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In this paper a novel low-cost multi-spectral optical fluorometer is presented and evaluated. The device uses a range of LEDs in the blue and violet regions of the electromagnetic spectrum and a mini-spectrometer to detect the emitted fluorescence in the UV to IR spectrum region. Custom built electronics and software were designed to control the system and the components were housed in bespoke 3D printed parts. A number of known fluorophores were tested to determine the capabilities of the fluorometer. Application of the device is demonstrated for the detection of chlorophyll a (Chl a) from laboratory grown algae and from environmental samples while analytical performance is established using both in vivo and extracted Chl a fluorescence and by comparison with a benchtop fluorometer.
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Clorofila , Plantas , Clorofila A , Eletrônica , SoftwareRESUMO
Understanding the dynamics of complex systems defined in the sense of Caputo, such as fractional differences, is crucial for predicting their behavior and improving their functionality. In this paper, the emergence of chaos in complex dynamical networks with indirect coupling and discrete systems, both utilizing fractional order, is presented. The study employs indirect coupling to produce complex dynamics in the network, where the connection between the nodes occurs through intermediate fractional order nodes. The temporal series, phase planes, bifurcation diagrams, and Lyapunov exponent are considered to analyze the inherent dynamics of the network. Analyzing the spectral entropy of the chaotic series generated, the complexity of the network is quantified. As a final step, we demonstrate the feasibility of implementing the complex network. It is implemented on a field-programmable gate array (FPGA), which confirms its hardware realizability.
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In situ water monitoring sensors are critical to gain an understanding of ocean biochemistry and ecosystem health. They enable the collection of high-frequency data and capture ecosystem spatial and temporal changes, which in turn facilitate long-term global predictions. They are used as decision support tools in emergency situations and for risk mitigation, pollution source tracking, and regulatory monitoring. Advanced sensing platforms exist to support various monitoring needs together with state-of-the-art power and communication capabilities. To be fit-for-purpose, sensors must withstand the challenging marine environment and provide data at an acceptable cost. Significant technological advancements have catalyzed the development of new and improved sensors for coastal and oceanographic applications. Sensors are becoming smaller, smarter, more cost-effective, and increasingly specialized and diversified. This article, therefore, provides a review of the state-of-the art oceanographic and coastal sensors. Progress in sensor development is discussed in terms of performance and the key strategies used for achieving robustness, marine rating, cost reduction, and antifouling protection.
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In this work, the problem of master-slave outer synchronization in different inner-outer network topologies is presented. Specifically, the studied inner-outer network topologies are coupled in master-slave configuration, where some particular scenarios concerning inner-outer topologies are addressed in order to disclose a suitable coupling strength to achieve outer synchronization. The novel MACM chaotic system is used as a node in the coupled networks, which presents robustness in its bifurcation parameters. Extensive numerical simulations are presented where the stability of the inner-outer network topologies is analyzed through a master stability function approach.
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In this paper, synchronization and encrypted communication transmissions of analog and digital messages in a deterministic small-world network (DSWN) are presented. In the first instance, we use a network with 3 coupled nodes in a nearest-neighbor (NN) topology, then the amount of nodes is increased until reaching a DSWN with 24 nodes. The synchronization and encrypted communication transmissions using a DSWN are presented experimentally by using Chua's chaotic circuit as node, in both analog and digital electronic implementations, where for the continuous version (CV) we use operational amplifiers (OA), and in the discretized version (DV) we use Euler's numerical algorithm implemented in an embedded system by using an Altera/Intel FPGA and external digital-to-analog converters.
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Marine biofouling, known as the unwanted accumulation of living organisms on submerged surfaces, is one of the main factors affecting the operation, maintenance and data quality of water quality monitoring sensors. This can be a significant challenge for marine deployed infrastructure and sensors in water. When organisms attach to the mooring lines or other submerged surfaces of the sensor, they can interfere with the sensor's operation and accuracy. They can also add weight and drag to the mooring system, making it more difficult to maintain the desired position of the sensor. This increases the cost of ownership to the point where it becomes prohibitively expensive to maintain operational sensor networks and infrastructures. Furthermore, the analysis and quantification of biofouling is extremely complex as it is based on biochemical methods such as the analysis of pigments such as chlorophyll-a as a direct indicator of the biomass of photosynthetic organisms, dry weight, carbohydrate analysis and protein analysis among others. In this context, this study has developed a method to estimate biofouling quickly and accurately on different submerged materials used in the marine industry and specifically in sensor manufacturing like copper, titanium, fiberglass composite, different types of polyoxymethylene (POMC, POMH), polyethylene terephthalate glycol (PETG) and 316L-stainless steel. To do this, in situ images of fouling organisms were collected with a conventional camera and image processing algorithms and machine learning models trained were used to construct a biofouling growth model. The algorithms and models were implemented with Fiji-based Weka Segmentation software. A supervised clustering model was used to identify three types of fouling to quantify fouling on panels of different materials submerged in seawater over time. This method is easy, fast and cost-effective to classify biofouling in a more accessible and holistic way that could be useful for engineering applications.
