Fundamental Measure Research Articles

Review of the Fundamental Measurement Modalities in Photoacoustic Mechanical Imaging

Review of the Fundamental Measurement Modalities in Photoacoustic Mechanical Imaging

Nursing prioritization and rationing decisions in acute care hospitals during the Covid-19 pandemic: a qualitative study

Nursing prioritization and rationing decisions in acute care hospitals during the Covid-19 pandemic: a qualitative study Abstract:Background: The Covid-19 pandemic has put decisions regarding prioritization and rationing of care resources on the health policy agenda. The effects on the allocation of nursing resources in clinical practice are unclear. Aim: In order to derive implications for future pandemic situations, we analyzed the extent to which decisions were made about the distribution of resources in acute inpatient care and how bottlenecks were dealt with. Methods: We conducted semi-structured interviews with nursing staff (n = 16) and nursing team leaders (n = 10) in five acute-care clinics in Germany and analyzed them inductively using thematic framework analysis. Results: In acute inpatient care under pandemic conditions, prioritization and rationing decisions were made, such as the postponement or reduction of nursing measures, in order to overcome pandemic-specific challenges. These decisions affected certain patient groups and certain near- and distant-patient services, in particular fundamental care measures, such as support with personal hygiene and nutrition, as well as access to acute inpatient care. The decisions were made implicitly rather than according to evidence-based criteria. Conclusions: Nursing prioritization and rationing decisions were made during the pandemic. These decisions are similar to comparable decisions outside of the pandemic, particularly in terms of insufficient evidence base, and emphasize the need for empirically based decision criteria.

High-order network degree revealed shared and distinct features among adult schizophrenia, bipolar disorder and ADHD.

Schizophrenia (SCHZ), bipolar disorder (BD), and attention-deficit/hyperactivity disorder (ADHD) share clinical symptoms and risk genes, but the shared and distinct neural dynamic mechanisms at adults remain inadequately understood. Degree is a fundamental and important graph measure in network neuroscience, and we here used eigenmodes to extend the degree to hierarchical levels and compared the resting-state brain networks of three disorders and healthy controls (HC) at adults (age: 21-50years old). First, compared to HC, SCHZ and BD patients exhibited substantially overlapped abnormalities in brain networks, wherein BD patients displayed more significant alterations. In contrast, ADHD patients exhibited few alterations. Second, compared to the graph theory measure, hierarchical degree better predicted the clinical symptoms of three disorders, and distinguished them from HC. Furthermore, three disorders shared associations of brain network abnormalities with dopamine receptors/transporters. Finally, the alterations in SCHZ and BD patients were associated with cellular localization and transport, as well as abnormal social behavior and communication, while ADHD patients were associated with energy production and transport. These findings provided a deep understanding of the shared and distinct neuropathology of three disorders and facilitated a more precise differentiation for them.

BLOOD PRESSURE MEASURING TECHNIQUES AMONG HEALTHCARE PROFESSIONALS IN KSA: A SYSTEMATIC REVIEW

Background: Accurate blood pressure (BP) measurement is critical for the diagnosis and management of hypertension, a leading cause of global morbidity and mortality. However, challenges in measurement techniques and knowledge gaps among healthcare professionals can lead to inaccurate readings, compromising patient care. This systematic review aimed to evaluate the difficulties healthcare professionals face in BP measurement and explore the variability in measurement practices. Methods: A comprehensive search of PubMed, Embase, Cochrane Library, and CINAHL databases was conducted to identify relevant studies. A total of 627 articles were initially identified. After removing 524 irrelevant articles, 103 studies were screened for eligibility. Of these, 60 full-text articles were reviewed, and two studies met the inclusion criteria. Data were synthesized to highlight common challenges and discrepancies in BP measurement practices among healthcare professionals. Results: The two included studies revealed significant challenges in BP measurement. One study identified that 60% of hospital staff in a teaching hospital lacked sufficient knowledge of fundamental BP measurement techniques. Key issues included improper understanding of cuff size, arm positioning, and deflation rates, which led to inconsistent and inaccurate readings. The other one examined BP measurement devices and methods in primary healthcare settings across Saudi Arabia. The study found that mercury sphygmomanometers were most commonly used (69.8%), followed by electronic devices (16.5%) and aneroid manometers (11.8%). However, electronic and aneroid devices were prone to measurement variations, especially in rural areas, emphasizing the need for standardized devices to reduce bias. Conclusion: This review highlights critical gaps in knowledge and variability in BP measurement methods among healthcare professionals, which can adversely impact hypertension management. Addressing these challenges requires targeted educational programs and the adoption of reliable and standardized devices to improve measurement accuracy. Enhancing BP measurement practices is essential for achieving better patient outcomes and reducing the burden of hypertension-related complications.

