Percentage Deviation Research Articles

Global warming: Nursing students’ knowledge and attitudes

This study was conducted to evaluate the knowledge and attitudes of nursing students, who are the health professionals of the future, towards global warming. 113 senior nursing students participated in this descriptive and relationship seeking study. Personal Information Form, Global Warming Knowledge Scale and Global Warming Attitude Scale were used to collect data. Percentage, mean and standard deviation were used to determine the socio-demographic characteristics of the students. T test, one-way ANOVA, Tukey test were used for multiple comparisons to determine the difference between groups and Pearson correlation analysis were used to determine the relationship between scales to compare the socio-demographic characteristics and scores of the students from the scales. In the study, it was determined that the education levels of the families and the students' grade point averages affected their knowledge and attitude levels and that the score difference between them was statistically significant. A positive correlation was found between global warming knowledge and attitude levels. It was predicted that health problems that will arise as a result of global warming should be included in the nursing curriculum.

Performance Evaluation of PρT-SAFT, PρT-PC-SAFT, PC-SAFT, and CPA Equations of State for Predicting Density, Thermal Expansion Coefficient, Isothermal Compressibility, Isobaric Heat Capacity, Speed of Sound, and Saturated Vapor Pressure of Three Pure Ethylene Glycols and Their Mixtures

Ethylene glycols are a group of versatile industrial solvents with broad applications across various sectors. Accurate thermodynamic modeling of these compounds is essential for enhancing their utilization and optimizing industrial processes. Among the advanced models available, the Statistical Associating Fluid Theory (SAFT) type equation of state (EoS) stands out for its effectiveness in capturing the thermodynamic behavior of complex fluids. This study employs the PρT-SAFT, PρT-PC-SAFT, PC-SAFT, and CPA EoSs to model pure monoethylene glycol (MEG), diethylene glycol (DEG), triethylene glycol (TEG), and their mixtures. Furthermore, the predictive capabilities of these models are critically evaluated for polyethylene glycol 400 (PEG 400). The performance of the PρT-SAFT, PρT-PC-SAFT, PC-SAFT, and CPA EoSs was evaluated for predicting key thermodynamic properties, including density, thermal expansion coefficient, isothermal compressibility, isobaric heat capacity, speed of sound, and saturated vapor pressure, for pure MEG, DEG, TEG, and PEG 400. Among the models, the PρT-SAFT demonstrated superior accuracy in modeling their properties. Subsequently, the volumetric properties and vapor–liquid equilibrium data of binary mixtures of MEG, DEG, and TEG were predicted using the same EoSs, without incorporating any binary interaction parameters. Under these conditions, the PρT-SAFT achieved the highest accuracy. Furthermore, predictions of the volumetric properties for the ternary mixture of MEG, DEG, and TEG also indicated that the PρT-SAFT outperformed the other models. The overall average absolute deviation percentages for the PρT-SAFT, PρT-PC-SAFT, PC-SAFT, and CPA EoSs across all examined thermodynamic properties and systems were 7.0, 8.2, 22.2, and 30.2, respectively, confirming the robustness of the PρT-SAFT.

The Efficiency of Temperature-Controlled Inventory Management: A Case Study of Convenience Store in Salaya Sub-District, Nakhon Pathom Province

Background and Aims: Current logistics management is an important goal that entrepreneurs can use as a source of competitive advantage. Both at the business level and national level. This is because of globalization that has resulted in more intense business competition. And greater trade liberalization As a result, the business sector must upgrade its ability to conduct business in every possible way. The purposes of this research were 1) to investigate the efficiency of temperature-controlled inventory management by studying personal factors, namely work experience, number of employees, position, and monthly average income. And study to investigate the factors of the inventory management system that affect the efficiency of temperature-controlled inventory management in convenience stores. Methodology: The questionnaire was used as a research instrument, it was collected from 15 samples. and collected the direct interviews with managers and employees who administer the inventory control. The statistics that were used were percentage, mean, and standard deviation. The statistics that were used to test the hypothesis were One-Way ANOVA. Results: The result of this study showed that among the sample of 15 convenience store staff, it was found that most of the staff had 1-5 years of work experience, with employees between 11-20 people in general positions, and an average personal monthly income of 10,001-20,000 baht. The hypothesis testing results revealed that the significance of the variables, work experience, position, and average monthly income was greater than the 0.05 level of significance. This indicated that despite differences in work experience, position, and average monthly income, there was no difference in the efficiency of temperature-controlled inventory management for the convenience store in Salaya, Nakhon Pathom. The results of the regression coefficient test revealed that there is only one independent variable had a significant impact on the efficiency of temperature-controlled inventory management of convenience stores. It was the replenishment system. The forecast coefficient was 40.8%. The remaining 59.2% is another factor apart from those mentioned above. For the replenishment system, according to the research results, entrepreneurs should pay great attention to product replenishment and always keep up with the needs of customers to be able to have enough customer service inventory. Conclusion: Work experience, position, and average monthly income do not affect the efficiency of temperature-controlled inventory management of convenience stores in the Salaya Subdistrict. The product replenishment system has an important effect on this efficiency at 40.8 percent. Product replenishment is a factor that entrepreneurs should give importance to to have sufficient inventory and meet customer demand in time.