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In recent years, chaotic synchronization has received a lot of interest in applications in different fields, including in the design of private and secure communication systems. The purpose of this paper was to achieve the synchronization of the Méndez-Arellano-Cruz-Martínez (MACM) 3D chaotic system coupled in star topology. The MACM electronic circuit is used as chaotic nodes in the communication channels to achieve synchronization in the proposed star network; the corresponding electrical hardware in the slave stages receives the coupling signal from the master node. In addition, a novel application to the digital image encryption process is proposed using the coupled-star-network; and the switching parameter technique is finally used to transmit an image as an encrypted message from the master node to the slave coupled nodes. Finally, the cryptosystem is submitted to statistical tests in order to show the effectiveness in multi-user secure image applications.
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Recently, chaotic maps have been considered to design pseudorandom number generator (PRNG). However, some chaotic maps present security disadvantages, such as low uniformity and low randomness properties. Nowadays, chaos-based PRNGs are used as the main source for the development of cryptographic algorithms. In this work, to overcome such weaknesses, a novel 2D hyperchaotic map is proposed based on discrete-time feedback by using Hénon map and Sine map. In addition, the dynamics of the hyperchaotic map are enhanced by using the remainder after division function (rem), where better random statistical properties are obtained. A comparison is made between the enhanced Hénon-Sine hyperchaotic map (EHSHM) and the Hénon-Sine hyperchaotic map through Lyapunov exponent analysis, attractor trajectory, histograms and sensitivity at initialization. Then, 8-bit pseudorandom number generator based on the proposed hyperchaotic map (PRNG-EHSHM) is designed and the initial seed of the PRNG is calculated by a secret key of 60 hexadecimal characters. It is implemented in both MATLAB and Arduino Mega microcontroller for experimental results. A complete security analysis is presented from a cryptographic point of view, such as key space, floating frequency, histograms and entropy of the information. Moreover, the randomness is verified with the tests of the National Institute of Standards and Technology (NIST 800-22). Based on the security results obtained, the proposed PRNG-EHSHM can be implemented in embedded cryptographic applications based on chaos.
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Background: Nationally, underrepresented minorities represent a significant proportion of the first-generation student population. These students also tend to report lower levels of belongingness compared to their peers, which may impact their wellness and be an important factor in their academic success. This study aimed to explore whether status as a first-generation student was associated with belongingness amongst medical students. Methods: In 2019, a previously validated 16-item survey was used to examine potential disparities in belongingness amongst groups of first-generation medical students. Differences between groups were assessed using a Mann-Whitney U-test for each individual item and three composite groupings of items regarding social belonging, academic belonging, and institutional support. Results: First-generation to college and first-generation to graduate school students reported lower belongingness across most individual items as well as in all three composite groups. Conclusions: Given that peer relationships and institutional support play an important role in medical student belonging, these findings represent an opportunity to address the specific needs of individuals from underrepresented groups in medicine. Doing so can support the academic and professional success of first-generation students and help close the diversity gap in medicine.
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Water monitoring sensors in industrial, municipal and environmental monitoring are advancing our understanding of science, aid developments in process automatization and control and support real-time decisions in emergency situations. Sensors are becoming smaller, smarter, increasingly specialized and diversified and cheaper. Advanced deployment platforms now exist to support various monitoring needs together with state-of-the-art power and communication capabilities. For a large percentage of submersed instrumentation, biofouling is the single biggest factor affecting the operation, maintenance and data quality. This increases the cost of ownership to the extent that it is prohibitive to maintain operational sensor networks and infrastructures. In this context, the paper provides a brief overview of biofouling, including the development and properties of biofilms. The state-of-the-art established and emerging antifouling strategies are reviewed and discussed. A summary of the currently implemented solutions in commercially available sensors is provided and current trends are discussed. Finally, the limitations of the currently used solutions are reviewed, and future research and development directions are highlighted.