Impact of Building Orientation on Energy Performance of Residential Buildings in Various Cities Across Afghanistan

Building or solar orientation, a key architectural design parameter, significantly influences energy consumption in buildings. Optimizing building orientation to harness passive solar benefits is a fundamental and cost-effective measure in designing energy-efficient buildings. However, the optimal orientation varies based on geographical location, climatic conditions, and building type. Notably, Afghanistan’s building sector currently lacks tailored energy efficiency regulations. Therefore, this study investigates the impact of building orientation on the energy performance of residential buildings across nine cities in Afghanistan, each characterized by distinct climatic conditions and geographic locations, employing BEoptTM energy simulation software. The findings reveal diverse optimal orientations, dividing the country into three distinct climatic zones: subarctic (optimal orientation: south-southeast), continental (optimal orientation: south), and hot-arid (optimal orientation: north). The optimal orientations in these regions yield potential energy savings ranging from 25.6% to 48.9% compared to the least efficient orientations. These insights are critical for establishing location-specific building regulations in Afghanistan, promoting energy-efficient design, and addressing the country’s current trend of unsustainable development.

WiSleep: Smartphone-driven Sleep Population Monitoring with Unsupervised Learning

With sleep deprivation being a public health concern, sleep-monitoring technology, mainly through consumer-grade wearables, has shown value among users to better understand their most fundamental measure of health. Unfortunately, utilizing wearable technology is bound to the conditions of users owning these devices and using them to bed every night. While wearables can deliver highly personalized sleep insights to users, they inadvertently affect the ability of sleep monitoring solutions to reach unprivileged sections of society due to added costs and device accessibility. With our primary motivation to promote sleep monitoring for public health use cases at the population scale, we developed WiSleep , a sleep monitoring system that infers sleep duration from solely relying on a user’s smartphone without requiring a wearable device. Unlike prior efforts that use supervised learning methods and require labelled training data to train sleep models, our method is based on unsupervised learning, which enables easy deployment to new population groups or new regions without a need for labelled data collection and training. Specifically, we employ the smartphone activity of the user, represented by time series of WiFi network event rates, as input data to infer the user’s sleep duration (i.e., sleep time and wake time) through an unsupervised Bayesian change-point detection ensemble model. Our evaluation shows WiSleep ’s efficacy in being a low-cost accessible sleep monitoring approach. We present results that yield comparable performance to prior techniques, particularly those requiring new users’ labeled data to achieve model personalization. System evaluation from a user study achieved an average of 93.68% accuracy within 59 minutes sleep time error, 31 minutes wake time error, and 57 minutes sleep duration error by utilizing coarse-grained time series data. We demonstrate the application of our technique to predict sleep for 1000 anonymous users and enable population-scale analytics with low computational overhead.

