Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrochemical behavior and differential pulse voltammetric determination of budesonide in suspension ampoules

Background and Aims: Budesonide (BUD) is a broad-spectrum anti-inflammatory and anti-allergic glucocorticosteroid agent. It is used in the treatment of chronic obstructive pulmonary disease (COPD), Crohn's disease, and ulcerative colitis. The aim of the study was to investigate the electrochemical properties of BUD for the first time and to develop a sensitive, easy, and selective new differential pulse voltammetry (DPV) method for its determination in drug formulation. Methods: The electrochemical behavior of BUD was investigated using cyclic voltammetry (CV) and differential pulse voltammetry (DPV) with a carbon paste electrode (CPE) in various electrolyte and buffer solutions with pH ranging from 2 to 9. An irreversible, well-defined reduction current peak of about -859 mV was obtained. A DPV method was developed and validated for the determination of BUD in suspension ampoules using a CPE electrode in a 0.1 M HCl electrolyte solution containing 13% KCl and 8% methanol. Results: The cathodic peak was found to be adsorption-controlled. The calibration curve was linear between 1.65-35.35 µg/ml. The limit of detection (LOD) and limit of quantification (LOQ) values were found to be 0.52 µg/mL and 1.57 µg/mL, respectively. The developed method offered an effective capability for the determination of BUD in suspension ampoules, with a recovery rate of 98.47%. Conclusion: The DPV method developed in this study could be used for routine quantitative analysis of BUD in pharmaceutical preparations due to its fast, accurate, inexpensive, and environmentally friendly nature.
Is There A Relationship between Motivational Beliefs and Learning Independently?

Motivation and self-regulated learning are two critical aspects of academic success that have received significant attention in the educational psychology literature. Research has shown that students who are motivated and possess self-regulated learning skills tend to achieve better academic outcomes than those who lack these qualities. Online learning was used in educational institutions during the Covid 19 pandemic and this forced learners to be more independent. This quantitative study examines the relationship between motivational beliefs and learning independently among foundation students post Covid-19. A purposive sample of 170 undergraduates responded to the survey which used a 5 Likert-scale survey divided into 4 sections and rooted from Pintrich & De Groot (1990). Data analysis using SPSS found that students have moderately high motivational beliefs and self-regulation abilities. There is also a strong positive relationship between motivational beliefs and independent learning among these participants. This suggests that the learning environment needs to be adjusted to enhance motivation and independence among students.
Global cities and cultural diversity: challenges and opportunities for young people's nutrition

Childhood obesity is a common concern across global cities and threatens sustainable urban development. Initiatives to improve nutrition and encourage physical exercise are promising but are yet to exert significant influence on prevention. Childhood obesity in London is associated with distinct ethnic and socio-economic patterns. Ethnic inequalities in health-related behaviour endure, underpinned by inequalities in employment, housing, access to welfare services, and discrimination. Addressing these growing concerns requires a clearer understanding of the socio-cultural, environmental and economic contexts of urban living that promote obesity. We explore opportunities for prevention using asset based-approaches to nutritional health and well-being, with a particular focus on adolescents from diverse ethnic backgrounds living in London. We focus on the important role that community engagement and multi-sectoral partnership play in improving the nutritional outcomes of London's children. London's children and adolescents grow up in the rich cultural mix of a global city where local streets are characterised by diversity in ethnicities, languages, religions, foods, and customs, creating complex and fluid identities. Growing up with such everyday diversity we argue can enhance the quality of life for London's children and strengthen their social capital. The Determinants of young Adult Social well-being and Health longitudinal study of about 6500 of London's young people demonstrated the positive impact of cultural diversity. Born to parents from over a hundred countries and exposed to multi-lingual households and religious practices, they demonstrated strong psychological resilience and sense of pride from cultural straddling, despite material disadvantage and discrimination. Supporting the potential contribution of such socio-cultural assets is in keeping with the values of social justice and equitable and sustainable development. Our work signals the importance of community engagement and multisectoral partnerships, involving, for example, schools and faith-based organisations, to improve the nutrition of London's children.
On the Facilitation of Voltage Over-Scaling and Minimization of Timing Errors in Floating-Point Multipliers