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STUDY OBJECTIVE: Few studies have compared continuous epidural infusion (CEI) against programmed intermittent epidural bolus (PIEB) epidural analgesia after major abdominal surgery. It has not been established whether the modality of epidural medication administration affects postoperative pain and other patient outcomes. The goal of this study was to compare the efficacy of PIEB against CEI in postoperative pain management after a broad range of surgeries with abdominal incisions, all managed in the context of an established enhanced recovery after surgery (ERAS) pathway. DESIGN: Prospective, randomized, controlled trial. SETTING: Postoperative acute care. PATIENTS: 120 patients scheduled for major surgery involving abdominal incisions with planned postoperative epidural analgesia were enrolled as study participants. INTERVENTIONS: All subjects received a standardized epidural solution containing ropivacaine 0.0625% and fentanyl 2 µg/ml. The CEI group received this solution as a continuous infusion, while the PIEB group received this solution as programmed intermittent boluses. MEASUREMENTS: The primary study outcome was the total local anesthetic used over the first 24 h post-operatively. Secondary outcomes included pain severity, pain interference, total opioid consumption, patient satisfaction, and adverse effects at 24, 48, and 72 h postoperatively. MAIN RESULTS: There was no difference in the primary outcome of total amount of local anesthetic administered in the first 24-hour postoperative period (PIEB: 123 mg [Interquartile Range (IQR): 114-136]; CEI: 126 mg [IQR: 120-134]). There were also no differences in average pain severity, total opioid consumption, patient satisfaction, number of PCEA requests and incidence of adverse events at 24, 48, and 72 h postoperatively. CONCLUSIONS: Our study suggests that within the context of an established ERAS program, PIEB and CEI modes of epidural analgesia can be equally efficacious and safe in providing postoperative analgesia after major abdominal surgery.
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The cyanobacterium Aphanizomenon gracile is the most widely distributed producer of the potent neurotoxin saxitoxin in freshwaters. In this work, total and extracellular saxitoxin and the transcriptional response of three genes linked to saxitoxin biosynthesis (sxtA) and transport (sxtM, sxtPer) were assessed in Aphanizomenon gracile UAM529 cultures under temperatures covering its annual cycle (12 °C, 23 °C, and 30 °C). Temperature influenced saxitoxin production being maximum at high temperatures (30 °C) above the growth optimum (23 °C), concurring with a 4.3-fold increased sxtA expression at 30 °C. Extracellular saxitoxin transport was temperature-dependent, with maxima at extremes of temperature (12 °C with 16.9% extracellular saxitoxin; and especially 30 °C with 53.8%) outside the growth optimum (23 °C), coinciding with a clear upregulation of sxtM at both 12 °C and 30 °C (3.8-4.1 fold respectively), and yet with just a slight upregulation of sxtPer at 30 °C (2.1-fold). Nitrate depletion also induced a high extracellular saxitoxin release (51.2%), although without variations of sxtM and sxtPer transcription, and showing evidence of membrane damage. This is the first study analysing the transcriptional response of sxtPer under environmental gradients, as well as the effect of temperature on putative saxitoxin transporters (sxtM and sxtPer) in cyanobacteria in general.
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Aphanizomenon/genética , Aphanizomenon/metabolismo , Saxitoxina/genética , Saxitoxina/metabolismo , Temperatura , Aphanizomenon/crescimento & desenvolvimento , Membrana Celular/metabolismo , Clorofila/metabolismo , Clorofila A , Genes BacterianosRESUMO
Copy number alteration (CNA) profiling of human tumors has revealed recurrent patterns of DNA amplifications and deletions across diverse cancer types. These patterns are suggestive of conserved selection pressures during tumor evolution but cannot be fully explained by known oncogenes and tumor suppressor genes. Using a pan-cancer analysis of CNA data from patient tumors and experimental systems, here we show that principal component analysis-defined CNA signatures are predictive of glycolytic phenotypes, including 18F-fluorodeoxy-glucose (FDG) avidity of patient tumors, and increased proliferation. The primary CNA signature is enriched for p53 mutations and is associated with glycolysis through coordinate amplification of glycolytic genes and other cancer-linked metabolic enzymes. A pan-cancer and cross-species comparison of CNAs highlighted 26 consistently altered DNA regions, containing 11 enzymes in the glycolysis pathway in addition to known cancer-driving genes. Furthermore, exogenous expression of hexokinase and enolase enzymes in an experimental immortalization system altered the subsequent copy number status of the corresponding endogenous loci, supporting the hypothesis that these metabolic genes act as drivers within the conserved CNA amplification regions. Taken together, these results demonstrate that metabolic stress acts as a selective pressure underlying the recurrent CNAs observed in human tumors, and further cast genomic instability as an enabling event in tumorigenesis and metabolic evolution.