The significant environmental issue of water pollution caused by emerging contaminants un-derscores the imperative for developing novel cleanup methods that are efficient, economically viable, and that are intended to operate at high capacity and under continuous flows at the in-dustrial scale. This study shows the results of the operational design to build a prototype for the retention at lab scale of pollutants residues in water by using as adsorbent material, insoluble polymers prepared by β-cyclodextrin and epichlorohydrin as a cross-linking agent. Laboratory in batch tests were run to find out the adsorbent performances against furosemide and hydro-chlorothiazide as pollutants model. The initial evaluation concerning the dosage of adsorbent, pH levels, agitation, and the concentration of pharmaceutical pollutants enabled us to identify the optimal conditions for conducting the subsequent experiments. The adsorption kinetic and the mechanisms involved were evaluated revealing that that the experimental data perfectly fit the pseudo second order model being the adsorption process mainly governed by chemisorption. According to the KF constants values of 0.044 (L/g) and 0.029 (L/g) for furosemide and hydro-chlorothiazide, respectively and determination coefficient (R2) higher than 0.9 for both com-pounds, Freundlich yielded the most favorable outcomes, suggesting that the adsorption process occurs on heterogeneous surfaces involving both chemisorption and physisorption processes. The maximum monolayer adsorption capacity (qmax) obtained by Langmuir isotherm reveal a saturation of the β-CDs-EPI polymer surface 1.45 times higher for furosemide (qmax = 1.282 mg/g) than hydrochlorothiazide (qmax = 0.844 mg/g). Based on these results, the sizing design and building of a lab scale model were conducted, which in turn will be used later to evaluate its performances working in continuous flow in a real scenario.

Although large language models demonstrate impressive capabilities, they sometimes generate irrelevant or nonsensical text, or produce outputs that deviate from the provided source input—an occurrence commonly referred to as hallucination. To mitigate this issue, we introduce a novel decoding method that incorporates both factual and hallucination prompts(DFHP), utilizing a contrastive output distribution to highlight the disparity in output probabilities between model predictions influenced by factual prompts and those affected by hallucination prompts. Experiments on both multiple-choice and text generation tasks show that our approach significantly enhances the factual accuracy of large language models without requiring additional training.

Acomys cahirinus is a unique Rodentia species with several distinctive physiological traits, such as precocial development and remarkable regenerative abilities. These characteristics render A. cahirinus increasingly valuable for regenerative and developmental physiology studies. Despite this, the structure and postnatal development of the central nervous system in A. cahirinus have been inadequately explored, with only sporadic data available. This study is the first in a series of papers addressing these gaps. Our first objective was to characterize the structure of the main visual thalamic region, the lateral geniculate complex, using several neuronal markers (including Ca2+-binding proteins, glutamic acid decarboxylase enzyme, and non-phosphorylated domains of heavy-chain neurofilaments) to label populations of principal neurons and interneurons in adult and newborn A. cahirinus. As typically found in other rodents, we identified three subdivisions in the geniculate complex: the dorsal and ventral geniculate nuclei (LGNd and LGNv) and the intergeniculate leaflet (IGL). Additionally, we characterized internal diversity in the LGN nuclei. The "shell" and "core" regions of the LGNd were identified using calretinin in adults and newborns. In adults, the inner and outer parts of the LGNv were identified using calbindin, calretinin, parvalbumin, GAD67, and SMI-32, whereas in newborns, calretinin and SMI-32 were employed for this purpose. Our findings revealed more pronounced developmental changes in LGNd compared to LGNv and IGL, suggesting that LGNd is less mature at birth and more influenced by visual experience.

This research follows the publication of recent scoping and systematic reviews of existing literature on vaccine literacy (VL), its relationship to vaccine hesitancy (VH), and associated variables, such as vaccination beliefs, attitudes, and behaviors towards immunization. In this review, 17 articles were selected, published between December 2022 and November 2023, in which VL tools were used, most of which support the notion of a negative association between VL and VH, although not confirmed by others. Moreover, the definitions of the variables under consideration were not homogeneous between studies, some aimed to evaluate the association of VL with vaccine confidence, while others were more focused on outcomes such as willingness to be vaccinated or vaccine uptake. The complexity of the factors underlying VL, and the heterogeneity of the methods applied in the studies, in particular the limitations of cross-sectional surveys, still make it difficult to have a comprehensive understanding of the role of VL. Therefore, it is important to develop future assessment tools that consider not just the measurement of psychological factors connected to the motivational aspect of VL, but also those related to knowledge and competencies. For this purpose, a theoretical framework is proposed, where the positioning of VL at the intersection between antecedents and beliefs/attitudes leading to behaviors explains why and how VL serves as a tool and a critical, direct, or mediating driver of vaccination choices, overcoming VH and increasing vaccination rates, operating at personal, as well as at organizational and community level.

Wounds are breaks in the continuity of the skin and the underlying tissues, due to external causes, such as cuts, blows and impacts, or even, during surgical interventions. Millions of people suffer minor or serious injuries, sometimes ending in death. Today, there are many commercially available products that promote healing from wounds. The high demand from the healthcare industry has created a huge market that continues to grow, fueling research and development of new wound healing products. In the present article, we review recent advances in wound healing products based on natural biopolymers, stem cells, and microRNAs. We analyze the advances of both, the commercial products and the products that are still in research phase, and we also include an overview of the opportunities, barriers, and regulatory issues for the commercialization of these products in the European, American, and Asian markets.

This study compares the effects of lecture-based instruction and process-oriented guided inquiry learning (POGIL)-based instruction on the self-efficacy performance of Grade 12 students. A quasi-experimental, pretest-posttest design was adopted to investigate and assess the impact of POGIL-based instruction versus lecture-based instruction on students’ performance as measured by three types of cognitive outcomes; Knowing, Applying and Reasoning (KAR). Two government high schools in Alain were selected as research sites, one for the boys and one for the girls. The total number of participants was approximately 110 students (N=110); 54 were assigned to treatment groups (25 girls and 29 boys), and 56 were assigned to control groups (27 girls and 29 boys). The treatment group was taught a circular motion unit in physics using POGIL-based instruction, while the control group was taught the unit using lecture-based instruction. The study's findings showed statistically significant differences between students of the control group and the treatment group in favour of the latter regarding their science performance, self-efficacy and science-related attitudes. Moreover, positive correlations were found between participants’ performance at the KAR test, self-efficacy and scientific attitudes towards scientific inquiry after the intervention. In conclusion, it is recommended to shift teaching towards POGIL-based instruction due to its positive impact on students’ performance and self-efficacy. It is also suggested to replicate the study to include government and private schools, elementary and high schools, teachers and advisors.

Cellulose nanocrystals (CNCs) are a kind of nano-inclusions that have experienced tremendous expansion in the material industry due to their outstanding mechanical qualities, sizable surface area, and capacity for functional tuning. Due to their vast potential, however, present practises fall short of fully using them. For example, employing CNCs in various matrices with various surface chemistries can be challenging; this problem tends to get worse if the focus is furthered on bio-based applications. This paper reviews the use of CNCs as fillers in natural and man-made polymers; we have explored in depth the production, characterisation, and of CNCs from various sources and their inclusion into various matrices. Surface alterations and the introduction of CNCs in biodegradable polymer can have a significant impact on several industrial behemoths such as tissue engineering and biomedical applications; therefore, pursue of current manuscript is extremely warranted. Throughout the manuscript various assembly techniques that involves alteration and adjustment of polymer network in building up a hydrogel with higher fracture energy and mechanical properties are also included. From rheological perspective the hydrogel processing is also discussed with some models routinely used in the literature to describe these hydrogels. Finally, bio-based hydrogels mechanically reinforced with CNCs such as Xanthan Gum, Alginate, protein, and polysaccharides were discussed.

Generating electricity from coal combustion is highly associated with ongoing pollution problems that negatively impact the environment. Coal fly ash (CFA) is a predominant waste by-product of coal combustion which is disposed of in exposed ash dams constructed in the vicinity of power stations. Its disposal requires a large piece of land and therefore more land is converted to unproductive disposal sites, degrading the ecosystem. This waste material is classified as a hazardous substance in South Africa due to unacceptable levels of inorganic and persistent organic pollutants and its potential for dust creation. CFA is recycled and sold to the building and construction sectors, but the rate of its utilization is far less than the production rate resulting to high volumes that is stockpiled in disposal sites. More than 500 million tons CFA is produced yearly and over 200 million tons yearly remain unused globally and more CFA will continue to be produced due to high consumer energy demands, especially in countries with heavy reliance on coal for power generation. In this context, the paper discusses production of CFA, pollution problems due to its disposal, examines existing gaps within the scope of ash dam restoration processes and presents opportunities offered by phytoremediation (a low-cost and environmentally friendly technology that utilizes plants to restore the degraded environments). Ecological restoration through the use of socio-economically valuable plants (aromatic plants, legumes and grasses) has potential in addressing societal challenges and consequently impacting positively the livelihood of communities.

The UK government and many international experts have pointed out that nuclear energy has an important role to play in the transition towards a decarbonized energy system since it is the only freely manageable very low-carbon energy technology with 24/7 availability to complement renewables. Besides current investments in light water reactor technologies, we need innovation for improved fuel usage and reduced waste creation, like offered by iMAGINE, for the required broad success of nuclear technologies. To allow quick progress into innovative technologies like iMAGINE and their regulation, a timely investment into urgently needed experimental infrastructure and expertise development will be required to assure the availability of capacities and capabilities. The initial steps to start the development of such a new reactor physics experimental facility to investigate molten salt fast reactor technology are discussed and a stepwise approach for the development of the experimental facility is described. The down selection to the choice for a diverse control and shutdown system is described through manipulating the reflector (control) and splitting the core (shutdown). The developed innovative core design of having the two core parts in two different rooms opens completely new opportunities and will allow to manifest the request for separated operational and experimental crews, as nowadays requested by regulators into the built environment. The proposed physical separation of safety relevant operational systems from the experimental room should on the one hand help to ease the access to the facility for visiting experimental specialists. On the other hand, the location of all safety relevant systems in a now separated access-controlled area for the operational team will limit the risk of misuse through third party access. The planned experimental programme described with the major steps: core criticality experiments, followed by experiments to determine the neutron flux, neutron spectrum, and power distribution as well as experiments to understand the effect of changes in reactivity and flux as a function of salt density, temperature and composition change.

A comprehensive Energy Audit of a Maintenance facility was performed to assess its energy performance and identify scope for improvement. The facility’s Energy Use Intensity (EUI) for 2022 was 404 kWh/m2 — more than double the Benchmark EUI for Maintenance facilities (151 kWh/m2) recommended by EnergyStar. Furthermore, the Load Factor for 2022 was 0.22, which is lower than the recommended minimum of 0.75 for an efficient building. The audit encompassed an in-depth evaluation of the building's structural and operational characteristics, comprising HVAC systems, lighting, building envelope, and energy-intensive machinery. An energy model of the building was developed to emulate the baseline building energy performance for 2022. Following the energy model's development and validation, an analysis was conducted to identify energy-intensive areas and opportunities for optimization. Energy Efficiency Measures were then formulated, focusing on improving energy efficiency while focusing on energy consumption reduction and GHG emission reduction. Results demonstrated the potential of Energy Audits and Modeling to enable significant reductions in energy consumption and promote sustainable building practices. Among the Energy Efficiency Measures considered, re-sizing and decarbonizing HVAC equipment contributed the most to energy savings, with a 100% decrease in natural gas and 37% decrease in electricity use annually.

The purpose of the research is to investigate the unique solvability of a nonlocal boundary value problem for a loaded equation of parabolic-hyperbolic type in a special domain. Methods: Using representations of a general regular solution, the existence and uniqueness of the problem posed is proved. Results: A new method for proving the unique solvability of nonlocal boundary value problems for one loaded equation of mixed type in a special domain has been formed and developed. Conclusions: The obtained results make it possible to solve some problems of genetics, immunology, transonic gas dynamics and thermal physics, which are associated with displacement.

Today, maritime transport is responsible for moving approximately 80 percent of the volume of world trade, which has favored Colombia, which, due to its geographical position, has managed to become one of the most competitive and dynamic economies in the world. South America. For this reason, this investigation is carried out in a port of their country, with the aim of identifying and analyzing restrictions or critical points that may cause delays in the unloading of goods, these would also cause delays in the loading of vehicles. To do this, it began with a diagnosis of the current situation through interviews with the operational personnel of the port, then a simulated model was designed in the ARENA software, in which it was observed that the weighing activities are where the queues were formed, this will cause a delay in the download. As possible solutions, it is recommended to senior management that a proper verification of the operation of the weighing equipment be carried out in order to unload goods more quickly. In addition, a replacement weighing equipment must be purchased. With this change, it would be possible to reduce inefficiencies or cost overruns caused by download delays, which are reducing the fluidity of the goods and the competitiveness of the organization

This code provides computational facilities to simulate current versus time during the charging of Li-ion cells at desire constant voltage by considering multiscale physical phenomena. This code only considers a powder of active materials (at microscale or nanoscale) and a small part of electrolyte around it as a half cell. Then it is extended to a complete cell by applying correct boundary conditions. This code is very useful by modifying code parameters to understand the effect of the complex shape of active materials powder (surface area and powder size), kind of electrolyte, and the applied voltages on the charging response of Li-ion cell. As a summary, a microscale approach to the design of Li-ion cells has been provided via this code.