Photovoltaic-Thermal Side-Absorption Concentrated Module with Micro-Structures as Spectrum-Division Component for a Hybrid-Collecting Reflection Solar System

A photovoltaic-thermal side-absorption concentrated module (PT-SACM) based on spectrum division for photovoltaic-thermal hybrid applications is carried out. In order to reduce the absorption by materials and the axial-chromatic aberration caused by the transmissive optical system and to improve the performance of the entire system, a reflective system, the parabolic mirror array, fabricated by the ultra-precision diamond turning technology, is proposed herein. For the purposes of spectrum division, thinner volume, lightweight, and wide acceptance angle, the proposed module is designed with a diffraction optical element (DOE), a light-guide plate with a micro-structure array and a parabolic mirror array. Among them, the DOE can separate the solar spectrum into the visible band, which is converted to electrical energy via photovoltaics, and the infrared band, whose thermal energy is collected. Experimental measurements show that the overall optical efficiency of the entire system reached 38.32%, while a deviation percentage of 3.5% is calculated based on the simulation. The system has successfully demonstrated the separation of visible and infrared bands of the solar spectrum. Meanwhile, the lateral displacement between the micro-structures of the light-guide plate and the focus of the parabolic mirror array can be used to compensate for the angular deviation of the sun incidence, thereby achieving wide-angle acceptance via the proposed solar concentration system.

N45 The Words of Bowels: Exploring Crohn's Disease through Metaphors

Abstract Background Crohn’s disease causes patients to cope with many symptoms and conditions during the course of illness, treatment and therapy. Patients experience psychosocial symptoms as well as physical symptoms. The metaphors with which patients describe their illnesses are important in terms of the disease process and compliance with treatment. This study was conducted to explore the meanings patients attribute to Crohn's disease through metaphors. Methods This study employed a phenomenological design and a qualitative research approach. It was conducted with 102 patients who consented to participate in research at the inflammatory bowel diseases clinic of a university hospital from January 15 to March 30, 2024. Data were collected through socio-demographic information, the Harvey-Bradshaw Index, and the completion of the sentence "Crohn's disease is like/because..." Participants produced metaphors that were categorized and presented with supporting examples. Demographic data were analyzed using frequency, percentage, mean, and standard deviation, calculated using IBM SPSS Statistics v26.0. Qualitative data were evaluated using content analysis. Results Participants with a mean age of 39.68±3.71 years created 80 metaphors about Crohn's disease. These metaphors were analyzed in 8 categories: loss of control, uncertainty, destruction/exhaustion, long process, suffering, transformation/change, care and support needs, and hope. The most frequently used metaphors are nightmare, flower, child, enemy, darkness, and snake. Conclusion The most common metaphors used by Crohn's disease patients are nightmare, flower, child, enemy, darkness, and snake. How patients make sense of their illnesses should be evaluated throughout the process by healthcare professionals and the care and treatment process should be planned.