Flame kinetics at scramjet-engine-relevant conditions: Role of prompt dissociation of weakly-bound radicals

Combustion in high-speed ram-based propulsion engines occurs under distinct thermodynamic conditions of high reactant temperatures (greater than 1000 K) and relatively low pressures (<5 atm). There is a lack of fundamental flame measurements at such conditions that result in adiabatic flame temperatures (Tad) exceeding 2500 K. In this work, we have measured laminar flame speeds of oxygen-enriched CH4/oxidizer mixtures at sub-atmospheric conditions to probe kinetics at high Tad using the isobaric spherically expanding flame approach. Simulations with recent kinetic models revealed increasing differences between data and model predictions with increasing Tad, reaching up to 25 %. Kinetic analyses reveal that at the thermodynamic conditions in these O2-enriched flames, i.e., lower pressures and higher Tad, the effects of HCO prompt dissociation are accentuated. In addition to HCO, the prompt dissociations of CH2OH and C2H5 are also considered. The prompt dissociations of all three radicals were evaluated and their effects considered in flame speed simulations. Reaction path analysis for the present flames revealed that approximately half of the reaction flux for HCO formation undergoes prompt dissociation to H + CO. Furthermore, these analyses also revealed that the pathways and sensitive reactions are similar between oxygen-enriched fuel/oxidizer mixtures and preheated fuel/air mixtures, if both have similar Tad. Thus, flames of oxygen-enriched mixtures could be a surrogate to probe the flame chemistry of highly preheated mixtures at relatively low pressures that are often encountered in ram-based propulsion engine combustors.

Impact of mixing and configurational entropies on the entropy-driven potential of mean force

Using classical density functional theory (cDFT) with the fundamental measure functional (FMF) approximation, we examine how the entropic force and its integration, the potential of mean force (PMF), between two hard walls in a polydisperse hard-body solvent vary with monomer size polydispersity (whether the solvent consists of spherical monomers or chain molecules formed by freely linked monomers) or the number of monomers in the chain solvent. Molecular dynamics simulations validate the FMF's accuracy in predicting density distributions for five- and seven-component hard sphere fluids in slit geometries, though improvements are possible at high packing fractions. The PMF calculations reveal that increasing monomer size polydispersity or the number of monomers in a chain molecule reduce entropic attraction strength at contact and lower the main potential barrier height. This reduction is due to the system's limited capacity to further increase entropy when both mixing and conformational entropies are already high. For monomer or dimer solvent, the main potential barrier position shows either monotonic or non-monotonic dependence on monomer size polydispersity, depending on bulk packing fractions, while the PMF range shortens with increasing monomer size polydispersity or chain molecule monomer number. These findings could inform the design of tunable materials.

(Invited) The Impact of "Fujishima-Honda Effect" in the Early Stage of Photoelectrochemical Research

Studies on semiconductor electrochemistry have been actively carried out since the 1950's mainly from fundamental points of view. Many reviews and books were published by the early 1970s (1-7). The paper by Fujishima and Honda on "Electrochemical Photolysis of Water at a Semiconductor Electrode" was published in Nature in 1972 (8) and it became very important as the 1st oil crisis took place in 1973 as this paper suggested that solar energy may be directly converted to chemical energy, hydrogen, by using semiconductor/aqueous electrolyte solution/metal cells.In this talk, I will describe the impact of the "Fujishima and Honda Effect" in the early days of photoelectrochemical research.References Green, in Modem Aspects of Electrochemistry, No. 2. Ed. by J. O'M. Bockris, Butterworths, London, 343-407 (1959).F. Dewald. in Semiconductors. ACS Monograph, No. 140, Ed. by N. B. Hannay, Reinhold, New York, 727-752 (1959).Gerischer.in Adv. Electrochem. Electrochem. Eng., Vol. 1, Ed. by P. Delahay, lnterscience, New York, 139-232 (1961).P. Holmes. Ed., The Electrochemistry of Semiconductors, Academic. London, 1962.V. Myamlin and Yu.V. Pleskov, Electrochemistry of Semiconductors. Plenum, New York. 1967.Gerischer, in Physical Chemistry: An Advanced Treatise, Vol. IXA. Ed. by H. Eyring. Academic. New York. 1970, Chap. 5.R. Morrison, Prog. Surf. Sci., 1(1971) 105.Fujishima and K. Honda, Nature, 238 (1972) 37.PV 77-3, "Semiconductor Liquid-Junction Solar Cells", by A. Heller.PV 82-3, "Photoelectrochemistry: Fundamental Processes and Measurement Ed. by W. L. Wallace, A. J. Nojik, and S. K. Deb.PV 88-14, "Photoelectrochemistry and Electrosynthesis on Semiconducting Materials", by D.S. Ginley, A. Nojik, N. Armstrong, K. Honda, A. Fujishima, T. Sakata, and T. Kawai.