Finding a solution for Euler's equations is a classic mechanics problem. This study revisits the problem with numerical approaches. For ease of teaching and research, a Maple code comprising 2 lines is written to find a numerical solution for the problem. The study's results are validated by comparing these with previous studies. Our results confirm the correctness of the principle of maximum moment of inertia of the rotating body, which is verified by thermodynamics. As an essential part of this study, the Maple code is provided.

The planning and decision-making for a distributed energy supply concept in complex actor structures like in districts calls for the approach to be highly structured. Here, a strategy with strong use of energetic simulations is developed, the core elements are presented and research gaps are identified. The exemplary implementation is shown using the case study of a new district on the former Oldenburg airbase in northwestern Germany. The process is divided into four consecutive phases, which are carried out with different stakeholder participation and use of different simulation tools. Based on a common objective, a superstructure of the applicable technologies is developed. Detailed planning is then carried out with the help of a multi-objective optimal sizing algorithm and Monte Carlo based risk assessment. The process ends with the operating phase, which is to guarantee a further optimal and dynamic mode of operation. The main objective of this publication is present the core elements of the planning processes and decision-making framework based on the case study and to find and identify research gaps that will have to be addressed in the future.

The IoT Internet of Things being a promising technology of the future. It is expected to connect billions of devices. The increased communication number is expected to generate data mountain and the data security can be a threat. The devices in the architecture are fundamentally smaller in size and low powered. In general, classical encryption algorithms are computationally expensive and this due to their complexity and needs numerous rounds for encrypting, basically wasting the constrained energy of the gadgets. Less complex algorithm, though, may compromise the desired integrity. In this paper we apply a lightweight encryption algorithm named as Secure IoT (SIT) to a quantized speech image for Secure IoT. It is a 64-bit block cipher and requires 64-bit key to encrypt the data. This quantized speech image is constructed by first quantizing a speech signal and then splitting the quantized signal into frames. Then each of these frames is transposed for obtaining the different columns of this quantized speech image. Simulations result shows the algorithm provides substantial security in just five encryption rounds.

Evaluating aviation emissions and examining the dispersion properties of contaminants are crucial for understanding atmospheric pollution. To more properly assess the pollutant emissions and dispersion of aircraft during the landing and take-off (LTO) cycle, and to more effectively address air pollution surrounding the airport resulting from flight operations, this study assessed emissions throughout the LTO phase utilizing Quick Access Recorder (QAR) data in conjunction with the first-order approximation method. An improved Gaussian diffusion model for mobile point sources is employed to examine the diffusion characteristics of contaminants. Additionally, CFD calculation outcomes for various exhaust velocities and wind speeds were utilized to validate the trustworthiness of the improved Gaussian model. The discussion also encompasses the influence of diffusion time, wind direction, wind speed, temperature gradient, and particle deposition on the concentration distribution of contaminants. The findings indicated that the Gaussian diffusion model aligned with the results of the CFD calculations. The diffusion distribution of contaminants around airports varies over time and is significantly influenced by atmospheric environmental factors, including wind direction, wind speed, and atmospheric stability.

The production of biomass fly ash has been increasing every year in Europe, reaching 5.5 million tons in 2020. Biomass fly ash is not yet accepted in the standards as a substitute material for cement in mortar and concrete. In a first approach, the substitution limit of biomass fly ash is determined by comparing the mechanical strengths, fresh state properties and hardened properties of mortars produced with biomass fly ash to those of mortars produced with classical coal fly ash. Then, masonry and rendering mortars have been designed with different substitution rates of biomass fly ashes from wood combustion in thermal power plant. Although there is an overall decrease in performance, mortars made with biomass ash retain properties that make them suitable for use in masonry or rendering.

While texturing of workpiece surfaces to promote lubrication in metal forming has been applied for several decades tool surface texturing is rather new. In the present paper tool texturing is studied as a method to prevent galling. Adopting a strip reduction test longitudinal pocket geometries oriented perpendicular to the sliding direction, with shallow pocket depth, small pocket angle to the workpiece surface and varying distance between pockets are investigated. The experiments reveal that the distance between pockets should be larger than the pocket width thereby creating a topography similar to flat table mountains to avoid mechanical interlocking in the valleys; otherwise an increase in drawing load and pick-up on the tools is observed. The textured tool surface lowers friction and improves lubrication performance provided that the distance between pockets is 2-4 times larger than the pocket width. Larger drawing speed facilitates escape of the entrapped lubricant in the pockets. Testing with low to medium viscosity oils leads to a low sheet roughness on the plateaus but also local workpiece material pick-up on the tool plateaus. Large lubricant viscosity results in higher sheet plateau roughness but also prevents pick-up and galling.

Shot peening is an attractive technique for fatigue enhanced performance of metallic components, because it promotes crack initiation retardation and later crack growth. Engineering design based on fatigue crack propagation predictions applying the principles of fracture mechanics is commonly used in aluminum structures for aerospace engineering. The main purpose of present work was to analyze the effect of shot peening on the fatigue crack propagation of the 7475 aluminum alloy, under both constant amplitude loading and periodical overload blocks. The tests were performed on 4 and 8 mm thickness specimen's with stress ratios of 0.05 and 0.4. The analysis of the shot-peened surface showed a small increase of the micro-hardness values, due to the plastic deformations imposed by shot peening. The beneficial effect of surface peening on fatigue crack growth rates is quite limited to an increasing near the threshold. The specimens’ thickness has only marginal influence on the crack propagation, in opposite to the stress ratio. Periodic overload blocks of 300 cycles promotes a reduction of the fatigue crack growth rate for both intervals of 7,500 and 15,000 cycles.

We propose a theoretical Photocurrent - Voltage characteristic (PC-V) model to assess the interfacial phenom-ena for a photo-electrochemical cell (PEC). The origin of voltage deficits and the distribution of the photocur-rent across the semiconductor-electrolyte interface (SEI) are reported for the cell. The model predicts the hole exchange current parameter to extract the cell polarization data at the SEI. The potential drop across the SEI across the cell is mapped for the n-type cells. The simulation results of the Pc-V model are used to differentiate the effect of the bulk and space charge region (SCR) recombination in the semiconductor cells. A deep neural network model is developed to assess the electron-hole transfer mechanism using the Pc-V characteristic curve. The applicability of the model is tested and validated with the real time data. The results show good agreement with the experimental data.

Objectives: the aim of this study was the assessment and monitoring of the safety and quality of the existing water supplies in Ibb and Taiz governorates from the microbial side and testing the quality of drinking water in the Ibb and Taiz governments and comparing it with the World Health Organization. Methods: the water samples (99 samples) taken from some water sources, distribution reservoirs, and different regions were studied for bacteriological analysis, in which they were inoculated into culture media using two methods: the presumptive test for the most probable number and the confirmatory test for bacterial identification. Results: the results indicated the non-existence of indicator bacteria that were used to indicate the possible presence of fecal bacteria among 24 (24.24%) water samples taken from Taiz governorate, while the presence of an unacceptable number of Escherichia coli in house tanks (30%) was indicated among 75 (74.25%) water samples taken from Ibb governorate. Conclusions: the results of the study in Taiz governorate show that the water is fit for human consumption, as well as the samples taken from water sources and distribution networks in Ibb governorate, but the results of the samples taken from house tanks showed that the water is not fit for human consumption and needs to be treated.

The primary objective of this systematic review study was to investigate the effectiveness, durability, and adverse events of PLLA treatment for aesthetic indications. The search strategy was performed in MEDLINE (Ovid). The electronic literature search of five databases was performed, from the inception of the databases until 12th of February 2024. This was to identify randomized clinical trials that assessed PLLA treatment in adult individuals exhibiting facial aging and/or facial lipoatrophy. Risk of bias was assessed using the Cochrane Risk-of-Bias Tool for Randomized Trials (RoB 2). Eleven RCTs out of 1467 identified citations were included. Four studies showed increased dermal thickness, significant improvement in facial lipoatrophy severity and aesthetic clinical scores, after PLLA treatment with its effects sustained for at least 25 months. Two studies demonstrated the superiority of PLLA over injectable human collagen. Also, three studies showed positive results favoring PLLA when compared with PH gel in lipoatrophy severity, trans epidermal water loss, skin quality, elasticity, and patient satisfaction. All adverse events were mild-to-moderate in intensity, and the main ones worth noting were bruising, hematoma, tenderness, nodules, and edema. Five out of 11 studies were considered as high risk of bias. The evidence on the effectiveness and safety of PLLA for facial rejuvenation is of low quality; thus, the reported high effectiveness, safety, and long-lasting effects for this purpose, should be further investigated.

The fulfillment of rights to maternal healthcare is a key factor for wellbeing of woman. However, there is a lack of instrument to know the experience of women during maternity to bind the monitoring. The aim of this study was to validate an instrument to measure the woman’s perception of the fulfillment of rights during healthcare in pregnancy, childbirth and immediate postpartum. The instrument consist in 50 items was screening by an exploratory factor analysis. Additionally, the final version of the instrument consists in 29 items which was validate by confirmatory factor analysis and know-group validity. The instrument was applied in 185 Spanish women. The global Aiken’s V of initial instrument proposal was 0.89. Process resolves an instrument with 5 factors (information, privacy, consent, support, and participation) that explained the 60% of the total variance. The score of the instrument was correlated with resilience, maternity beliefs, and positive and negative affect. External validation showed relations with age, gravida, and number of labors. Additionally, the reliability Cronbach´s was 0.93 [0.91; 0.94]. In conclusion, the instrument developed is consistent and has appropriate psychometric properties for assess the fulfillment rights maternity healthcare.

Digital health has added numerous promising solutions to enhance the health and wellness of people with neurocognitive disorders (NCDs) and their informal caregivers: (1) Background: It is important to get a comprehensive view of currently available technologies, their outcomes, and conditions of success to inform recommendations regarding digital health solutions for people with NCDs and their caregivers. This environmental scan was performed to identify the features of existing digital health solutions relevant to the targeted population. This work reviews currently available digital health solutions and their related characteristics to develop a decision support tool for older adults living with mild or major neurocognitive disorders and their informal caregivers. This knowledge will inform the development of a decision support tool to assist older adults and their informal caregivers in their search for adequate digital health solutions according to their needs and preferences, based on trustable information.; (2) Methods: We conducted an environmental scan to identify digital health solutions from a systematic review and targeted searches in grey literature covering the regions of Canada and Europe. Technological tools were scanned based on a preformatted extraction grid. We assessed their relevance based on selected attributes and summarized findings; (3) Results: We identified 100 available digital health solutions. The majority (56%) were not specific to NCDs. Only 28% provided scientific evidence of their effectiveness. Remote patient care, movement tracking, and cognitive exercises were the most common purposes of digital health solutions. Most solutions were presented as decision aid tools, pill dispensers, apps, web, or a combination of these platforms. (4) Conclusions: This environmental scan allowed the identification of current digital health solutions for older adults with mild or major neurocognitive disorders and their informal caregivers. Findings from the environmental scan highlight the need for additional approaches to strengthen digital health interventions for the well-being of older adults with mild and major NCDs and their informal and formal healthcare providers.

Care coordination (CC) for children with special healthcare needs and medical complexity (CSHCN-CMC) is challenging, and medication management is especially difficult for providers, parents/caregivers, and patients alike. While numerous strategies for CC have been suggested and implemented, barriers to medication optimization remain. The report describes the creation of a pediatric clinical pharmacotherapy practice, related standard operating procedures to assure consistent application of screening tools and care provision through comprehensive medication management (CMM), and establishment of a collaborative practice agreement (CPA) to guide drug therapy delegation, monitoring, and modification. The methodology of a prospective case series is also presented to highlight drug therapy problems and their resolution in CSHCN-CMC. Future opportunities to expand the practice for engagement in population health management as well as prior authorization activities on behalf of physicians will be discussed.