Comparison of 1D and 3D volume measurement techniques in NF2-associated vestibular schwannoma monitoring

To compare 1D (linear) tumor volume calculations and classification systems with 3D-segmented volumetric analysis (SVA), focusing specifically on their effectiveness in the evaluation and management of NF2-associated vestibular schwannomas (VS). VS were clinically followed every 6 months with cranial, thin-sliced (< 3 mm) MRI. We retrospectively reviewed and used T1-weighted post-contrast enhanced (gadolinium) images for both SVA and linear measurements. 3D-SVA was performed manually or combined with semiautomated segmentation by using axial planes. The maximum linear dimensions (MLD) were determined in three dimensions (anteroposterior, transverse, and craniocaudal planes) using axial and coronal planes. The MLD was cubed (MLD3), and orthogonal analysis (OA) was derived to establish comparability with the SVA. The Hannover and Koos classification was used to depict the size ratio in each MRI and tumor. A linear regression model was performed to compare 1D/classification systems to SVA, and the percentage deviation change of MLD3 and OA to SVA was established using a one-way multivariate variance analysis. 2586 SVA and 10344 linear measurements were performed in a cohort of 149 NF2 patients and 292 associated VS. All measurement techniques (MLD3, OA, KOOS, and Hannover) significantly (and strongly, r2 > 0.5) correlated with SVA (p < 0.001). The OA showed an even stronger positive correlation than the MLD3 to SVA. Smaller classified tumors (T1/T2, K1/K2) exhibited a low-moderate positive correlation (r2 = 0.23–0.44) compared to medium-sized (T3, K2/3) and large tumors (T4, K4; r2 = 0.54–0.76). Pre- and postoperative MLD3 and OA statistically significantly predict SVA (p < 0.001), but the postoperative correlation was weaker, particularly for MLD3 to SVA values. All analyses showed a large scatter range. In the percentage deviation analysis of MLD3 and OA from SVA, small tumors (K1/K2, T1/T2) were overestimated. Compared to the SVA, the MLD3 and especially the OA are a time-saving alternative for monitoring the tumor volume of NF2-associated VS. However, the scatter range in small/surgically reduced tumors is enormous. For this reason, they are not recommended for monitoring off-label therapy with Bevacizumab or for treatment decisions depending on a precise assessment of tumor volume and growth. Developing deep learning-based volume determinations in the future is essential to reduce SVA’s time intensity.

유아 사회정서발달 지원과 평가에 대한 교사 인식 및 현황

Objectives The purposes of this study were to address early childhood teachers’ perceptions and current use of support and evaluation for preschool children’s social emotional development to enhance their social emotional development in early childhood institutions. Methods The sample consisted of 248 teachers working in early childhood institutions located in Seoul, Gyeongi, and Incheon. A questionnaire, based on literature analysis, was tested with 10 preschool teachers and validated for content by early childhood experts. The questionnaire consisted of 36 items including 7 items about teachers’ background and was distributed through an online survey system. Using SPSS, the data was calculated in frequency, percentage, average, and standard deviation. Results The major findings show that the teachers recognized a need for supporting and evaluating preschool children’s social emotional development, however, the implementations and satisfactions are less compared with their perception. More than half of the teachers did not evaluate social emotional development due to lack of knowledge about evaluation methods and no request from the institutions. The teachers experience challenges in supporting and evaluating social emotional development because of high teacher-child ratio, lack of time and reliable evaluation tools. To overcome these difficulties, they demand for more teachers and social emotional development curriculum. Conclusions It is necessary to assist teachers to perceive importance of supporting and evaluating preschool children’s social emotional development and provide working environments that they can implement social emotional practices. Also, professional development program on social emotional development programs, evaluation methods and tools are necessary.

Contribution of Home Gardening to the Welfare of Rural Households in Osun State Nigeria

Purpose: This study describes the socio-economic characteristics of rural households, identifies the agricultural activities practiced in the home gardens, examines the respondents’ perception of home gardening, determines the contribution of home gardening to the households’ welfare, and investigates constraints to the practice of home gardening in the studied area.Research Method: A sample of 150 rural households from three Agricultural zones (Osogbo, Ife-Ijesha, and Iwo) was selected using a multistage sampling procedure. Data were collected through a structural interview schedule comprising both open and close-ended questions and the data were summarized using descriptive statistics such as frequency, percentage, mean and standard deviation; along with inferential statistics like Chi-Square and Pearson Product Moment Correlation.Findings: The result revealed that the mean age of household heads was 45.09±15.08 years. Additionally, the majority had received their first experience of home gardening in childhood (71.2%) and expressed willingness to continue home gardening practice (92.4%). Furthermore, they engaged in plantain cultivation (x = 2.50) always and fowl rearing (x = 2.16) often in their home gardens, among other activities. The majority (90.7%) was favourably disposed to home gardening and indicated a high contribution (86.4%) of home gardening to their households’ welfare. In addition, pilfering (x = 1.51) was identified as a serious constraint to the practice of home gardening.Research Limitation: The economic importance and marketing aspect of home gardening are not covered due to limited resources.Originality/ Value: The study provides insight into how home gardening could be incorporated into the extension activities of relevant organizations to enhance the full exploitation of the potentials inherent in the practice.

