.3 × 10⁻¹¹ Am².^1/2 We successfully measured the representative magnetization of a geological sample using an alternative model that takes into account the sample geometry and identified different micrometric characteristics in the sample slice.

A lensless camera is an ultra-thin computational-imaging system. Existing lensless cameras are based on the axial arrangement of an image sensor and a coding mask, and therefore, the back side of the image sensor cannot be captured. In this paper, we propose a lensless camera with a novel design that can capture the front and back sides simultaneously. The proposed camera is composed of multiple coded image sensors, which are complementary-metal-oxide-semiconductor~(CMOS) image sensors in which air holes are randomly made at some pixels by drilling processing. When the sensors are placed facing each other, the object-side sensor works as a coding mask and the other works as a sparsified image sensor. The captured image is a sparse coded image, which can be decoded computationally by using compressive-sensing-based image reconstruction. We verified the feasibility of the proposed lensless camera by simulations and experiments. The proposed thin lensless camera realizes super field-of-view imaging without lenses or coding masks, and therefore can be used for rich information sensing in confined spaces. This work also suggests a new direction in the design of CMOS image sensors in the era of computational imaging.

An ethanol vapor sensor based on a microfiber with quantum-dots (QDs) gel coating is proposed and demonstrated. The QDs gel was made from UV glue as the gel matrix and the CdSe/ZnS QDs with a concentration of 1mg/mL. The drawing and coating process were conducted by using a simple and low-cost home-made system. The bending, ethanol sensing, temperature response and time response tests were carried out, alternatively. The experimental results show that the fabricated sensor has a high sensitivity of -3.3%/ppm, a really low temperature cross-sensitivity of 0.17 ppm/℃ and a fast response time of 1.1s. The robust structure with ease of fabrication and excellent sensing performance render it a promising platform for real ethanol sensing application.

This paper proposes a hybrid medium access control (MAC) protocol for wireless sensor network (WSN) data gathering, employing unmanned aerial vehicles (UAV). The UAV sends a beacon frame periodically to inform sensor nodes regarding its presence. Afterward, each sensor node which receives beacon frame contends to send registration frame to the UAV. The UAV will transmit the second beacon frame to the registered nodes to notify their transmission schedule. The time-slot scheme is used for the transmission schedule. The transmission schedule of each sensor is determined based on their priority. Specifically, the priority of each sensor is determined during the registration process. Furthermore, the architecture of UAV-WSN data gathering system is introduced in this paper. Simulations are performed, showing that the proposed MAC protocol achieves fairness while enhancing network performance.

In wireless sensor networks, there is no a central controller to enforce cooperation between nodes. Therefore, nodes may generate selfish behavior to conserve their energy resources. In this paper, we address the problems of transmission power minimization and energy balance in wireless sensor networks using a topology control algorithm. We considered the energy efficiency and energy balance of the nodes, and an improved optimization-integrated utility function is designed by introducing the Theil index. Based on this, a topological control game model of energy balance is established, and it is proved that the topological game model is an ordinal potential game with Pareto optimality. Additionally, an energy-balanced topology control game algorithm (EBTG) is proposed to construct topologies. The simulation and comparison show that, compared with other topological control algorithms based on game theory, the EBTG algorithm can improve energy balance and energy efficiency while reducing the transmitting power of nodes, thus prolonging the network lifetime.

A The agri-food sector is in full renovation, continuously demanding new systems that allow farmers to facilitate their work. Efficient agricultural practices are essential for increasing farm profitability. Efficient agricultural practices can be increased by understanding and managing water neeeds. However, real-time monitoring of water needs is currently slow, and irrigation decisions are based on previous data or physical evidence. Furthermore, the prices of automatic systems for collecting data from several sources (soil and climate) are expensive and the autonomy is very low. Emerging Internet of Things (IoT) technologies such as wireless sensor networks can be used to collect vast amounts of data recorded via apps. By means of an LPWAN communication the farmer can know in real time the state of his crops thanks to a large number of sensors connected wirelessly and distributed across his farm. This paper presents a low consumption solution based on LoRaWAN technology. The wireless sensor node, called BoX, exhibits very low power since it has been optimized both in terms of hardware and software. The result is a higher degree of autonomy than commercial motes. That will allow the farmer to have all the information necessary to achieve an efficient management of his crops with full autonomy.

Linear regression is a basic tool in mobile robotics, since it enables accurate estimation of straight lines from range-bearing scans or in digital images, which is a prerequisite for reliable data association and sensor fusing in the context of feature-based SLAM. This paper discusses, extends and compares existing algorithms for line fitting applicable also in case of strong covariances between the coordinates at each single data point, which must not be neglected if range-bearing sensors are used. Besides, particularly the determination of the covariance matrix is considered, which is required for stochastic modeling. The main contribution is a new error model of straight lines in closed form for calculating fast and reliably the covariance matrix dependent on just a few comprehensible and easily obtainable parameters. The model can be applied widely in any case when a line is fitted from a number of distinct points also without a-priori knowledge of the specific measurement noise. By means of extensive simulations the performance and robustness of the new model in comparison to existing approaches is shown.