Retinitis pigmentosa (RP) is a heterogeneous inherited retinal disorder. Mutations in KIZ cause autosomal recessive (AR) RP. We aimed to characterize the genotype, expression pattern, and phenotype in a large cohort of KIZ cases. Sanger and whole exome sequencing were used to identify KIZ variants. Medical records were reviewed and analyzed. Thirty one patients with biallelic KIZ mutations were identified: 28 homozygous for c.226C>T (p.R76*), 2 compound heterozygous for p.R76* and c.3G>A (p.M1?), and one homozygous for c.247C>T (p.R83*). c.226C>T is a founder mutation among patients of Jewish descent. Clinical parameters were less severe in KIZ compared to DHDDS and FAM161A cases. RT-PCR analysis in fibroblast cells revealed the presence of four different transcripts in both WT and mutant samples with a lower percentage of the WT transcript in patients. Sequence analysis identified an exonic sequence enhancer (ESE) that includes the c.226 position which is affected by the mutation. KIZ mutations are an uncommon cause of IRD worldwide, but are not rare among Ashkenazi Jews. Our data indicate that p.R76* affect an ESE which in turn results in pronounced skipping of exon 3. Therefore, RNA-based therapies might show low efficacy since the mutant transcripts is spliced.

Although the neurofilament light chain (NfL) is used as a biomarker for neurodegenerative decline, its use in surgery- and anaesthesia-induced acute cognitive dysfunction remains controversial. We aimed to synthesise the evidence to explore the potential of NfL as an established biomarker for perioperative neurocognitive disorders (PND). We systematically searched the PubMed, EMBASE, MEDLINE, Cochrane Library electronic databases, and Cochrane Central Registry of Clinical Trials. Our results show that CSF NfL levels positively correlated with blood NfL levels (r = 0.63; 95% confidence interval [CI], 0.42-0.77). The pooled standardised mean difference (SMD) showed a significantly higher preoperative CSF NfL levels (SMD = 0.27; 95% CI, 0.07-0.47) and both pre- and postoperative blood NfL levels (SMD = 0.53, 95% CI, 0.40-0.66 and SMD = 0.58, 95% CI, 0.43-0.73) in the postoperative delirium (POD) group. Postoperative blood NfL levels were significantly elevated in both POD group (SMD = 0.49; 95% CI, 0.34-0.64) and no-POD group (SMD = 0.67; 95% CI, 0.53-0.81). Our meta-analysis indicates that NfL may serve as a potential biomarker for POD, and elevated preoperative blood NfL levels could be a risk factor for POD. Further studies are needed to confirm the association of CSF/blood NfL levels with other PND types.

Mass spectrometry (MS) has revolutionized clinical chemistry, offering unparalleled capabilities for biomolecule analysis. This review explores the growing significance of MS, particularly when coupled with liquid chromatography (LC-MS), in identifying disease biomarkers and quantifying biomolecules for diagnostic and prognostic purposes. The unique advantages of MS in accurately identifying and quantifying diverse molecules have positioned it as a cornerstone in personalized medicine advancement. MS-based technologies have transformed precision medicine, enabling comprehensive understanding of disease mechanisms and patient-specific treatment responses. LC-MS has shown exceptional utility in analyzing complex biological matrices, while high-resolution MS has expanded analytical capabilities, allowing detection of low-abundance molecules and elucidation of complex biological pathways. The integration of MS with other techniques, such as ion mobility spectrometry, has opened new avenues for biomarker discovery and validation. As we progress towards precision medicine, MS-based technologies will be crucial in addressing the challenges of individualized patient care, driving innovations in disease diagnosis, prognosis, and treatment strategies.

Omega-3 fatty acids (ω-3 FAs) are important fatty acids having the beneficial roles in human health including reducing blood pressure, lowering the risk of cardiovascular disease and exerting anti-inflammation activities. Omega-3 FAs were mainly found in fish oils, therefore, determination of these FAs is very important. This study highlighted the employment of FTIR spectroscopy combined with multivariate data analysis for determination of ω-3 FAs in fish oils. Fish oils were obtained from the extraction of corresponding fishes and subjected to purification. The oils were further subjected to FTIR spectroscopic measurement at mid infrared region (4000-450 cm-1). Fatty acid compositions of ω-3 FAs namely eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) were determined using gas chromatography with flame ionization (GC-FID), and the results from GC-FID were used as actual values. Two multivariate regressions along with wavenumbers regions or their combinations were optimized and compared to provide the best condition for prediction of EPA and DHA in fish oils. The results showed that partial least square regression (PLSR) was suitable for prediction of DHA applying the variable of absorbance values of the second derivative spectra, with the values of coefficient of determination (R2) of 0.9916 and 0.9316 in calibration and validation models, respectively. The values of root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) obtained were 0.789 and 2.53. While, prediction of EPA was performed using principal component regression with R2 value of > 0.72 and low values of RMSEC and RMSEC. It can be concluded that the combination of FTIR spectra and multivariate regression provides the effective tools and alternative GC-FID method for the prediction of EPA and DHA in fish oils.

This article compares the predictive capabilities of six models namely the Linear Discriminant Analysis (LDA), Logistic Regression (LR), Support Vector Machine (SVM), XGBoost, Random Forest (RF) and Deep Neural Network (DNN) to predict the default behaviour of credit card holders in Taiwan using data from the UCI machine learning database. Python programming language was used for data analysis. Statistical methods were compared with machine learning algorithms using the confusion matrix measured in metric terms of prediction accuracy, sensitivity, specificity, precision, G-mean, F1 score, ROC and AUC. The dataset contains 30,000 credit card user’s information with 6636 default observations and 23,364 non-default cases. The study results found that modern machine learning methods outperformed traditional statistical methods in terms of predictive performance measured by F1 score, G-mean and AUC. Traditional methods like logistic regression were marginally better than linear discriminant analysis and support vector machines in terms of predictive performance measured by area under the receiver operating characteristic curve. In the modern machine learning methods, deep neural networks were better in most of the predictive performance metrics than XGBoost and Random Forest methods.

Background: Resistant hypertension (HTN) is associated with high risk of cardiovascular complications. Our study aimed to assess prevalence, characteristics and treatment of patients with resistant HTN; Methods: We screened 4340 consecutive cardiovascular patients and identified 3762 with HTN. Of them 128 fulfilled criteria for resistant HTN and were included in our study. We matched these patients to 128 hypertensive patients with controlled HTN; Results: Resistant HTN patients were 3.4% of all hypertensives. Most of these patients (67.2%) were at high or very high cardiovascular risk compared to controlled HTN patients (40.6%), p<0001. Resistant HTN patients had more frequently concomitant chronic kidney disease (CKD) (60.9%), overweight/obesity (52.3%), dyslipidemias (35.2%), smoking (27.3%) and diabetes (21.9%) compared to controlled HTN patients (37.5%, 29.7%, 28.1%, 14.1% and 7.8% respectively), p<0.001. Regression analysis showed strongest association of resistant HTN with CKD (OR 6.64), stage III HTN (OR 3.07) and obesity/overweight (OR 2.60). In contrast, single-pill combinations (SPCs) were associated with lower likelihood of uncontrolled HTN (OR 0.58); Conclusions: Resistant HTN represented a small proportion of all hypertensives in our study, but it was characterized by high/very high cardiovascular risk. Optimized therapy including increased usage of SPCs could improve blood pressure control and long-term prognosis of these patients.

: This study aimed to validate the effects of self-compassion-based forest healing therapy as an intervention for reducing stress and promoting coping resources. Therefore, we investigated the effects of self-compassion-based forest healing therapy on stress, self-compassion, and connectedness to nature. A total of 30 participants were divided into an experimental and control group. Two sessions of forest healing meditation activities were held at the Forest of Healing every two weeks between October and November 2023. As a repeated measures experiment, data were collected before the intervention, after the first intervention, and after the second intervention. Perceived stress, positive and negative affect, and salivary cortisol were measured to assess physiological and psychological stress in participants. Connectedness to nature and self-compassion were measured to evaluate stress-coping resources. The results showed that the forest healing program had significant positive effects on stress and emotional states in the experimental group after the intervention. Further, there was a significant incremental effect on connectedness to nature and self-compassion in the experimental group. Therefore, self-compassion meditation-based forest healing therapy is a feasible and efficient approach for facilitating stress management and coping resource building.

Nurses continue to experience intense psychological repercussions despite the official conclusion of the COVID-19 pandemic. In this cross-sectional study conducted after the end of the pandemic crisis, in nurses, we evaluated the levels and explored the associations between anger, insomnia and resilience. A total of 442 nurses participated in an online survey and were invited to state their work experience, gender and age and complete the self-report measures of the Dimensions of Anger Reactions-5 (DAR-5), the Athens Insomnia Scale (AIS) and the Brief Resilience Scale (BRS). 62.1% of participants presented with positive scores on the AIS, 41.5% displayed positive values on the DAR-5 scale, whereas 24.9% of nurses demonstrated scores indicative of low resilience on the BRS scale. Regression analysis revealed that 23.5% of the variance in the AIS scores can be attributed to the DAR-5 scores and 3% to the BRS scores. Mediation analysis confirmed the protective role of resilience contributing as a negative mediator in the DAR-5 and the AIS relationship. Screening for insomnia symptoms and anger issues among nurses after the end of the pandemic and implementing appropriate interventions is considered imperative to avoid long-term health consequences.

Cervical cancer remains a significant global health challenge, ranking as the fourth most common cancer among women. The primary causative agents, Human papillomavirus (HPV) strains 16 and 18, are well-known for their role in cervical carcinogenesis, primarily through the actions of the E6 and E7 oncoproteins. This study aimed to identify a natural compound capable of inhibiting both E6 and E7 oncoprotein activities, thereby offering a potential therapeutic approach using a single agent. This study also comprises an extensive in silico analysis with molecular docking studies by AutoDock Vina and Schrodinger Maestro to analyse the binding affinity, hydrogen bonds interactions of selected compounds against HPV 16 E6 &E7 proteins. GROMACS package and iMODS server was used to perform molecular dynamics simulations of protein-ligand complexes to elucidate stability of the ligands around the receptor at different time points. SwissADME was utilized for the prediction of pharmacokinetic properties while PROTOX-II helped in predicting toxicological data Capsaicin emerged as the most promising candidate, exhibiting binding energies of -7.3 kcal/mol and -5.6 kcal/mol against the HPV 16 E6 and E7 proteins, respectively. Notably, Capsaicin formed a single hydrogen bond with each oncoprotein, indicating a strong and specific interaction. The compound also demonstrated a favourable pharmacokinetic profile, with no violations of drug-likeness rules, and was classified as Toxicity Class 4, suggesting a moderate safety profile. These results, thus branding Capsaicin as a promising lead compound for further investigations in cervical cancer therapy that deserves documentation through well-equipped wet lab experiments followed by clinical studies.

The authors undertook pilot studies to assess the accuracy of the reverse engineering process of worn nonstandard spur gears (non-standardized modulus value, unusual profile/pressure angle, high or low teeth), using conventional techniques and measuring instruments. Eight gears were tested, the module of which ranges from 1.020 to 4.98 mm and the number of teeth from 13 to 42. The key parameter, the basic pitch, was selected to estimate the accuracy of the process. The goal is to determine the value of the profile angle. Eleven models were proposed to estimate the nominal tolerance field, using various types of random data distribution. The tested gears were made in IT grade: 6, 7, 8 and 9 according to DIN 3961. Vernier disc micrometers with various measurement ranges were used for research. It has been shown that the nominal module does not have to be treated as a random variable in the population. EIG (Equation of Identity) was developed, allowing conversion of any gear with specific values of geometric parameters into an identical gear with alternative values of these parameters. The directions and degrees of shifts of the estimated tolerance fields relative to the nominal field were determined. The most effective estimating model was selected in the context of the percentage filling of the nominal tolerance field, taking into account the symmetric Student-Fisher distribution with a confidence level of 60%. Further directions of the research activities were described.

Background: Peloids are therapeutic agents used in thermal and thalasso centers for curative, preventive, and skin care purposes. Marine peloids are those that include seawater and algae, both macro and/or microalgae. The aim of this study is to investigate the suitability of a marine peloid composed by seawater, clay and microalgae for thalasso-wellness and dermocosmetic uses; Methods: the thermophysical properties of the marine peloid were determined and compared with a non-marine peloid using different techniques as densimetry, conductimetry, calorimetry, and viscometry; skin hydration was also measured by means of Corneometry; Results: marine peloid has been shown to be suitable for thermotherapy and thalaso-wellness treatments as its thermophysical properties were similar to other peloids used for this purpose; marine peloids also showed to improve skin hydration after seven days of treatment; Conclusions: this research provides a comprehensive study of the thermophysical properties of a marine peloid composed by clay, seawater and microalgae for thalasso-wellness and cosmetic uses, as well as its moisturizing properties, highlighting its potential as a valuable natural product for skin care applications as well as for wellness treatments in form of cataplasm, poultices and/or wraps.