Rapid Identification of Saline–Alkali Stress-Tolerant Peanut Varieties Based on Multimodal Data

The cultivation of saline–alkali-tolerant peanut (Arachis hypogaea L.) varieties can effectively increase grain yield in saline–alkali land. However, traditional assessment methods are often cumbersome and time consuming. To rapidly identify saline–alkali stress-tolerant peanut varieties, this research proposed a saline–alkali stress tolerance evaluation method based on deep learning and multimodal data. Specifically, the research first established multimodal datasets for peanuts at different growth stages and constructed a saline–alkali stress score standard based on unsupervised learning. Subsequently, a deep learning network called BO-MFFNet was built and its structure and hyperparameters were optimized by the Bayes optimization (BO) algorithm. Finally, the point prediction of the saline–alkali stress score were carried out by using the Gaussian process regression model. The experimental results show that the multimodal method is superior to the single-modal data and the BO algorithm significantly improves the performance of the model. The root mean squared error and relative percentage deviation of the BO-MFFNet model are 0.089 and 3.669, respectively. The model effectively predicted the salt–alkali stress tolerance of five varieties, and the predicted results were Huayu25, Yuhua31, Yuhua33, Yuhua32, and Yuhua164 from high to low. This research provides a new method for assessing crop tolerance under extreme environmental stress.

Efficacy of the Roy Adaptation Model with smartphone training in reducing urinary tract infection in pediatric clean intermittent catheterization: a prospective study

PurposeStudy aimed to compare incidence of urinary tract infection (UTI), type of bacteria grown, development of antibiotic resistance over 2 years in children whose caregivers underwent training based on the Roy Adaptation Model with an android phone application for patients clean intermittent catheterization (RAMACIC) versus those whose caregivers received routine training in hospital.MethodThis study was conducted as a descriptive, prospective study with 40 patients and caregivers between October 2021 and 2023 as a continuation of a previously conducted randomized controlled experimental study by the researchers. Data were collected the “Participant Form,” and “Urine Test Form” analyzed with the SPSS 22 package. Descriptive data were determined by number (n), percentage (%), mean, and standard deviation. The frequency of UTI between the two groups was determined by the Chi-square test, and the effect size of the data was determined by Cramer’s V value of the Chi-square test.ResultsA significant reduction in UTI incidence among children of RAMACIC-trained caregivers during the first, second, third, and fourth 6-month periods compared with those under routine CIC training was observed (p < 0.05). It was determined that E. coli was the most frequently grown bacteria in both groups, with a higher rate in the group receiving routine training in the hospital, and antibiotic resistance was higher in the group receiving routine training in the hospital compared with RAMACIC.ConclusionRAMACIC, when administered to caregivers, effectively lowers the long-term risk of UTI development in patients undergoing CIC, also effective in reducing the antibiotic resistance that developed in patients.

Bridging the gap: understanding the perspective of healthcare professional students towards precision medicine in a Nigerian tertiary institution (a cross-sectional study)

BackgroundIndividuals often respond differently to medications, giving rise to the field of precision medicine (PM), which focuses on tailoring treatments to individual genetic, environmental, and lifestyle factors. This study examined the level of comfort healthcare professional students have with their knowledge of precision medicine, alongside their attitudes and perceptions toward precision medicine, at a tertiary institution in Nigeria.MethodsA cross-sectional questionnaire-based study was conducted among healthcare professional students (400–600 level) at the University of Nigeria Nsukka between January and March 2024. The data were analyzed via IBM Statistical Product and Service Solutions (SPSS) for Windows version 27. Descriptive analyses (frequency, percentage, mean, and standard deviation) and chi-square tests were used to summarize and compare the variables. Statistical significance was set at p < 0.05.ResultsA total of 431 healthcare professional students participated in this study. Fewer than half (n = 200, 46.4%) were pharmacy students, and the majority were within the age range of 21–25 years (n = 288, 66.8%). Nearly half (n = 206, 47.8%) reported having information about precision medicine from the internet, and the majority (n = 341, 79.1%) expressed having an interest in a career involving research in precision medicine. More than half of the students (n = 240, 55.7%) were comfortable with their knowledge of precision medicine and had favourable attitudes (n = 236, 54.8%). Additionally, more than half had positive perceptions of ethical concerns (n = 216, 50.1%) and education in precision medicine (n = 239, 55.5%). Gender, age, department, level of study, awareness of PM, and interest in a career involving research were significantly associated with students’ knowledge, attitudes, and perceptions of precision medicine (p < 0.001).ConclusionHealthcare professional students were comfortable with their knowledge of PM and, in addition, had favourable attitudes and positive perceptions toward the use of precision medicine.