Current smartphones incorporate different types of sensors that allow us to know our spatial position, they give us information about pressure, speed, acceleration, time, acoustic level, and other different physical magnitudes. These smartphones measure each component of the magnetic field, bearing in mind that any current perpendicular to a magnetic field produces a small potential difference, transversal to the said current, being this voltage easily measurable by Hall sensors. With the implementation of three Hall sensors, and an appropriate app, we can measure the three components of the magnetic field vector, and with this we can obtain information and deduce properties of the physical systems considered. In this paper we are exploring the use of smartphones in a physics laboratory for freshman students. To do this, we have measured, using Hall sensors, the magnetic field created by a linear quadrature, and we have obtained, first of all, its dependence on the distance between the quadrupole and the magnetic sensor. The second purpose of this work is to show that the laboratory is a powerful tool that increases the significant learning of freshman students through advanced technological tools.

This paper presents a methodology to design sensor fusion parameters using real performance indicators of navigation in UAVs based on PixHawk flight controller and peripherals. This methodology and the selected performance indicators allows to find the best parameters for the fusion system of a determined configuration of sensors and a predefined real mission. The selected real platform is described with stress on available sensors and data processing software, and the experimental methodology is proposed to characterize sensor data fusion output and determine the best choice of parameters using quality measurements of tracking output with performance metrics not requiring ground truth.

Smart sensors based on graphene field effect transistor and biologically receptors are regarded as a promising nanomaterial that could be the basis for future generations of selective real-time monitoring of target analytes and smaller electronics. So the purpose of this paper is to provide details a real-time and selective explosive sensor based on GFETs and PDA-based lipid membranes coupled with biologically inspired TNT peptide receptors. Following an introduction, this paper describes the way of fabrication of the GFETs device by investigation methods for transferring graphene sheet from Cu substrates to target substrates, which is functionalized by the TNT peptide receptors, in order to offer a system which has the capability of answering the presence of related target molecules. Field effet transistor was fabricated using graphene as a channel and monitored by the source-drain current and back-gate voltage curves in the measurement. The transport property changed compared to that of the FET made by intrinsic graphene, that is, the Dirac point position moved from positive Vg to negative Vg, indicating the transition of graphene from p-type to n-type after annealing in TNT, and GFET sensor show good sensitivity and selectivity response.

Continuous object tracking in WSNs, such as monitoring of mud-rock flows, forest fires etc., is a challenging task due to characteristic nature of continuous objects. They can appear randomly in the network field, move continuously, and can change in size and shape. Monitoring such objects in real-time generally require tremendous amount of messaging between sensor nodes to synergistically estimate object’s movement and track its location. In this paper, we propose a novel twofold-sink mechanism, comprising of a mobile and a static sink node. Both sink nodes gather information about boundary sensor nodes, which is then used to uniformly distribute energy consumption across all network nodes, thus helping in saving residual energy of network nodes. Numerous object tracking schemes, using mobile sink, have been proposed in the literature. However, existing schemes employing mobile sink cannot be applied to track continuous objects, because of momentous variation of network topology. Therefore, we present in this paper a mechanism, transformed from K-means algorithm, to find the best sensing location of the mobile sink node. It helps to reduce transmission load on the intermediate network nodes situated between static sink node and the ordinary network sensing nodes. The simulation results show that the proposed scheme can distinctly improve life time of the network, compared to one-sink protocol employed in continuous object tracking.

A new and easy-to-make polymer film sensor was prepared by dip-coating technique and this film used as fluorescent chemosensor for the detection of metal ions in aqueous solution. The proposed film sensor exhibited dual emissions at 540 and 582 nm under a single excitation wavelength. The fluorescence behavior of this film sensor toward metal ions has been investigated using these two wavelengths. The proposed sensor was found to show selectivity and sensitive to Fe³⁺ ion when compared the other metal ions in deionized water with excellent photostability. Detection limit of the polymeric film sensor was calculated as 86.15 and 28.90 μM. The results showed that the sensor can be successfully applied to the determination of Fe³⁺ ions in aqueous media. Contact angle measurement of PAZU film probe was also investigated and the result showed that the proposed film probe has hydrophobic property.

Depth-sensing technology has led to broad applications of inexpensive depth cameras that can capture human motion and scenes in 3D space. Background subtraction algorithms can be improved by fusing color and depth cues, thereby allowing many issues encountered in classical color segmentation to be solved. In this paper, we propose a new fusion method that combines depth and color information for foreground segmentation based on an advanced color-based algorithm. First, a background model and a depth model are developed. Then, based on these models, we propose a new updating strategy that can eliminate ghosting and black shadows almost completely. Extensive experiments have been performed to compare the proposed algorithm with other, conventional RGB-D algorithms. The experimental results suggest that our method extracts foregrounds with higher effectiveness and efficiency.