Monte Carlo simulations towards the formation of a positronium coherent beam

Positronium (Ps) has emerged as a promising test particle within the QUantum interferometry with Positrons, positronium and LASers (QUPLAS) project, which aims to measure for the first time the gravitational effect on Ps, the entirely leptonic atom comprising an electron and a positron. In this work, we present a Monte Carlo simulation to generate a mono-energetic and highly coherent Ps beam by creating a negative Ps ion (Ps− consisting of two electrons and one positron) to be used in a Mach–Zehnder interferometer. We propose the equations to estimate the initial velocity distributions in the longitudinal and transversal directions of the Ps− emitted from the target converter (positron/Ps−) necessary for the Monte Carlo simulation. The resulting simulated device needs a very low divergence Ps beam at the interferometer entrance, for this reason an intensive positron beam is necessary, such as a high-flux electron LINAC. Subsequently, we utilize a Fabry–Perot IR laser cavity operating in CW at a wavelength of 1560 nm to selectively remove the extra electron. An alternative pulsed laser operating at a 3600 nm wavelength was studied to reduce broadening due to recoil and excitation. Here, we provide a Monte Carlo simulation to estimate the characteristics of the Ps beam, including its energy distribution and intensity profiles at two different temperatures (10 K and 300 K). Despite the limitations given by the assumptions mentioned in the text within the limit of our knowledge, these first simulation results obtained from our study will provide essential groundwork for future advancements in fundamental particles gravity measurements.

A Free-Standing Boron-Doped Diamond Grid Electrode for Fundamental Spectroelectrochemistry.

Spectroelectrochemistry (SEC) is a powerful technique that enables a variety of redox properties to be studied, including formal potential (Eo), thermodynamic values (ΔG, ΔH, ΔS), diffusion coefficient (D), electron transfer stoichiometry (n), and others. SEC requires an electrode which light can pass through while maintaining sufficient electrical conductivity. This has been traditionally composed of metal or metal oxide films atop transparent substrates like glass, quartz, or metallic mesh. Robust electrode materials like boron-doped diamond (BDD) could help expand the environments in which SEC can be performed, but most designs are limited to thin films (∼100-200 nm) on transparent substrates less resilient than free-standing BDD. This work presents a free-standing BDD grid electrode (G-BDD) for fundamental SEC measurements, using the well-characterized Fe(CN)63-/4- redox couple as proof-of-concept. With a combination of cyclic voltammetry (CV), thin-layer SEC, and chronoabsorptometry, several of the redox properties mentioned above were calculated and compared. For Eo', n, and D, similar results were obtained when comparing the CV [Eo' = +0.279 (±0.002) V vs Ag/AgCl; n = 0.97; D = 4.1 × 10-6 cm2·s-1] and SEC [Eo' = +0.278 (±0.001) V vs Ag/AgCl; n = 0.91; D = 5.2 × 10-6 cm2·s-1] techniques. Both values align with what has been previously reported. To calculate D from the SEC data, modification of the classical equation used in chronoabsorptometry was required to accommodate the G-BDD electrode geometry. Overall, this work expands on the applicability of SEC techniques and BDD as a versatile electrode material.