Food needs and health behaviors in the COVID-19 situation: a case study of quarantined communities in densely populated areas of Bangkok, Thailand

BackgroundThe Thai government’s initial response to the novel coronavirus disease 2019 (COVID-19) led to confusion and food insecurity in quarantined low-income communities. Although free food programs were initiated, no official assessment of their impact exists. The objective of this study was to evaluate the effectiveness of these food programs by surveying the food requirements, food needs, and health behaviors of quarantined, densely populated communities in Bangkok.MethodsA cross-sectional descriptive study was conducted with 410 urban dwellers from quarantined communities who received free food assistance. Data were collected via a questionnaire on food requirements, food hygiene, food needs, and health behaviors during the COVID-19 epidemic. The data were analyzed in terms of frequency, percentage, mean, and standard deviation. The associations between demographic characteristics, food needs, and health behaviors were analyzed using logistic regression.ResultsThe participants demanded dried/canned food (54.9%) and three meals per day (64.9%), while the majority of the food provided consisted of rice and side dishes (96.2%) that were clean and qualified. In consideration of food needs, a high level of demand was observed in the first three levels: enough food, acceptable food, and reliability. Overall, dietary health behaviors were good. Logistic regression analysis revealed that being elderly (AOR = 3.67, 95% CI = 1.63–8.27) and having a moderate to high income level (AOR = 3.93, 95% CI = 2.23–6.94) were positively correlated with food needs. Similarly, good health behaviors were positively correlated with being female (AOR = 1.74, 95% CI = 1.12–2.69), being elderly (AOR = 3.73, 95% CI = 1.72–8.08), and having a moderate to high income level (AOR = 3.76, 95% CI = 2.38–5.93).ConclusionsPreparing for future crises requires the consideration of demographic factors that influence food needs, personal choices, and dietary health behaviors. Future food assistance programs should focus on the provision of nonperishable and long-lasting food, which will ensure the consistent availability of three meals per day.

Optical anisotropy effects in laminated tempered glass

Minor fluctuations in the tempering process of architectural glass lead to residual stress differences resulting in birefringence and undesired optical iridescence, also known as anisotropy effects. The control of anisotropies, which are quantified as optical retardation, is limited to monolithic glass. In modern architecture, laminated glass panes consisting of an interlayer of polyvinyl butyral or ionomer (SentryGlas®) are frequently applied. In this paper, photoelastic studies are performed on laminated glass panes before and after the lamination process to evaluate their effect and to investigate the influence of the superposition of different orientated glass panes. An influence from the interlayer is not markedly evident. Aside from a few outliers, there are percentage deviations of less than 6% in the 95% quantile value. The influence of the retardation pattern of the individual sheets is significant; depending on their position in the furnace, the superposition of the individual glass sheets results in a dot-shaped or a strip-shaped pattern. The experiments have demonstrated that retardation can be cumulative or reduced depending on the azimuth angle of the individual retardation value. Finally, six glass panes were installed in an outdoor test rig to observe the optical appearance under various light condition and different viewing points. Here, a correlation of the findings from the previous retardation measurements is clearly revealed.