Serum transferrin (sTf) plays a pivotal role in regulating iron biodistribution and homeostasis within the body. The molecular details of sTf Fe(III) binding, blood transport, and cellular delivery through transferrin receptor-mediated endocytosis are generally well-understood. Emerging interest exists in exploring sTf complexation of nonferric metals as it facilitates the therapeutic potential and toxicity of several of them. This review explores recent X-ray structural and physiologically relevant metal speciation studies to understand how sTf partakes in the bioactivity of key non-redox active hard Lewis acidic metals. It challenges preconceived notions of sTf structure function correlations that were based exclusively on the Fe(III) model by revealing distinct coordination modalities that nonferric metal ions can adopt and different modes of binding to metal-free and Fe(III)-bound sTf that can directly influence how they enter into cells and, ultimately, how they may impact human health. This knowledge informs on biomedical strategies to engineer sTf as a delivery vehicle for metal-based diagnostic and therapeutic agents in the cancer field. It is the intention of this work to open new avenues for characterizing the functionality and medical utility of nonferric-bound sTf and to expand the significance of this protein in the context of bioinorganic chemistry.

Allopolyploidy in plants involves the merging of two or more distinct parental genomes into a single nucleus, a significant evolutionary process in the plant kingdom. Transcriptomic analysis provides valuable insights into the fate of duplicated genes, evolutionary novelties, and environmental adaptations exhibited by allopolyploid plants. However, transcriptome profiling is challenging due to genomic redundancy, which is further complicated by the presence of multiple chromosomes sets and the variations among homoeologs and allelic genes. Prior to transcriptome analysis, sub-genome phasing and homoeology inference are essential for obtaining a comprehensive view of gene expression. This review aims to clarify the terminology in this field, identify the most challenging aspects of transcriptome analysis, explain their inherent difficulties, and suggest reliable analytic strategies. Furthermore, bulk RNA-seq is highlighted as a primary method for studying allopolyploid expression, with an emphasis on the critical steps of read mapping and normalization in differential gene expression analysis.

In order to study the thermal deformation behavior of uranium-50wt.%zirconium, used Gleeble 3800 thermal simulation testing machine to carry out compression deformation experiments at different temperatures for this material. The effects of deformation temperature and strain rate on the alloy were studied. The results show that the peak stress of U-50wt.%Zr metallic fuel decreases with the increase of deformation temperature after thermal deformation at 500°C~600°C, especially at 600°C compared with that at 500°C and 550°C. At the same temperature, the peak stress increases with the increase of strain rate, especially the peak stress at strain rate 0.1s-1 and 1s-1 is significantly higher than that at strain rate 0.01s^-1, and then the microstructure and diffraction results of U-50wt.%Zr metal-type fuel after thermal deformation are compared and analyzed, and the Arrhenius-type constitutive equation and thermal proces550℃,έ=1s^-1 diagram of U-50wt.%Zr metal-type fuel are established based on the peak stress.

Entrepreneurial activities in economic and social domains are considered one of the conditional pillars for successful transformation of resource-rich countries to sustainable, knowledge-based and diversified economies. However, there is no, and cannot be, a single recipe for such a transformation as every country or region needs to develop its own strategy, policy toolbox and implementation plan depending on its historical and present socio-economic make up and trajectory. This paper advances the qualitative findings of a previously published work to delve deeper into the complexities of entrepreneurship within resource-based economies, with a particular focus on Qatar. Employing a mixed methodology that blends explanatory and quantitative analysis, this paper aims to validate and refine the entrepreneurship framework proposed previously, ensuring its relevance and adaptability to Qatar's unique economic and cultural context, and its extendibility to similar resource-rich country settings. It systematically focuses on discovering various social, economic, and environmental dimensions critical to fostering entrepreneurship in resource-rich countries. These include examining government policies, cultural and social factors, financial support mechanisms, innovation ecosystem, technology adaptation, and digitization. A primary component of this study is the methodological approach, which includes collecting and analyzing quantitative data through a survey developed based on previous findings on qualitative explorations. This approach allows for an objective assessment of the effectiveness of the proposed recommendations. The paper presents a set of detailed recommendations aimed at various stakeholders, including government bodies, supporting agencies, and entrepreneurs themselves. These recommendations encompass integrating entrepreneurship education into academic curricula, increasing easy access to business and market information, simplifying, unifying and streamlining policies and procedures, and adapting them into the legal system. Other important and unique recommendations include establishing a country-wide entrepreneurship free-zone (Ent-Q) and facilitating its operations though an online digital platform (Ryadah), allocating certain percentage of governmental ministries’, agencies’ as well as large corporations’ budgets into innovative small business development programs and preferred purchasing from small business. These initiatives are validated to become effective tools and avenues to create a conducive entrepreneurial environment, facilitating transformation into a diversified, knowledge-based and sustainable economy. The expected outcomes of implementing these recommendations include an increase in the efficiency of entrepreneurship-related policymaking, a rise in the number, quality and impact of entrepreneurs, and the sustained diversification of the economy into non-oil/gas sectors and actors. In conclusion, this paper provides a comprehensive set of strategies and recommendations expected to significantly contribute to the nurturing and growth of entrepreneurship in resource-based economies.

Whiteflies of Aleurocanthus spiniferus and A. woglumi (Hemiptera: Aleyrodidae) are serious pests of citrus and other important fruit crops. The problem in citrus has initiated the successful introductions of several natural enemies for biocontrol programs in Hawaii and many other countries. Here we summarized the history of infestation and biocontrol efforts of the two whiteflies in Hawaii for possible importation into Greece. Two Platygasteridae (Amitus hesperidum Silvestri, A. spiniferus (Brethes) and three Aphelinidae (Encarsia clypealis (Silvestri), E. smithi (Silvestri), E. perplexa Huang and Polaszek) were released in Hawaii for biocontrol of the citrus whiteflies during the period 1974-1999. The aphelinid, Cales noacki Howard, purposely released for Aleurothrixus flococcus (Maskell) in 1982 was also reported to attack other whiteflies including Aleurocanthus species on citrus. An additional aphelinid parasitoid, Encarsia nipponica Silvestri, native to Japan and China, was accidently introduced and found to attack both citrus whiteflies on the islands. Since the colonization of introduced parasitoids in infested fields on four Hawaiian Islands, no survey was done to evaluate their potential impact. We made two short surveys during September-November 2022 on Kauai, Hawaii, and Oahu Islands to introduce the dominant parasitoids to Greece for the biocontrol of A. spiniferus. Results showed that the infestation level was very low on Kauai, Hawaii, and Oahu Islands with mean infestation level ranged 1.4 - 3.1 on Hawaii and Oahu Islands mostly on pummelo and sweet orange, with no detection on Kauai Island. Only was E. perplexa the dominant parasitoid with parasitism rates ranged 0 -28 % on Hawaii Island and 11-65% on Oahu Island. Starter colony of the parasitoids has been colonized in Greece for evaluation and approval for release. This was the first field survey on Hawaii since the introduction and release of citrus whitefly natural enemies.

The rapid and extensive loss of biodiversity globally has resulted in an increased urgency to capture and conserve the diversity which is present, including genetic diversity within species. However, for many species there is currently no detailed genetic data available to inform the collection and use of material held in ex situ collections and this can hamper the consideration of genetic issues and reduce the likelihood collection represent the diversity present. Even in the absence of direct genetic data, however, it is possible to consider genetic issues using the existing theoretical and empirical evidence-based and biological, ecological and demographic data for a given species. Here a framework to facilitate the consideration of genetic diversity and genetic issues, even where genetic data is lacking, is presented.

Marine renewable energy is emerging as one of the fast-growing industry in the last decades, as modern society pushes for technologies that can convert energy contained from winds, waves, tides and stream flows. The implementation of renewable energy technologies impose high demands on both structural and environmental engineering, as the energy converters have to work under extreme conditions where parameters such as sea-bottom configuration, water transparency and depth, sea-states and prevailing winds are harsh. Constant monitoring of the marine environment is crucial in order to keep this sector reliable. Active acoustics is becoming a standard tool to collect multi-dimensional data from physical, geological and biological properties of the marine environment. The Div. of Electricity of Uppsala University have been developing an environmental monitoring platform based on sonar (Sound Navigation And Raging) systems. This platform aims to monitor the installation, operation and decommissioning of marine renewable energy converters. The focus will be given the observations of behaviours of marine animals in vicinity of energy converters but also structural inspection and monitoring of MRETs. This paper describes how this multifunctional environmental monitoring platform come to existence from the design to the deployment phase.

The new WHO Environmental Noise Guidelines for the European Region have recommendations for limiting noise exposure associated with adverse health effects. The limits are said to be based on a systematic review of existing evidence. This paper gives a systematic assessment of the presented evidence with respect to aircraft noise annoyance and demonstrates that the new guidelines are based on an arbitrary selection of existing studies comprising an imperfect and faulty set of data not representative for the general airport population.

Medically underserved communities have limited access to effective disease management resources in the U.S. Mobile health applications (mHealth apps) offer patients a cost-effective way to monitor and self-manage their condition and to communicate with providers; however, current diabetes self-management apps have rarely included end-users from underserved communities in the design process. This research documents key stakeholder-driven design requirements for a diabetes self-management app for medically underserved patients. Semi-structured survey-interviews were carried out with 97 patients with diabetes and 11 healthcare providers from medically underserved counties in South Texas to elicit perspectives and preferences regarding a diabetes self-management app, and their beliefs regarding such an app’s usage and utility. Patients emphasized the need for accessible educational content and for quick access to guidance on regulating blood sugar, diet, and exercise and physical activity using multimedia rather than textual form. Healthcare providers indicated that glucose monitoring, educational content, and graphical visualization of diabetes data were among the top-rated app features. These findings suggest that specific design requirements for the underserved may improve the adoption, usability, and sustainability of such interventions. Designers should consider health literacy and numeracy, linguistic barriers, data visualization, data entry complexity, and information exchange capabilities.

The phenomenon of decreased serum uric acid (UA) levels in patients with Parkinson’s disease (PD) and its relationship with purine metabolic pathways remain unclear. We compared inosine, hy-poxanthine, xanthine, and UA levels in serum and cerebrospinal fluid (CSF) of PD patients with those of controls, and investigated the effect of changes in the purine metabolic system on UA levels in PD. Overall, 134 samples (serum, 45 PD patients and 30 controls; CSF, 39 PD patients and 20 controls), were analyzed using liquid chromatography-tandem mass spectrometry. A general linear model (GLM) was used to investigate relationships among purine metabolites. Compared to controls, PD patients had significantly lower UA levels in the serum and CSF, and serum and CSF UA levels were significantly correlated. Additionally, in PD, decreased serum hypoxanthine levels were observed with decreased CSF inosine and hypoxanthine levels, suggesting the involvement of the purine recycling system. GLM analysis indicated that the reduced UA levels in PD were mainly due to sources other than the purine metabolic system, such as exercise, nutritional indices, muscle volume, or adipose tissue. Our results highlight the impairment of purine recycling pathways in PD, as evidenced by the decreased serum hypoxanthine and CSF inosine.

The study of vegetation community and structural change has been central to ecology for over a century, yet how disturbances reshape the physical structure of forest canopies remains relatively unknown. Moderate severity disturbance including fire, ice storms, insect and pathogen outbreaks, affects different canopy strata and plant species, which may give rise to variable structural outcomes and ecological consequences. Terrestrial lidar (light detection and ranging) offers an unprecedented view of the interior arrangement and distribution of canopy elements, permitting the derivation of multidimensional measures of canopy structure that describe several canopy structural traits with known linkages to ecosystem functioning. We used lidar-derived canopy structural measured within a machine learning framework to detect and differentiate among various disturbance agents, including moderate severity fire, ice storm damage, age-related senescence, hemlock woolly adelgid, beech bark disease, and chronic acidification. We found that disturbance agents such as fire and ice storms primarily affected the amount and position of vegetation within canopies, while acidification, pathogen and insect infestation, and senescence altered canopy arrangement and complexity. Only two of the six disturbance agents significantly reduced leaf area, indicating that this commonly quantified canopy feature is insufficient to characterize many moderate severity disturbances. Rather, measures of canopy structure, including those that describe multidimensional change, are needed to characterize disturbance at moderate severities because structural changes from these events are spatially and quantitatively variable. Our findings suggest that standard disturbance detection methods, such as optical based remote sensing platforms, may currently be limited in their ability to detect, differentiate, and characterize disturbance. Further, we conclude that a more broadly inclusive definition of ecological disturbance that incorporates multiple aspects of canopy structure change will improve the modeling, detection, and prediction of functional implications of moderate severity disturbance.