DOENÇA RENAL CRÔNICA CONCOMITANTE À ERLIQUIOSE: RELATO DE CASO

Kidney disease can range from acute kidney injury to chronic kidney disease, often caused by inflammation that impairs filtration. When kidney function is compromised, toxins accumulate, which can lead to kidney failure. In advanced cases, dialysis treatment becomes necessary. Other associated pathologies, such as ehrlichiosis, can make the condition irreversible. Ehrlichiosis triggers an inflammatory response affecting the kidneys, with the formation of immune complexes during infection. These complexes deposit in the renal capillaries, causing glomerulonephritis, an inflammation that impairs the function of the glomeruli, responsible for blood filtration. The purpose of this report is to present a case where kidney disease developed concomitantly with ehrlichiosis. In this case, an animal was referred to a veterinary hospital for dialysis treatment due to kidney disease. Laboratory tests were conducted, including a complete blood count, biochemical analysis, rapid ehrlichiosis test, and PCR, which confirmed the presence of active ehrlichiosis infection. Additionally, hemodialysis and dialysis sessions were performed, among other treatments. This case highlights the complexity and challenges of treating chronic kidney disease aggravated by ehrlichiosis, emphasizing the importance of advanced therapies and the need for ethical planning to balance available resources and the animal's quality of life. Raising awareness among pet owners about the risks, the importance of early diagnosis, correct treatment, and continuous monitoring are fundamental measures that can help in the early detection of kidney impairment and increase the chances of successful treatment.

A statistical mechanics investigation of unfolded protein response across organisms

Living systems rely on coordinated molecular interactions, especially those related to gene expression and protein activity. The Unfolded Protein Response is a crucial mechanism in eukaryotic cells, activated when unfolded proteins exceed a critical threshold. It maintains cell homeostasis by enhancing protein folding, initiating quality control, and activating degradation pathways when damage is irreversible. This response functions as a dynamic signaling network, with proteins as nodes and their interactions as edges. We analyze these protein-protein networks across different organisms to understand their intricate intra-cellular interactions and behaviors. In this work, analyzing twelve organisms, we assess how fundamental measures in network theory can individuate seed proteins and specific pathways across organisms. We employ network robustness to evaluate and compare the strength of the investigated protein-protein interaction networks, and the structural controllability of complex networks to find and compare the sets of driver nodes necessary to control the overall networks. We find that network measures are related to phylogenetics, and advanced network methods can identify main pathways of significance in the complete Unfolded Protein Response mechanism.

A BIOSSEGURANÇA NO ÂMBITO DA ODONTOLOGIA: REVISÃO DA LITERATURA

Kidney disease can range from acute kidney injury to chronic kidney disease, often caused by inflammation that impairs filtration. When kidney function is compromised, toxins accumulate, which can lead to kidney failure. In advanced cases, dialysis treatment becomes necessary. Other associated pathologies, such as ehrlichiosis, can make the condition irreversible. Ehrlichiosis triggers an inflammatory response affecting the kidneys, with the formation of immune complexes during infection. These complexes deposit in the renal capillaries, causing glomerulonephritis, an inflammation that impairs the function of the glomeruli, responsible for blood filtration. The purpose of this report is to present a case where kidney disease developed concomitantly with ehrlichiosis. In this case, an animal was referred to a veterinary hospital for dialysis treatment due to kidney disease. Laboratory tests were conducted, including a complete blood count, biochemical analysis, rapid ehrlichiosis test, and PCR, which confirmed the presence of active ehrlichiosis infection. Additionally, hemodialysis and dialysis sessions were performed, among other treatments. This case highlights the complexity and challenges of treating chronic kidney disease aggravated by ehrlichiosis, emphasizing the importance of advanced therapies and the need for ethical planning to balance available resources and the animal's quality of life. Raising awareness among pet owners about the risks, the importance of early diagnosis, correct treatment, and continuous monitoring are fundamental measures that can help in the early detection of kidney impairment and increase the chances of successful treatment.