A Hybrid Honey Badger Algorithm to Solve Energy-Efficient Hybrid Flow Shop Scheduling Problems

A well-planned schedule is essential to any organization’s growth. Thus, it is important for the literature to cover a more comprehensive range of scheduling problems. In this paper, energy-efficient hybrid flow shop (EEHFS) scheduling problems are considered. Researchers have developed several techniques to deal with EEHFS scheduling problems. Also, researchers have recently proposed several metaheuristics. Honey Badger Algorithm (HBA) is one of the most recent algorithms proposed to solve various optimization problems. The objective of the present work is to solve EEHFS scheduling problems using the Hybrid Honey Badger Algorithm (HHBA) to reduce the makespan (Cmax) and total energy cost (TEC). In the HHBA, a constructive heuristic known as the NEH heuristic was incorporated with the Honey Badger Algorithm. The suggested algorithm’s performance was verified using an actual industrial scheduling problem. The company’s results are compared with those of the HHBA. The HHBA could potentially result in an 8% decrease in total energy cost. Then, the proposed algorithm was applied to solve 54 random benchmark problems. The results of the proposed HHBA were compared with the FIFO dispatching rule, the NEH heuristic, and other metaheuristics such as the simulated annealing (SA) algorithm, the genetic algorithm (GA), the particle swarm optimization (PSO) algorithm, Honey Badger Algorithm, and the Ant Colony Optimization (ACO) algorithms addressed in the literature. Average percentage deviation (APD) was the performance measure used to compare different algorithms. The APD of the proposed HHBA was zero. This indicates that the proposed HHBA is more effective in solving EEHFS scheduling problems.

Diet Quality and Caloric Accuracy in AI-Generated Diet Plans: A Comparative Study Across Chatbots.

Background/Objectives: With the rise of artificial intelligence (AI) in nutrition and healthcare, AI-driven chatbots are increasingly recognised as potential tools for generating personalised diet plans. This study aimed to evaluate the capabilities of three popular chatbots-Gemini, Microsoft Copilot, and ChatGPT 4.0-in designing weight-loss diet plans across varying caloric levels and genders. Methods: This comparative study assessed the diet quality of meal plans generated by the chatbots across a calorie range of 1400-1800 kcal, using identical prompts tailored to male and female profiles. The Diet Quality Index-International (DQI-I) was used to evaluate the plans across dimensions of variety, adequacy, moderation, and balance. Caloric accuracy was analysed by calculating percentage deviations from requested targets and categorising discrepancies into defined ranges. Results: All chatbots achieved high total DQI-I scores (DQI-I > 70), demonstrating satisfactory overall diet quality. However, balance sub-scores related to macronutrient and fatty acid distributions were consistently the lowest, showing a critical limitation in AI algorithms. ChatGPT 4.0 exhibited the highest precision in caloric adherence, while Gemini showed greater variability, with over 50% of its diet plans deviating from the target by more than 20%. Conclusions: AI-driven chatbots show significant promise in generating nutritionally adequate and diverse weight-loss diet plans. Nevertheless, gaps in achieving optimal macronutrient and fatty acid distributions emphasise the need for algorithmic refinement. While these tools have the potential to revolutionise personalised nutrition by offering precise and inclusive dietary solutions, they should enhance rather than replace the expertise of dietetic professionals.

การพัฒนาแชทบอทเพื่อส่งเสริมการท่องเที่ยวชุมชนช่างศิลป์จังหวัดนครปฐม

The objectives of this research are to 1) develop an information system to promote tourism through the Chatbot application system in tourist attractions of the artisan community in Nakhon Pathom Province 2) study tourists' satisfaction with the Chatbot with Python language to promote tourism through the application system. LINE Chatbot in Nakhon Pathom Province The data was collected from a sample of 423 tourists and members of online social groups, which is a specific sample group. Statistics used in data analysis include frequency, percentage, mean, and standard deviation. The research results found that the study of tourist behavior in using chatbots in 4 areas: meeting needs, being able to work. according to function, ease of use, and efficiency It was found that tourists' satisfaction in using chatbots was at a high level, with an average of 4.20. The aspect that tourists are most satisfied with is the ease of use. has an average of 4.23 in terms of meeting the needs and system performance They have an average of 4.20 and the ability to work according to their duties. has an average of 4.18, respectively.