The dynamic landscape of 3D printing has experienced a notable surge in the development of diverse filaments tailored for a wide range of applications in medicine. This experimental study thoroughly examines the mechanical properties of nine popular 3D printer filaments, namely PLA, ABS, HIPS, PETG, PA, Carbon Fiber, Ceramic, PMMA, and Metal composite. Focusing on key aspects such as tensile strength and compressive tests, the study delves into the intricate mechanical characteristics of these 3D printer filaments. In addition to the mechanical properties, the study provides a comprehensive exploration of essential filament attributes, including melting point, bed temperature requirements, and density of nine different filament properties. Furthermore, the study addresses crucial considerations in material selection for different applications. Through insightful comparisons, the article illuminates the advantages and limitations of various available filaments within the realm of applications. This study serves as a valuable resource, offering nuanced insights for researchers, engineers, and medical professionals seeking a deeper understanding of the mechanical characteristics of 3D printer filaments and their potential applications.

Shiga toxin (Stx) produced by Escherichia coli is the main pathogenic factor of diarrhea-associated hemolytic uremic syndrome (HUS), which is characterized by obstruction of renal microvasculature by platelet-fibrin thrombi. It is well known that the oxidative imbalance generated by Stx induces platelet activation, contributing to thrombus formation. Moreover, activated platelets release soluble CD40 ligand (sCD40L) which in turn contributes to oxidative imbalance, triggering the release of reactive oxidative species (ROS) on various cellular types. The aim of this work was to determine if the interaction between the oxidative response and platelet-derived sCD40L participates in the pathogenic mechanism during HUS. Activated human glomerular endothelial cells (HGEC) by Stx2 induced platelets to adhere to them. Although platelet adhesion did not contribute to endothelial damage, high levels of sCD40L were released to the medium. The release of sCD40L by activated platelets was inhibited by antioxidant treatment. Furthermore, we found increased levels of sCD40L in plasma from HUS patients, which were also able to trigger the respiratory burst in monocytes, in a sCD40L-dependent manner. Thus, we concluded that platelet-derived sCD40L and the oxidative response are reciprocally stimulated during Stx2-associated HUS. This process may contribute to the evolution of glomerular occlusion and the microangiopathic lesions.

The connection between a prefabricated reinforced concrete column and a pocket foundation is a case treated from a general perspective in the European Standard named EN 1992-1-1, and when the structural engineer deals with the dimensioning or verification of the connection, he tackles several unknowns. The present work aims to fill in the missing information by presenting detailed calculation models based on the strut-and-tie method for 4 of the widely used pocket foundations: pedestal pocket foundation with smooth, rough or keyed internal walls, and pad foundation with pocket possessing keyed internal walls. Additionally, detailed design prescriptions applicable to seismic areas are given. Afterwards, as a case study, a pocket foundation is designed in all 4 variations, having the structural design particularities, similitudes and differences pointed out. Finally, to conclude the advantages and disadvantages are mentioned for pocket foundations in respect to the type of internal wall surface used. Quantifiable data based on the case study undertaken is available.

Aluminum is a strategic mineral resource, and China’s aluminum production and consumption is fairly large. However, its supply guarantee is uncertain because of a high dependency on external raw materials. This uncertainty may expand, so finding a way to reduce the uncertainty of aluminum resource supply is especially important. This paper applies the SFA method to analyze the aluminum flows in mainland China from 1996 to 2014, and establishes a supply structure model to measure its supply guarantee degree. The results claim that: (1) China’s aluminum production can satisfy demand and even create a surplus; (2) Domestic self-productive primary and secondary aluminum increased at an annual rate of 12% and 24%; (3) The proportion of self-productive secondary aluminum in the supply structure increased from 7.7% in 1996 to 12.8% in 2014, while that of primary aluminum decreased from 79.6% to 42.8%; (4) The total supply guarantee degree decreased from 87.3% to 55.6% in this period. These results provide a feasible way to solve this plight: the proportion of secondary aluminum in the supply structure should be enhanced, and an efficient aluminum resource recycling system needs to be established as soon as possible to ensure its sustainable supply.

Background/ObjectivesMental health and substance use disorders (MHD, SUD) affect cardiac allograft and VAD recipients and impact their quality of life and compliance. Limited research on MHDs and SUDs in transplant and MCS candidates and recipients. This study compares the incidence of MHDs and SUDs in transplant list, VAD, and post-transplant patients with that in heart failure patients. MethodsStudy cohorts were derived from the TriNetX using ICD-10 codes. Differences in incidence were examined using the log-rank test. Adults with mental health disorders before the window of time were excluded. Propensity score matching was performed using TriNetX to balance demographic and medical comorbidities. Statistical significance was set at p<0.05. All comparisons were made between propensity-matched cohorts. ResultsTransplant waitlist patients showed a statistically significant increase in the incidence of anxiety, panic disorder, adjustment disorder, depression, mood disorder, alcohol use disorder, and eating disorder. Post-transplant patients showed a statistically significant increase in the incidence of depression and opioid use compared to the heart failure population. VAD patients showed a statistically significant increase in the incidence of depression and a statistically significant decrease in panic disorder and anxiety. ConclusionsThe results pave the pathway for further investigations on prevention and coping strategies because deterioration of mental health will significantly impact compliance with medications as well as patient survival and quality of life. The use of opioids for pain management in the early postoperative period should be further investigated to assess its impact on long-term substance use and addiction. .

Simultaneously being a non-radiative and non-invasive technique makes magnetic resonance imaging (MRI) one of the highly sought imaging techniques for the early diagnosis and treatment of diseases. Despite more than four decades of research on finding a suitable imaging agent from fluorine for clinical applications, it still lingers as a challenge to get the regulatory approval compared to its hydrogen counterpart. The pertinent hurdle is the simultaneous intrinsic hydrophobicity and lipophobicity of fluorine and its derivatives that make them insoluble in any liquids, strongly limiting their application in areas such as targeted delivery. A blossoming technique to circumvent the unfavorable physicochemical characteristics of perfluorocarbon compounds (PFCs) and guarantee a high local concentration of fluorine in the desired body part is to encapsulate them in nanosystems. In this review, we will be emphasizing different types of nanocarrier systems studied to encapsulate various PFCs and fluorinated compounds, headway to be applied as a contrast agent (CA) in fluorine-19 MRI (19F MRI). We would also scrutinize the different types of PFCs and their specific applications and limitations concerning the nanoparticle (NP) system used to encapsulate them studied over the last decade. A critical evaluation for future opportunities would be speculated.

Diagnostics often require specialized equipment and trained personnel in laboratory settings, creating a growing need for point-of-care tests (POCT). Among genetic testing methods, Loop-mediated Isothermal Amplification (LAMP) offers a viable solution for developing genetic POCT due to its compatibility with simplified devices. This study aimed to create a genetic test that integrates all steps from sample processing to results while minimizing the complexity, handling, equipment, and time required. Several challenges were addressed to achieve this goal: 1) Developing a buffer for bacterial DNA extraction that is compatible with both LAMP and immunochromatographic tests; 2) Adapting the LAMP protocol for its use with the device; and 3) Optimizing the detection protocol for specific test conditions, with a lateral flow immunoassay format selected for its POCT compatibility. Following these developments, the test was validated using Escherichia coli and non-E. coli strains. A portable heating station was also developed to enable amplification without costly equipment. The resulting genetic POCT achieved 100% sensitivity and 85% specificity, with results available in 60 to 75 minutes. This study demonstrated that our closed-method POCT efficiently performs DNA extraction, amplification, and detection for bacterial identification. The test’s simplicity and cost-effectiveness will support its implementation in various settings.

Cancer remains a leading cause of death despite advancements in research and treatment, with traditional therapies often causing significant side effects and resistance. Oxyhydrogen gas, a mixture of 66% molecular hydrogen (H₂) and 33% molecular oxygen (O₂) has shown exceptional promise as a novel therapeutic agent due to its ability to modulate oxidative stress, inflammation, and apoptosis. H2, a key component of oxy-hydrogen gas, neutralises reactive oxygen and nitrogen species, enhancing existing treatments and reducing harmful oxidative states in cancer cells. H₂ also lowers pro-inflammatory mediators including chemokines, cytokines and interleukins, inhibiting cancer cell proliferation and boosting the effectiveness of conventional therapies. Additionally, hydrogen can induce apoptosis in cancer cells by modulating pathways such as MAPK and inhibiting the PI3K/Akt phosphorylation cascade. Preclinical and clinical evidence supports oxyhydrogen gas's potential in treating various cancers. In lung cancer models, it inhibits cell proliferation, induces apoptosis, and enhances chemotherapy sensitivity. Similar results have been observed in breast cancer, where patients reported improved quality of life. In colorectal cancer, oxyhydrogen gas suppresses tumour growth, induces apoptosis and improves intestinal microflora dysbiosis. The unique properties of oxyhydrogen gas make it a promising adjunctive or standalone cancer treatment. However, further research is needed to understand H₂'s mechanisms, optimise treatment protocols, and evaluate long-term safety and efficacy in human patients.

Wicked problems, such as climate change, systemic poverty, and healthcare inequalities, rep- resent the most pressing and intractable challenges facing society today. We propose a novel approach that leverages complex systems theory as a comprehensive framework for understanding and tackling these challenges. By applying concepts such as state space analysis, attractors, and nonlinear dynamics, we offer a sophisticated toolkit for mapping the intricate web of interactions defining wicked problems and exploring potential interventions. Our approach moves beyond tradi- tional reductionist methods, embracing the inherent complexity and dynamism of these issues. We demonstrate how this framework can lead to more nuanced, adaptive, and effective strategies for addressing persistent societal problems. Despite the prevalence of wicked problems and the avail- ability of complex systems theory, practical applications of this approach remain uncommon. This paper aims to bridge this gap, illustrating the potential of complex systems theory to transform our engagement with intractable problems and pave the way for more robust, holistic solutions. By synthesizing insights from mathematics, physics, and social sciences, we present a transdisci- plinary approach that promises to revolutionize how we conceptualize and address society’s most challenging issues.

Polymyalgia rheumatica (PMR) is an inflammatory disease common in people aged 50 years and older. This condition is characterized by the presence of pain and stiffness involving mainly the shoulder and pelvic girdle. Besides the frequent association with giant cell arteritis (GCA), several conditions may mimic PMR or present with PMR features. Since the diagnosis is basically clinical, an adequate diagnosis of this condition is usually required. Positron emission tomography-computed tomography (PET-CT) has proved to be a useful tool for the diagnosis of PMR. The use of 18F-FDG-PET imaging appears promising as it provides detailed information on inflammatory activity that may not be evident with traditional methods. However, since PET-CT is not strictly necessary for the diagnosis of PMR, clinicians should consider several situations in which this imaging technique can be used in patients with suspected PMR.

From an industrial point of view, the milling of 2.5D cavities is a frequent operation, 1 consuming time and presenting optimization potential, especially through a judicious choice of 2 the tool trajectory. Among the different types of trajectories, some have a general spiral-like aspect 3 and can potentially offer a reduced machining time. They are called curvilinear trajectories and are 4 obtained by interpolation between structure curves which are the numerical solutions of a partial 5 differential equation. In this case, the machine tool will connect points and the trajectory will be made 6 up of small segments. Even if, macroscopically, these trajectories have all the qualities to allow the 7 tool to move quickly, on a small scale, the discontinuities in tangency, inherent in the discretization, 8 significantly increase machining time. This article suggests to enhancing the continuity level of the 9 toolpath by rebuilding structure curves with a set of Hermite quartic spline patches connected in 10 tangency and curvature. Thanks to this, the tool will machine at an average feedrate closer to the 11 programmed one and will, de facto, reduce traveling time. 12 This article shows that the proposed method increases, on the two tested cavities, toolpath quality 13 indicators, reduces milling time from 10% to 18% for a curvilinear method without a filter and make 14 it possible to generalize the Bieterman and Sandström method for all non convex pockets.

Intellecta dataset emerges as an innovative synthetic dataset, engineered to enhance the cognitive processing capabilities of contemporary language models. With a composition of 11.53 billion tokens, integrating 8.01 billion tokens of synthetic data with 3.52 billion tokens of rich textbook data, Intellecta is crafted to foster advanced reasoning and comprehensive educational narrative generation. Leveraging the Mixtral-8x7B-Instruct-v0.1 model, the dataset facilitates the generation of complex thought processes and detailed, textbook-style explanations, thus enabling language models to engage in both critical thinking and profound educational discourse. This hybrid dataset stands as a testament to the potential of synthetic data in pushing the boundaries of AI, offering a repository that is not only vast and varied but also refined to align with ethical standards and intellectual rigor.

This Paper delves into the critical role played by fossil fuel-based polymers in promoting United Nations Sustainable Development Goals (SDGs) in the face of challenges brought about by swift population growth, suburbanization, and mechanization. It sheds light on the environmental and energy security recompences of converting plastic waste into biofuels and other valuable energy resources through state-of-the-art processes such as thermochemical conversion and pyrolysis. Besides, the research investigates the utilization of polymers in solar energy, energy storage, and low carbon transportation, emphasizing the inevitability of a dual approach that combines advancements in bio-based polymers and recycling technologies. It highlights the significance of collaborative endeavors involving governments, industries, and communities to overcome the technical, economic, and regulatory complications in transitioning towards a sustainable and circular plastic economy. Eventually, it showcases the potential of fossil fuel-based polymers in fostering a sustainable energy landscape, conducive to decarbonization efforts, and endorsing environmental sustainability.