OPTIMIZING AUTHENTICATION SECURITY IN INTELLIGENT SYSTEMS THROUGH VISUAL BIOMETRICS FOR ENHANCED EFFICIENCY

Context. The primary objective of this article is to explore aspects related to ensuring security and enhancing the efficiency of authentication processes in intelligent systems through the application of visual biometrics. The focus is on advancing and refining authentication systems by employing sophisticated biometric identification methods. Objective. A specialized intelligent system has been developed, utilizing a Siamese neural network to establish secure user authentication within the existing system. Beyond incorporating fundamental security measures such as hashing and secure storage of user credentials, the contemporary significance of implementing two-factor authentication is underscored. This approach significantly fortifies user data protection, thwarting most contemporary hacking methods and safeguarding against data breaches. The study acknowledges certain limitations in its approach, possibly affecting the generalizability of the findings. These limitations provide avenues for future research and exploration, contributing to the ongoing evolution of authentication methodologies in intelligent systems. Method. The two-factor authentication system integrates facial recognition technology, employing visual biometrics for heightened security compared to alternative two-factor authentication methods. Various implementations of the Siamese neural network, utilizing Contrastive loss function and Triplet loss function, were evaluated. Subsequently, a neural network employing the Triplet loss function was implemented and trained. Results. The article emphasizes the practical implications of the developed intelligent system, showcasing its effectiveness in minimizing the risk of unauthorized access to user accounts. The integration of contemporary authentication methodologies ensures a secure and robust user authentication process. Conclusions. The implementation of facial recognition technology in authentication processes has broader social implications. It contributes to a more secure digital environment by preventing unauthorized access, ultimately safeguarding user privacy and data. The study’s originality lies in its innovative approach to authentication, utilizing visual biometrics within a Siamese neural network framework. The developed intelligent system represents a valuable contribution to the field, offering an effective and contemporary solution to user authentication challenges.

A Theoretical Framework to Quantify Ecosystem Pressure-Volume Relationships.

'Water potential' is the biophysically relevant measure of water status in vegetation relating to stomatal, canopy and hydraulic conductance, as well as mortality thresholds; yet, this cannot be directly related to measured and modelled fluxes of water at plot- to landscape-scale without understanding its relationship with 'water content'. The capacity for detecting vegetation water content via microwave remote sensing further increases the need to understand the link between water content and ecosystem function. In this review, we explore how the fundamental measures of water status, water potential and water content are linked at ecosystem-scale drawing on the existing theory of pressure-volume (PV) relationships. We define and evaluate the concept and limitations of applying PV relationships to ecosystems where the quantity of water can vary on short timescales with respect to plant water status, and over longer timescales and over larger areas due to structural changes in vegetation. As a proof of concept, plot-scale aboveground vegetation PV curves were generated from equilibrium (e.g., predawn) water potentials and water content of the above ground biomass of nine plots, including tropical rainforest, savanna, temperate forest, and a long-term Amazonian rainforest drought experiment. Initial findings suggest that the stored water and ecosystem capacitance scale linearly with biomass across diverse systems, while the relative values of ecosystem hydraulic capacitance and physiologically accessible water storage do not vary systematically with biomass. The bottom-up scaling approach to ecosystem water relations identified the need to characterise the distribution of water potentials within a community and also revealed the relevance of community-level plant tissue fractions to ecosystem water relations. We believe that this theory will be instrumental in linking our detailed understanding of biophysical processes at tissue-scale to the scale at which land surface models operate and at which tower-based, airborne and satellite remote sensing can provide information.

Lattice Fundamental Measure Theory Beyond 0D Cavities: Dimers on Square Lattices

Using classical density functional theory, we study the behavior of dimers, i.e. hard rods of length L=2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$L=2$$\\end{document}, on a two-dimensional cubic lattice. For deriving a free energy functional, we employ Levy’s prescription which is based on the minimization of a microscopic free energy with respect to the many-body probability under the constraint of a fixed density profile. Using that, we recover the "0D cavity" functional originally found by Lafuente and Cuesta and derive an extension by applying a more general "cluster density functional theory" method introduced by Lafuente and Cuesta as well. Moreover, we introduce a new free energy functional, which is based on approximated configurational probabilities. Both derived free energy functionals are exact on cavities that can hold at most two particles simultaneously. The first functional allows to improve the prediction of the free energy in bulk and both of them improve the prediction in highly confined systems, especially for high packing fractions, in comparison to the "0D cavity" functional.