PLACEBO MARKETING TOWARDS CONSUMER EXPECTATION AND PRODUCT INTEGRITY AMONG HEALTH SUPPLEMENTS USERS IN CAVITE

The study aimed to determine the placebo marketing towards consumer expectation and product integrity among health supplement users in Cavite. This also determines the participants' perception of placebo effect marketing in their consumer expectation about the performance and reliability of the product, ease of use, value for money, and emotional connection towards its consumers. The participant's perception of placebo effect marketing on product integrity in terms of transparency and expectation versus reality. It employed a descriptive-correlational research design using a survey questionnaire administered through Google Forms, considering 120 health supplement users in Cavite. For this study, the researcher also used statistical methods including frequency distribution, mean, percentage, and standard deviation. A Likert scale that used to assess participants' perceptions of marketing strategies and their influence on health supplement use and expectations. Results show that the participants towards the placebo marketing strategies have effectively created a positive initial impression among health supplement users in Cavite. These strategies, such as professional endorsements, scientific language, and attractive packaging, make products seem reliable and valuable. This means that while marketing can create strong first impressions, it is difficult to keep these impressions once the product is used. Results also show a gap between what the marketing promises and what the products actually deliver and to keep consumers' trust and uphold the brand's integrity, companies need to ensure that their marketing claims match the actual benefits of their products. For the sake of brand integrity, businesses should prioritize transparency in product labeling by providing clear and accurate information about ingredients, testing procedures, and certifications. For consumers, it is recommended to remain critical and informed when evaluating health supplement claims. The study emphasizes the need for ethical marketing practices to foster trust and loyalty in the health supplement industry.

The Euro Area has a growth problem

The decomposition of GDP into potential output—the level of output consistent with current technologies and "normal" use of capital and labor—and the output gap—the percentage deviation of GDP from its potential—is a fundamental task for policymakers. Potential output tells us how fast an economy can grow in the long run; the output gap helps assess the cyclical position of the economy and, thus, potential inflationary pressures (Jarociński and Lenza, 2018).

Motion Artifact Removal in Functional Near‐Infrared Spectroscopy Based on Long Short‐Term Memory‐Autoencoder Model

ABSTRACTMotion artifact removal is a critical issue in functional near‐infrared spectroscopy (fNIRS) analysis tasks, with traditional methods relying heavily on expert‐based knowledge and optimal selection of model parameters within brain regions. In this paper, we propose a deep learning denoising model based on long short‐term memory (LSTM)‐autoencoder (viz., LSTM‐AE) to reduce motion artifacts. By training a neural network to reconstruct hemodynamic response coupled with neuronal activity, LSTM‐AE achieves positive denoising results on both our synthesized noisy simulated dataset and the real dataset. The LSTM‐AE processes the raw fNIRS in three phases: (1) Morphological feature extraction of the raw fNIRS is conducted through the encoder module. (2) The LSTM module captures temporal correlations between individual samples to enhance features. (3) The decoder module recovers and reconstructs the morphological feature information of fNIRS from the latent space. Finally, clean reconstructed fNIRS is generated at the output layer. We compare our proposed method with existing calibration algorithms for hemodynamic response estimation using the following metrics: mean square error (MSE), Pearson's correlation (R2), signal‐to‐noise ratio (SNR), and percent deviation ratio (PDR). The proposed LSTM‐AE method outperforms conventional methods, demonstrating an improvement in all these metrics. Additionally, the proposed LSTM‐AE method shows statistically significant differences from other motion artifact algorithms in terms of effectiveness (p &lt; 0.01, significance level α = 0.05). This study demonstrates the potential of deep network architectures to remove motion artifacts in fNIRS data.

Utilising artificial neural networks for optimising supercritical CO2 extraction of Pongamia pinnata (L.) seed oil

ABSTRACT The application of various mathematical models in supercritical CO2 extraction processes is constrained by the high sensitivity to slight variations in process variables. Consequently, supercritical fluid extraction (SFE) processes have become an appealing field for employing artificial neural networks (ANNs). Feed forward back propagation (FFBP) and Cascade forward back propagation (CFBP) networks have been used for optimising SC-CO2 extraction of Pongamia pinnata (L.) (PP) seed oil. Both networks included TRAINLM and LEARNGDM as training function and learning function respectively, PURELIN and TANSIG as transfer functions for output and hidden layer respectively. A single layer with six hidden neurons was used for predicting cumulative extraction yield (CEY) of PP seed oil. The influence of five extraction variables – namely pressure, temperature, particle size, flow rate – CO2 and co-solvent percentage was examined with regard to CEY of PP seed oil. The values of performance parameters e.g. mean square error = 0.00013, average-absolute-relative deviation percentage = 3.18649, and correlation coefficient = 0.99195 for CFBPN model and 0.00017, 4.39994, and 0.98741 respectively for FFBPN model indicating that CFBPN model is superior over FFBPN model. Gas chromatography confirmed essential fatty acids in the oil extracted from PP seeds.