Ensuring the security of vertical applications in fifth-generation (5G) mobile communication systems and previous generations is crucial. These systems must prioritize maintaining the confidentiality, integrity, and availability of services and data. Examples of vertical applications include smart cities, smart transportation, public services, Industry 4.0, smart grids, smart health, and smart agriculture. Each vertical application has specific security requirements and faces unique threats within the mobile network environment. Thus, it is essential to implement comprehensive and robust security measures. This approach helps minimize the attack surface and effectively manage risks. This survey thoroughly examines mobile networks and their security challenges in vertical applications, shedding light on associated threats and potential solutions. Our study considers the interplay between security considerations in 5G, legacy networks, and vertical applications. We emphasize the challenges, opportunities, and promising directions for future research in this field and the importance of securing vertical applications in the evolving landscape of mobile technology.

Microplastics and nanoplastics (MP/NPs) have been found everywhere they have been searched. On the top of Everest, in the Mariana Trench, on the clouds e recently, microplastics have been discovered in the human placenta, meconium and babies’ feces. In this review we explain what the consequences of the presence of these pollutants in fetuses and newborns are, with particular attention to human breastfeeding. Finally, we outline the possible political and social solutions to the problem of plastic overproduction that characterizes the modern world.

The increase in ecosystem biodiversity can be perceived as one of the universal processes converting energy into information across a wide range of living systems. This study delves into the dynamics of living systems, highlighting the distinction between ex-post adaptation, typically associated with natural selection, and its proactive counterpart, ex-ante adaptability. Through coalescence experiments using synthetic ecosystems, we (i) quantified an ecosystem stability, (ii) identified correlations between species richness and the stability, (iii) proposed a mechanism for increasing biodiversity through moderate inter-ecosystem interactions, and (iv) inferred that the information carrier of ecosystems is species composition, or merged genomic information. Additionally, we observed that (v) changes in ecosystems are constrained to a low-dimensional state space, with three distinct alteration trajectories—fluctuations, rapid environmental responses, and long-term changes—converging into this state space in common. These findings suggest that daily fluctuations may predict broader ecosystem changes. Our experimental insights, coupled with an exploration of living systems' information dynamics from an ecosystem perspective, enhance our predictive capabilities for natural ecosystem behavior, providing a universal framework for understanding a broad spectrum of living systems.

This work presents a new algorithm to resolve the problem of distribution network reconfiguration using the Tabu Search metaheuristic and voltage drop. The proposed method presents a different way to obtain the initial solution using the voltage drop, as well as a new way to generate a neighborhood of candidate solutions, based on randomness and the voltage drop, to perform a smooth and steady descent execution of the algorithm. The proposed algorithm has the main objective to reduce the active power losses in distribution networks, but it also achieves an refinement in the voltage profile. The proposed method was tested in two distribution systems, the 33-Bus and 94-Bus systems, commonly found and tested in the literature. The results of the tests show that the proposed method presents a low computational cost, achieves good solutions, and is better than the other methods found in the literature.

To proactively manage information security, enterprises often employ information security risk assessment techniques. Asset value - which is used to calculate the financial impact of possible threats - is one of the key parameters of information security risk. However, assets in a system are rarely independent, and their values are typically interdependent. Asset owners and IT teams may hold different views as regards these values, and there is thus the need to reduce subjectivity in a qualitative risk assessment. The research entails the development of a conceptual framework derived from the literature to minimize subjectivity, and the design of a system based on those concepts. The study uses the Unified Modeling Language as a design tool and puts forward an object-oriented model for defining asset values, in which the relationships between assets, vulnerabilities and related threats are identified. A “segregation of duties” approach is integrated into the risk management system to mitigate against subjectivity and better determine asset values. Survey responses from 16 practitioners working in the private and public sectors confirm the validity of the approach, but suggest it may be more workable in larger organisations where resources allow dedicated risk professionals to operate.

The graph model enables a broad range of analysis, thus graph processing is an invaluable tool in data analytics. At the heart of every graph processing system lies a concurrent graph data structure that stores the graph. Such a data structure needs to be highly efficient for both graph algorithms and queries. Due to the continuous evolution, the sparsity, and the scale-free nature of real-world graphs, graph processing systems face the challenge of providing an appropriate graph data structure that enables both fast analytical workloads and low-memory fast graph mutations. Existing graph structures offer a hard tradeoff between read-only performance, update friendliness, and memory consumption upon updates. In this paper, we introduce CSR++, a new graph data structure that removes these tradeoffs and enables both fast read-only analytics and quick and memory-friendly mutations. CSR++ combines ideas from CSR, the fastest read-only data structure, and adjacency lists to achieve the best of both worlds. We compare CSR++ to CSR, adjacency lists from the Boost Graph Library, as well as state-of-the-art update-friendly graph structures: LLAMA, STINGER, GraphOne, and Teseo. In our evaluation, which is based on popular graph processing algorithms executed over real-world graphs, we show that CSR++ remains close to CSR in read-only concurrent performance (within 10% on average), while significantly outperforming CSR (by an order of magnitude) and LLAMA (by almost 2×) with frequent updates. We also show that both CSR++’s update throughput and analytics performance exceed that of several state-of-the-art graph structures, while maintaining low memory consumption when the workload includes updates.

Lucid dreaming is a dream in which one is aware that they are dreaming while dreaming as well as being able to influence the dream. It is utilized in scientific research to explore dreaming, in clinical context to treat nightmares, and in private settings to have fun, solve problems, and to train various skills. In this paper, based on an interview with a lucid dreamer, a fascinating, yet hardly described way to use lucid dreaming in sports and martial arts is presented. The dreamer used his lucid dreams to explore new movements and new possibilities in martial arts. For the interview, the guide from Schädlich and Erlacher [1] was used. The interviewee’s lucid dream experience is compared to interviews of other lucid dreamers and their experience and to contemporary research on lucid dreams. While the potential of lucid dreaming is explored, the interviewee also mentions the possible shortcomings of lucid dreaming.

In recent times, there has been a revolutionary surge in antioxidant research, with a focus on harnessing microalgae to enhance wellness and extend human longevity. Microalgae, a diverse group of unicellular photosynthetic organisms, have emerged as promising sources of natural antioxidants due to their ability to synthesize various bioactive compounds, including carotenoids, polyphenols, and tocopherols. These antioxidants play a pivotal role in scavenging free radicals and reducing oxidative stress, known contributors to aging and chronic diseases. This review provides an overview of recent advancements in understanding microalgae's antioxidant potential, covering their biochemical composition, extraction techniques, and purification methods. Moreover, it delves into compelling in vitro and in vivo studies showcasing microalgae-derived antioxidants' protective effects against oxidative damage, inflammation, cardiovascular diseases, and neurodegenerative disorders. The sustainable cultivation of microalgae in controlled environments further supports the potential for large-scale production and commercialization of their antioxidant compounds. As microalgae continue to revolutionize antioxidant research, they hold immense promise in developing novel preventive and therapeutic strategies to promote human health and wellbeing.

Since the first published genome sequence of Trypanosoma cruzi in 2005, there has been tremendous technological advance in genomics, reverse genetics, and assay development for this elusive pathogen. However, there is still an unmet need for new and better drugs to treat Chagas disease. Here we introduce a T. cruzi assay strain that is useful for drug research as well as basic studies in host-pathogen interaction. Trypanosoma cruzi STIB980 is a strain of discrete typing unit TcI that grows well in culture as axenic epimastigotes or intracellular amastigotes. We have evaluated the optimal parameters for genetic transfection and constructed derivatives of T. cruzi STIB980 that express reporter genes for fluorescence- or bioluminescence-based drug efficacy testing, as well as a Cas9-expressing line for CRISPR/Cas9-mediated gene editing. The genome of T. cruzi STIB980 was sequenced by combining short-read Illumina with long-read Oxford Nanopore technologies. The latter served for the primary assembly, the former to correct mistakes and fill the gaps. This resulted in a high-quality nuclear haplotype assembly of 28 Mb in 400 contigs, containing 10,043 open-reading frames with a median length of 1077 bp. We believe that T. cruzi STIB980 is a useful addition to the antichagasic toolbox, and propose that it can serve as a DTU TcI reference strain for drug efficacy testing.

High Resolution Melting Analysis (HRM) has been pointed as a suitable alternative method to detect and identify Leishmania species. Herein, we aimed to evaluate the sensitivity, specificity, accuracy, and limitations of a HSP70-HRM protocol both as a diagnostic scheme applied in clinical samples and as a species typing tool for laboratory research and reference services. Our data reveal the pronounced species-typing potential of the HSP70-HRM in DNA from cultured parasites. For clinical samples, however, we advise caution due to the parasite load-dependent accuracy. In the light of these findings and considering the importance of parasite load determination for clinical and research purposes we recommend the integration of the presented typing scheme and the previously published Leishmania quantifying approach as combined tools for clinicians, surveillance, and research.

Although a slightly radioactive element, thorium is considered very toxic because its various species, which reach the environment, can constitute an important problem for the health of the population. The present paper aims to expand the possibilities of using membrane processes in the removal, recovery and recycling of thorium from industrial residues reaching the municipal waste processing platforms. The paper includes a short introduction on the interest shown for this element, a weak radioactive metal, followed by highlighting of some common (domestic) uses. In a distinct but concise part, the bio-medical impact of thorium is presented. The classic technologies for obtaining thorium are concentrated in a single schema, and then the speciation of thorium is presented with an emphasis on the formation of hydroxo-complexes and complexes with common organic reagents. The determination of thorium has been highlighted both on the basis of its radioactivity, but especially through methods that call for extraction followed by an established electrochemical, spectral or chromatographic method. Membrane processes are presented based on the electrochemical potential difference, rapidly presenting barro-membrane processes, electrodialysis, liquid membranes and hybrid processes. A separate sub-chapter is devoted to proposals and recommendations for the use of membranes in order to achieve some progress in urban mining for the valorization of thorium.

The transportation sector is seeing an increased adoption rate of electric vehicles (EV), which comprise battery electric vehicles (BEV), hybrid electric vehicles (HEV) and plug-in hybrid electric vehicles (PHEV). This mode of transportation is likely to displace automobiles powered by internal combustion engines (ICE) in the nearest future, as indicated by the current trend. Each of the key EC components is home to a variety of technologies that are either currently in use or will be in the near future. Electric vehicles have the potential to have a significant impact on a variety of fields, including the economy, the energy infrastructure, and the natural environment. As a result of the production of carbon dioxide gas from the combustion of fossil fuels, transportation is the sector that is responsible for the second-highest amount of greenhouse gas emissions. Electric vehicles, often known as EVs, are getting a lot of attention as a potentially game-changing solution to this issue. It is possible for electric vehicles to produce fewer emissions of carbon dioxide (CO2) than conventional automobiles due to the fact that an electric motor serves as the vehicle's propeller rather than an internal combustion engine. EVs have the potential to become zero-emission vehicles if they are paired with renewable energy sources. This document presents an overview of the numerous types of EV drive circuits, covering their design as well as the benefits and drawbacks associated with each type. The current state of battery technology, particularly that pertaining to the batteries utilized in electronic vehicles, is discussed in this paper. This article also discusses electric motor efficiency, power density, fault tolerance, dependability, cost, and the best electric motor for EVs. Then, a thorough study of future EV implementation's obstacles and prospects is done. Charging times and battery performance are examples of technological challenges, but government regulation of EVs continues to be a substantial non-technical hurdle.

Bioelectric effect is known as combinatorial biofilm treatment with low dose of antibiotics with small electricity. When external electric field or current are applied, biofilms can be affected by the electrostatic force, non-uniform distribution of essential electrolytes, induction of low activity of enzyme, and increase of permeability of biofilms. In this work, we have focused on the reduction of applied electric power consumption that could avoid water electrolysis which was one of major challenges for biomedical applications. We have developed a new type of electrical signal that enhances the efficacy of biofilm removal. The results show combination of alternating and direct current remove biofilm effectively without causing electrolysis. We further developed an oral healthcare device as a bioelectric toothbrush and tested in dental clinic. The results demonstrated 75% reduction of gingivitis. In addition, we have tested a mimicked air conditioner biofilms that are root causes of aerobic hygiene infection. The result demonstrates 81.8% increased biofilm removal. In conclusion, a new bioelectric technology has been developed and demonstrated the biofilm removal efficacy without the electrolysis.