Physical Patrol and Border Security Management at the Namanga One Stop Boarder Post, Kenya

Border administration encompasses all legal and administrative measures a sovereign state implements to secure, protect, and strengthen the sovereignty, security, safety, and integrity of its territory. Consequently, it is essential to any national migration strategy. The border administration policies emphasize the necessity for all participants in border management to be engaged to enhance the effectiveness of border operations. Security measures are normally enhanced along the border posts to improve on the national security of a given country by preventing entrance of terrorists, illegal goods and human trafficking. These security measures ensure safety at the border. The primary objective was to evaluate the effects of physical patrol on border security management at the Namanga one stop boarder post, Kenya. A descriptive survey research design was utilized. The population comprised of the employees at the Namanga OSBP, including police officers, customs officials, immigration officers, and National Intelligence Service employees, among others. The research used stratified random sampling. The data was collected via the use of questionnaires. Data analysis was done with the help of SPSS and then presented using tables, percentages, graphs and pie charts. This study found out that border security is complex and it requires various interventions, which entails a combination of technology and human security personnel for effective operations. In regard to objective one, the researcher finds that physical patrol emerges as a fundamental border security management measure, and is considered essential in enhancing security at the border point by minimizing insecurity incidents and eliminating potential of border security breaches. Based on the findings, this study concluded that various security measures, including physical patrols, integrated scanning, and electronic monitoring, are essential in the management of border security and in enhancing services. A major recommendation of the study is to promote greater multi-agency and multi-stakeholder collaboration as a means of detaining individuals attempting to enter a country illegally and effectively seizing any contraband goods. This necessitates more efficient border patrols and surveillance strategies.

Capturing autonomy, competence, and relatedness at work: further examining and validating an English language version of the work-related basic need satisfaction scale.

Self-Determination Theory (SDT) maintains that the satisfaction of the basic psychological needs for autonomy, competence, and relatedness is associated with optimal individual functioning, including in the workplace. A self-report instrument, the Work-related Basic Need Satisfaction scale (W-BNS), has previously been developed and validated in Dutch and Italian. We aimed to validate an English version of the W-BNS. We also evaluated a bifactor model to assess the extent to which the item responses could be explained by a single, underlying general latent trait. A Rasch calibration was also carried out to assess the extent to which the scores conformed to the assumptions of 'fundamental measurement' and could be converted to a common metric. We used data from 141 staff employed by a large UK-based mental health service provider. The postulated three-factor structure provided a good fit to the data. However, a bifactor model, introducing an underlying general factor, provided a superior fit. The items generally conformed to the Rasch measurement model. Evidence of convergent/divergent validity was observed via the correlations between the W-BNS scores and those for the Basic Psychological Needs Satisfaction and Frustration Scale (BPNFS). Regarding construct validity, both the separate needs and total W-BNS scores statistically significantly predicted an individual's reported intention to leave the current employer. Our findings foster research with the WBNS and have implications for how the W-BNS is optimally implemented in practice as a useful brief tool for assessing staff work-related need satisfaction.

Prediction OPEC oil price utilizing long short-term memory and multi-layer perceptron models

The present study undertakes a comprehensive assessment of two predictive models, namely Long Short-Term Memory (LSTM) and Multi-layer Perceptron (MLP), with a specific emphasis on their effectiveness in predicting oil prices, particularly those of the Petroleum Exporting Countries (OPEC). In this study, three fundamental statistical measures are utilized: The Symmetric Mean Absolute Percentage Error (SMAPE), the Mean Squared Error (MSE), and the Mean Absolute Percentage Error (MAPE). The results demonstrate that the LSTM model regularly surpasses the MLP model in the three benchmarks. In particular, the LSTM model demonstrates lower values for SMAPE, MSE, and MAPE, indicating higher prediction accuracy. The decreased error scores linked to the LSTM model highlight its improved capacity for precise oil price prediction in comparison to the MLP model. These results signify a notable progress in the use of machine learning techniques for predicting OPEC oil prices. Moreover, this study provides invaluable perspectives for OPEC management, policymakers, and organizations focused on oil price fluctuations, therefore contributing to the wider endeavour of enhancing the stability and economic sustainability of the oil pricing system in OPEC countries. The consequences of the study include the promotion of a pricing system that facilitates the achievement of economic and social development goals in these countries.