Accumulation of extra fats in the body results in disturbance in homeostasis causing obesity. The pathophysiology of obesity has been associated with various genetic, epigenetic factors and the disturbed lifestyles of an individual. One of the outcomes is disturbance in the sleep cycle which leads to sleep disorders. The evolutionary significance of sleep lies in the fact that it saves energy and is crucial for adjustment of an individual to ecological and environmental factors, and thus maintains homeostasis. Sleep has an anabolic function and replenishes the wakefulness-associated loss of glycogen stores. However, the modern lifestyle is well known to disrupt sleep behavior and patterns affecting human health negatively. Alteration in homeostasis leads to several acute and chronic pathophysiological conditions like obesity and related metabolic morbidities being one amongst them. Shorter sleep duration and poor sleep quality are important risk factors associated with the development of obesity and have more adverse effects on energy homeostasis. Consequently, it is crucial to comprehend the obesity and sleep relationship and its therapeutic strategies, given that strong crosstalk exists between energy balance that favors obesity and sleep apnea. It is therefore highly recommended to the people with a high risk of obesity to maintain sleep discipline and good sleep hygiene in our daily life. Interventions are required to improve both sleep quality and quantity, and associated obesity. More focused research is needed for uncovering the pieces of evidence that determine whether such interventions can improve obesity-related health consequences. The present review discusses the important findings on the therapeutic and neuroendocrine mechanisms regulating sleep and obesity.

In offshore drilling, accidents such as gas invasion, overflow, and kicks are inevitable, and they can escalate into blowouts and other catastrophic events that result in casualties and substantial economic losses. Therefore, maintaining drilling safety requires accurate monitoring of gas invasion and overflow. The majority of overflow monitoring methods currently utilized at drilling sites are threshold-based. However, monitoring parameters acquired during actual drilling operations frequently contain noise signals, making it difficult for threshold-based methods to strike a balance between improving accuracy and minimizing false positives. In this paper, Pattern Recognition-based Kick Detection (PRKD) is proposed as a novel method for diagnosing overflow in offshore drilling. This method utilizes the overflow evolution process by integrating multi-phase flow calculations, data filtering theory, pattern recognition theory, the Bayesian framework, and other theoretical models. The PRKD effectively detects and monitors gas intrusion and overflow based on single parameters by analyzing the shape and wave characteristics of the curves. The case analysis demonstrates that the proposed method for monitoring drilling overflow achieves high precision while maintaining a low false positive rate. By combining advanced computational techniques with pattern recognition algorithms, the PRKD improves the accuracy and reliability of kick detection, enabling proactive responses to potential risks, protecting the environment and human lives, and optimizing drilling operations.

A pandemic can have a huge impact on normal human life and the economy, taking COVID-19 as an example. While the population flow between countries and regions is the main factor affecting the change of a pandemic, exactly as the airline network. Therefore, realizing the overall control of airports is an effective way to control a pandemic. However, restricted to the differences in prevention and control policies in different areas and privacy issues, the patients’ personal data of the medical center cannot be effectively combined with the passengers’ personal data. This prevents more precise airport control decisions from being made. To the end, this paper designs a novel data sharing framework (i.e., PPChain) based on blockchain and federated learning. The experiment shows that the relationship between the epidemic and aircraft transport can be effectively explored by PPChain, without sharing raw data. This approach does not require centralized trust and improves the security of the shareing process.The scheme can help formulate more scientific and rational prevention and control policies on airports’ control. And it can use aerial data to predict pandemics more accurately.

In Los Angeles, at one point, the Covid-19 testing positivity rate was 6.25%, or one in sixteen. This translates to, on average, one in sixteen specimens testing positive and the vast majority testing negative. Usually, we run sixteen tests on sixteen specimens to identify the positive one(s). This process can be time consuming and expensive. Since a group of negative specimens pooled together for testing will produce a negative result, one single test could potentially eliminate many specimens. Only when the pooled specimen tests positive do we need further testing to identify the positive one(s). Based on this concept, we designed a strategy that will identify the positive specimen(s) efficiently. Assuming one in sixteen specimens is positive, we find that only four tests are needed. Furthermore, we can run them simultaneously, saving both resources and time. Although, in the real world, we cannot make the assumption of only one positive specimen, the same strategy works with slight modification and proves to be much more efficient than the conventional testing. Our strategy returns an answer 48% of the time in four tests and one time cycle. Overall, the average number of tests is seven or eight depending on the follow-up testing, and the average time cycle is about one and a half.

Artificial membrane systems can serve as models to investigate molecular mechanisms of different cellular processes, including transport, pore formation, and viral fusion. However, the current simulacrums such as SUVs, GUVs, and the supported lipid bilayers suffer from issues, namely high curvature, heterogeneity, and surface artefacts, respectively. Freestanding membranes provide a facile solution to these issues, but current systems developed by various groups use silicon or aluminium oxide wafers for fabrication that involves access to a dedicated nanolithography facility and high cost while conferring poor membrane stability. Here, we report the development, characterization and applications of an easy-to-fabricate suspended lipid bilayer (SULB) membrane platform leveraging commercial track-etched porous filters (PCTE) with defined microwell size. Our SULB system offers a platform to study the lipid composition-dependent structural and functional properties of membranes with exceptional stability in a high throughput fashion. With dye entrapped in PCTE microwells by SULB, we show that sphingomyelin significantly augments the activity of pore-forming toxin, Cytolysin A (ClyA) and the pore formation induces lipid exchange between the bilayer leaflets. Further, we demonstrate high efficiency and rapid kinetics of membrane fusion by dengue virus in our SULB platform. Our suspended bilayer membrane mimetic offers a novel platform to investigate a large class of biomembrane interactions and processes.

We examine a family of nonlinear q-difference-differential Cauchy problems obtained as a coupling of linear Cauchy problems containing dilation q-difference operators, recently investigated by the author, and quasi-linear Kowalevski type problems that involve contraction q-difference operators. We build up local holomorphic solutions to these problems. Two aspects of these solutions are explored. One facet deals with asymptotic expansions in the complex time variable for which a mixed type Gevrey and q-Gevrey structure is exhibited. The other feature concerns the problem of confluence of these solutions as q tends to 1.

Eating disorders (EDs) are serious, life-threatening psychiatric conditions associated with physical and psychosocial impairments, as well as high morbidity and mortality. Given the chronic refractory nature of EDs and the paucity of evidence-based treatments, there is a pressing need to identify novel approaches for this population. The noncompetitive N-methyl-D-aspartate receptor (NMDAr) antagonist, ketamine, has recently been approved for treatment-resistant depression, exerting rapid and robust antidepressant effects. It is now being investigated for several new indications, including obsessive-compulsive, post-traumatic, and substance use disorder; and shows transdiagnostic potential for EDs, particularly among clinical non-responders. As such, the aim of this review is to examine contemporary findings on the treatment of EDs with ketamine, whether used as a primary, adjunctive, or combination psychopharmacotherapy. Avenues for future research are also discussed. Overall, results are encouraging and point to therapeutic value, yet are limited to case series and reports on anorexia nervosa. Further empirical work is thus needed to explore ketamine efficacy across ED subgroups; establish safety profiles and optimize dosing; and develop theory-driven, targeted treatment strategies at the individual patient level.

Biocultural heritage preservation relies on ethnobotanical knowledge and the paleoethnobotanical data used in (re)constructing histories of human-biota interactions. Biocultural heritage, defined as the knowledge and practices of Indigenous and Local peoples and their biological relatives, is often guarded information, meant for specific audiences and withheld from other social circles. As such, these forms of heritage and knowledge must also be included in the ongoing data sovereignty discussions and movement. In this paper we share the process and design decisions behind creating an online database for ethnobotanical knowledge and associated paleoethnobotanical data, using a content management system designed to foreground Indigenous and local perspectives. Our main purpose is to suggest the Mukurtu content management system, originally designed for physical items of cultural importance, be considered as a potential tool for digitizing and ethically circulating biocultural heritage, including paleoethnobotanical resources. With this database, we aim to create access to biocultural heritage and paleoethnobotanical considerations for a variety of audiences while also respecting the protected and sensitive natures of Indigenous and local knowledges.

Abstract: Calcium-based catalysts are of a high interest for glycerol polymerization due to their high catalytic activity and large availability. However, their poor stability under reaction conditions is an issue. In the present study, we investigated the stability and catalytic activity of Ca-hydroxyapatites (HAps) as one of the most abundant Ca-source in nature. A stochiometric, a Ca-deficient and a Ca-rich HAps have been synthetized and tested as catalysts in the glycerol polymerization reaction. Deficient and stochiometric HAps exhibited a remarkable 100% selectivity to triglycerol at 15 % of glycerol conversion at 245 °C after 8 h of reaction in the presence 0.5 mol.% of catalyst. Moreover, under the same reaction conditions, Ca-rich HAp showed a high selectivity (88 %) to di- and triglycerol at a glycerol conversion of 27 %. Most importantly, these catalysts were unexpectedly stable towards leaching under the reaction conditions based on the ICP-OES results. However, based on the catalytic tests and characterization analysis performed by XRD, XPS, IR, TGA-DSC and ICP-OES, we found that HAps can be deactivated by the presence of the reaction products themselves, i.e., water and polymers.

The aerospace industry develops prognosis and health management algorithms to ensure better safety on board. Particularly for in-flight controls where jamming is dreaded. For that, vibration signals are monitored to predict future defect occurrences. However, time series are not labeled according to severity level, and the user can only assess the system health from the data mining procedure. To that extent, we developed a clustering algorithm using a deep neural network core. We encoded the time series into pictures to be feed into an artificially trained neural network: U-NET. From the segmented output, one-dimensional information on cluster frontiers is extracted and filtered without any parameter selection. Then, a kernel density estimation finally transforms the signal into an empirical density. Ultimately, a Gaussian mixture model extracts the latter independent components. The method empowered us to reveal different degrees of severity faults in the studied data, with their respective likelihood without prior knowledge. We compared it to state-of-the-art machine learning algorithms. However, internal clustering results evaluation for time series is an open question. As state-of-the-art indexes were not producing relevant results, we built a new indicator to fulfill this task. We applied the whole method to an actuator consisting of an induction machine linked to a ball screw. This study lays the groundwork for future training of diagnosis and prognosis structures in the health management framework.

Cutaneous wound healing is a complex multi-stage process involving direct and indirect cell communication events with the aim of efficiently restoring the barrier function of the skin. One key aspect in cutaneous wound healing is associated with cell movement and migration into the physically, chemically and biologically injured area resulting in wound closure. Understanding the conditions under which cell migration is impaired and elucidating the cellular and molecular mechanisms that improve healing dynamics is therefore crucial in devising novel therapeutic strategies to elevate patient suffering, reduce scaring and eliminate chronic wounds. Following the global trend towards automation, miniaturization and integration of cell-based assays into microphysiological systems, conventional wound healing assays such as the scratch assay or cell exclusion assay have recently been translated and improved using microfluidics and lab-on-a-chip technologies. These miniaturized cell analysis systems allow precise spatial and temporal control over a range of dynamic microenvironmental factors including shear stress, biochemical and oxygen gradients to create more reliable in vitro models that resemble the in vivo microenvironment of a wound more closely on a molecular, cellular, and tissue level. The current review provides (a) an overview on the main molecular and cellular processes that take place during wound healing, (b) a brief introduction into conventional in vitro wound healing assays, and (c) a perspective on future cutaneous and vascular wound healing research using microfluidic technology.

A fundamental question in biology is how cell shapes are genetically encoded and enzymatically generated. Prevalent shapes among walled bacteria include spheres and rods. These shapes are chiefly determined by the peptidoglycan (PG) cell wall. Bacterial division results in two daughter cells, whose shapes are predetermined by the mother. This makes it difficult to explore the origin of cell shapes in healthy bacteria. In this review, we argue that the Gram-negative bacterium Myxococcus xanthus is an ideal model for understanding PG assembly and bacterial morphogenesis because it forms rods and spheres at different life stages. Rod-shaped vegetative cells of M. xanthus can thoroughly degrade their PG and form spherical spores. As these spores germinate, cells rebuild their PG and reestablish rod shape without preexisting templates. Such a unique sphere-to-rod transition provides a rare opportunity to visualize de novo PG assembly and rod-like morphogenesis in a well-established model organism.

The dataset reports a collection of earnings call transcripts, the related stock prices, and the related sector index. It contains a total of 188 transcripts, 11970 stock prices, and 1196 sector index values. Furthermore, all of these data originated in the period 2016-2020 and are related to the NASDAQ stock market. The data have been collected using Yahoo Finance and Thomson Reuters Eikon. Specifically, Yahoo Finance offered daily stock prices and traded volume. At the same time, Thomson Reuters Eikon has been used as source for the earnings call transcripts. The dataset can be used as a benchmark for the evaluation of several NLP techniques as well as machine learning algorithms for understanding their potential for financial applications. Moreover, it is also possible to expand the dataset by extending the period in which the data originated following a similar procedure.

The way in which the human being learns certain complex contents has always been a focus of interest and a challenge for researchers. Given the fact that children's cognitive abilities do not fully develop until a certain age, this topic is particularly important in the young children's learning scope as they do not correctly and easily learn some content of abstract nature, such as contents in math class. This work presents the results of the use of an application called "Mathematics Learning System with Augmented Reality based on Kinect" (SAM-RAK by its acronym in Spanish), which was designed to cover basic topics of mathematics in the Basic General Education level (EGB by its acronym in Span-ish) in Ecuador. The research was carried out under an experimental quantitative approach with 30 children (18 girls and 12 boys), who study in third grade of EGB level, from 2 different educational in-stitutions in Riobamba city. In order to obtain the results that evaluate the developed application, a pre-test and a post-test were applied, which were contrasted with the student’s t-test for paired samples. The statistical evidence suggests that the proposed computer system had a positive effect on children's performance, when it was used as a support tool in the classroom. The system was more effective in low performance children compared to those of high performance. It was also proved that children were motivated and showed positive attitudes when using the proposed System.

There is an urgent need to advance safe and affordable COVID-19 vaccines for low- and middle-income countries of Asia, Africa and Latin America. Such vaccines rely on proven technologies such as recombinant protein-based vaccines to facilitate its transfer for emerging market vaccine manufacturers. Our group is developing a two-pronged approach to advance recombinant protein-based vaccines to prevent COVID-19 caused by SARS CoV2 and other coronavirus infections. One vaccine is based on a yeast-derived (Pichia pastoris) recombinant protein comprised of the receptor binding domain (RBD) of the SARS-CoV formulated on alum and referred to as the CoV RBD219-N1 Vaccine. Potentially this vaccine could be used as a heterologous vaccine against COVID-19. A second vaccine specific for COVID-19 is also being advanced using the corresponding RBD of SARS-CoV-2. The first antigen has already undergone cGMP manufacture and is therefore “shovel ready” for advancing into clinical trials, following vialing and required GLP toxicology testing. Evidence for its potential efficacy to cross-protect against SARS-CoV-2 includes cross-neutralization and binding studies using polyclonal and monoclonal antibodies. Evidence in support of its safety profile include our internal assessments in a mouse challenge model using a lethal mouse adapted SARS strain, which show that SARS-CoV RBD 291N1 (when adsorbed to Alhydrogel®) does not elicit eosinophilic lung pathology. Together these findings suggest that recombinant protein-based vaccines based on the RBD warrant further development to prevent SARS, COVID-19 or other coronaviruses of pandemic potential.

A human organism depends on stable glucose blood levels in order to maintain the metabolic needs. Glucose is considered as the most important energy source and glycolysis is postulated as a backbone pathway. However, when glucose supply is limited, ketone bodies and amino acids can be used to produce enough ATP. In contrast, for the functioning of pentose phosphate pathway (PPP) glucose is essential and cannot be substituted by other metabolites. PPP generates and maintains levels of NADPH needed for reduction of oxidized glutathione and protein thiols, synthesis of lipids and DNA as well as for xenobiotic detoxification, regulatory redox signaling and counteracting infections. Flux of glucose into a PPP, particularly under extreme oxidative and toxic challenges is critical for survival, whereas the glycolytic pathway is primarily activated when glucose is abundant, and there is lack of NADP⁺ that is required for activation of glucose-6 phosphate dehydrogenase. An important role of glycogen stores in resistance to oxidative challenges is discussed. Current evidences explain disruptive metabolic effects and detrimental health consequences of chronic nutritional carbohydrate overload and provides new insights into positive metabolic effects of intermittent fasting, caloric restriction, exercise, and ketogenic diet through modulation of redox homeostasis.

The present article discusses the institutional model adopted in Brazil regarding energy production through biomass. The theoretical-empirical method is used to conclude that the model's difficulties can be overcome by adopting a network of contracts capable of subjecting renewable energy generation to an energy compensation model.

Counterfeiting and theft have always been problems that incur high costs and results in considerable losses for the international markets. In this research paper, we will address the issue of counterfeiting while using RFID technology in retailer systems or other industries by presenting a new anti-counterfeiting and anti-theft system for the retailer market. This system will address the two above mentioned issues and provide a solution that can save the retailer systems millions of dollars yearly. This proposed system will achieve the objective of preventing or minimising the counterfeiting and theft of tagged products. At the same time, it will provide a strong indication for suspiciously sold or obtained items. Furthermore, we conducted a security analysis to prove the correctness of our protocol on the basis of the strand spaces.

Can ‘restoration and therapy in design’ signify something more than the places like hospitals and healing gardens? Can those restorative environments be brought inside the working and living environments to mitigate the psychological problem at the source? The main objective of this paper is to look at the strategies and developments of Biophilic design with respect to therapy and restoration in order to achieve sustainability in terms of quality of life within the immediate built-environment. The paper explores the mental health issues under the domains of built-environment and indoor environment with respect to their connection with nature. Biophilic design has gained a favourable momentum within the last four decades and is now visualised as a medium that bridges the gap between humans and the nature. Out of a variety of measures of sustainable environmental design, biophilic design focuses on the end-results of naturally nurtured or inspired habitats and workplaces. It embodies strategies of Green and Intelligent buildings, works as a mitigation strategy for foul indoor environment and establishes the vision that veristic sustainability can only be achieved if there is qualitative control over human physiological prosperity and psychological health. In context of work efficiency, preference and productivity within the indoor environment, it is seen as a promoter of constructive thoughts and enhancer of creativity. The paper aims to enlist biophilic design and retrofitting strategies, which can improve cognitive function, reduce stress and provide mental peace within the built environment.

Nutrients management is a mainspring in agricultural systems for sustained productivity, economy sustainability and environmental quality. Excessive and lesser nutrient application caused environmental pollution and reduced production, respectively impacting socio-economics of the entire ecosystems. Sustainable agricultural production thus demands supplementation of nutrients either through natural processes, application of animal by-products, and mineral fertilizers to crop fields. Technology application for treating useless agricultural wastes into useful source is a management strategy that prevents environment pollution. Crude animal manures triggered soil degradation, attenuation air and water quality, and resulted in higher concentrations of heavy metals. Primary nutrients, i.e., nitrogen, phosphorus and potassium are used globally and are non-renewable. Augmented upsurge in prices of inorganic fertilizers and required discharge restrictions on nutrient has stimulated the technological developments including biochar, composting, vermicomposting, composting with biochar, pyrolysis, forward osmosis, and electro-dialysis to recover nutrients. Therefore, outlining the research gaps considering the present and imminent potential of these technologies for adaptation of nutrient recycling is of great importance. Thus, it’s need of an hour to fix our environment and for that scientists are trying to introduce and renovate the technologies which have immense potential to mitigate the negative effects of technology adversities on our environment.

Several design methods and principles have been presented so far, in order to guide the design of autonomous operations. Putting the required efforts into learning and using the methods for designing autonomous operations is a daunting task. Experiences so far have shown that the use of methods meant to the help the design process are often ignored. One reason could be that the design guidelines are too complex and contain much information often not relevant for the project at hand, and therefore there is no easy way to distinguish what is important from what is not. This is an issue that needs to be solved with our approach. In this article, the Autonomous Job Analysis (AJA) method is presented. The proposed methodology is created in order to guide the design of autonomous operations in maritime systems by breaking them down in to sub-operations in order to reveal challenges, needs and limitations regarding autonomous behavior. The canvas contains the categories of the AJA method on a single page format -the canvas- and each category is supported with questions to be asked during the design procedure, as well as example answers. We will describe the AJA method and the AJA canvas in detail, and present a use case scenario of an autonomous operation in order to show how they can be applied. The particular use-case is the design of an autonomous operation for the detection, inspection and tracking of a waste water plume.

Model-based design has received considerable attention in biological and chemical industries over the last two decades. However, the parameter uncertainties of first-principle models are critical in model-based design and have led to the development of robustification concepts. Various strategies were introduced to solve the robust optimization problem. Most approaches suffer from either unreasonable computational expense or low approximation accuracy. Moreover, they are not rigorous and do not consider robust optimization problems where parameter correlation and equality constraints exist. In this work, we propose a highly efficient framework for solving robust optimization problems with the so-called point estimation method (PEM). The PEM has a fair trade-off between computation expense and approximation accuracy and can be easily extended to problems of parameter correlations. From a statistical point of view, moment-based methods are used to approximate robust inequality and equality constraints. We also suggest employing the information from global sensitivity analysis to further simplify robust optimization problems with a large number of uncertain parameters. We demonstrate the performance of the proposed framework with two case studies where one is to design a heating/cooling profile for the essential part of a continuous production process and the other is to optimize the feeding profile for a fed-batch reactor of the penicillin fermentation process. The results reveal that the proposed approach can be used successfully for complex (bio)chemical problems in model-based design.

Human milk composition is dynamic and substitute formulae are intended to mimic its protein content. The purpose of this study was to investigate the potentiality of matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF MS) followed by multivariate data analyses as a tool to analyze peptide profiling of mammalian, human and formula milks. Breast milk samples from women at different lactation stages (2 (n = 5), 30 (n = 6), 60 (n = 5), and 90 (n = 4) days postpartum), and milk from donkeys (n = 4), cows (n = 4), buffaloes (n = 7), goats (n = 4), ewes (n = 5), and camels (n = 2) were collected. Different brands (n = 4) of infant formulae were also analyzed. Protein content (<30 kDa) was analyzed by MS and data were exported for statistical elaborations. Mass spectra for each milk closely clustered together, whereas different milk samples resulted well separated. Human samples formed a cluster in which colostrum constituted a well-defined subcluster. None of the milk formulae correlated with animal or human milk, although specifically characterized and well correlated each other. These findings propose MALDI-TOF MS milk profiling as an analytical tool to discriminate, in a blinded way, different milk types. As each formula has a distinct specificity, shifting a baby from one to another formula implies a specific proteomic exposure. These profiles may assist in milk proteomics for easiness of use and low cost consuming, suggesting that the MALDI-TOF MS pipelines may result useful for milk adulteration assessment but also for the characterization of banked milk specimens in paediatric clinical settings.

The influence of the film thickness and the substrate’s refractive index on the surface mode at the superstrate is an important study step that may help clearing some of the misunderstandings surrounding their propagation mechanism. A single sub-wavelength slit perforating a thin metallic film is among the simplest nanostructure capable of launching Surface Plasmon Polaritons on its surrounding surface when excited by an incident field. Here, the impact of the substrate and the film thickness on surface waves is investigated. When the thickness of the film is comparable to its skin depth, SPP waves from the substrate penetrate the film and emerge from the superstrate, creating a superposition of two SPP waves, that leads to a beat interference envelope with well-defined loci which are the function of both the drive frequency and the dielectric constant of the substrate/superstrate. As the film thickness is reduced to the SPP’s penetration depth, surface waves from optically denser dielectric/metal interface would dominate, leading to volume plasmons that propagate inside the film at optical frequencies. Interference of periodic volume charge density with the incident field over the film creates charge bundles that are periodic in space and time.

This paper addresses the problem of assessing and optimizing acoustic positioning system for underwater target localization with range measurements only. We present a new three-dimensional assessment model to assess the optimal geometric beacon formation whether meet user needs. For the sake of mathematical tractability, it is assumed that the measurements of the range between the target and beacons are corrupted with white Gaussian noise with variance is distance-dependent. Then by adopting dilution of precision (DOP) parameters in the assessment model, the relationship between DOP parameters and positioning accuracy is derived. In addition, the optimal geometric beacon formation that will yield the best performance is achieved by minimizing the values of geometric dilution of precision (GDOP) on condition that the position of target is known and fixed. Next, in order to make sure whether the estimate positioning accuracy over interesting region satisfy the precision needed by the users, geometric positioning accuracy (GPA), horizonal positioning accuracy (HPA) and vertical positioning accuracy (VPA) are utilized to assess the optimal geometric beacon formation. Simulation examples are designed to illustrate the exactness of the conclusion. Unlike other work which only use GDOP to optimize the formation and cannot assess the performance of the specified dimensions, this new three-dimensional assessment model can assess the optimal geometric beacon formation in each dimension for any point in three-dimensional space, which can provide users with guidance advices to optimize performance of every specified dimension.

Precision and accuracy estimation is an important index used to reflect the measurement performance and quality of a measurement system. To reveal the significance and connotations of the precision and accuracy estimation index of a close-range photogrammetry system, several common precision and accuracy estimation methods used in close-range photogrammetry are explained from a theoretical perspective, and the mechanism of the internal coincidence precision estimation and the external coincidence accuracy estimation are deduced, respectively. Through detailed experimental design and testing, the validity and reliability of the proposed precision and accuracy estimation methods are verified, which provides strong evidence for the quality control, optimisation, and evaluation of the measurement results from a close-range photogrammetry system. At the same time, it has significance for the further development of precision and accuracy estimation analysis of close-range photogrammetry systems.