Voltage over-scaling (VoS) may be one of the most effective power reduction approaches, however, it makes circuits susceptible to timing failures. Various techniques were proposed to facilitate VoS by detecting and correcting errors and moving away from traditional voltage and timing guardbands. However, such approaches require the addition of extra redundant hardware leading to area and power overheads, especially in case of large timing errors. Recent, complementary approaches tried to redesign the target circuits, however, they were not yet applied on complex pipelined architectures like floating point multiplier which is extensively used in neural networks and other popular applications. In this paper, we develop a low-power pipelined floating-point IEEE-754 compatible multiplier that can operate reliably under voltage over-scaling (VoS). This is achieved by applying a path-shaping approach that helps minimize the number of paths susceptible to timing errors under lower voltages. In addition, our micro-architectural modifications isolate the critical paths only to a single pipeline stage, thus minimizing the error-prone stages under VoS. To showcase the efficacy of our approach, we perform post-place dynamic timing analysis using various benchmarks, indicating that our design can lead up to 171% better SNR, 80% less BER and 36% less power under 18% less voltage compared to the baseline multiplier. The applied analysis reveals that our approach can help limit the erroneous outputs of the unit by up to 74% and reduce by 20% the multi-bit error probability, in such a widely used arithmetic unit.
Chemical and antibacterial properties of chitosan derived from Mucor spp., Rhizopus. Oryzae and Hermetia illucens

At present, commercial chitosan is mainly produced from crustacean shell. However, there are still other potential natural sources for production of chitosan, such as fungi and insects. In this study, chemical characteristic and antibacterial activity of chitosan derived from Mucor spp. , Rhizopus oryzae, and black soldier fly ( Hermetia illucens ) larvae were examined and compared with a commercial chitosan from shrimp. Chitosan recovery obtained from Mucor spp. , R. oryzae , and H. illucens was 157.3 mg/g biomass, 133.1 mg/g biomass, 4.28 mg/g biomass, respectively. The deacetylation degree (DD) of chitosan from Mucor spp. , R. oryzae , and H. illucens was 80.09%, 80.92%, and 84.18%, respectively. The values resemble the DD of chitosan from commercial shrimp, 79.14%. The results of this study showed that chemical properties in chitosan influence its antibacterial activity. The chitosan from Mucor spp. , R. oryzae , and H. illucens inhibits the growth of Staphylococcus aureus with an inhibition diameter of 16.8 ± 0.4 mm, 20.9 ± 0.1 mm, and 28.5 ± 2.8 mm. In addition, the chitosan from Mucor spp. , R. oryzae, and H. illucens also inhibits the growth of Escherichia coli with an inhibition diameter of 12.8 ± 0.5 mm, 14.9 ± 0.5 mm, and 25.2 ± 1.9 mm, respectively. The findings of this study clearly show that Mucor spp. , R. oryzae , and H. illucens have great potential as alternative sources of bioactive material applied in the field of food and medicine.
Neuroevolution untuk optimalisasi parameter jaringan saraf tiruan

Artificial Neural Network is a supervised learning method for various classification problems. Artificial Neural Network uses training data to identify patterns in the data; therefore, training phase is crucial. During this stage, the network weight is adjusted so that they can recognize patterns in the data. In this research, a neuroevolution approach is proposed to optimize artificial neural network parameters (weight) Neuroevolution is a combination of evolutionary algorithms, including various metaheuristics algorithms, to optimize neural network parameters and configuration. In particular, this research implemented particle swarm optimization as the artificial neural network optimizer. The performance of the proposed model was compared to backpropagation, which uses gradient information to adjust the neural network parameter. There are five datasets used as the benchmark problems. The datasets are iris, wine, breast cancer, ecoli, and wheat seeds. The experiment results show that the proposed method has better accuracy than the backpropagation in three out of five problems and has the same accuracy in two problems. The proposed method is also faster than the backpropagation method in all problems. These results reveal that neuroevolution is a promising approach to improving the performance of artificial neural networks. Further studies are needed to explore more benefits of this approach.
The Impact of Regular Exercise on Life Satisfaction, Self-Esteem, and Self-Efficacy in Older Adults

This study employed the correlational survey model to examine how regular exercise influenced life satisfaction, self-esteem, and self-efficacy in men over 65. The study sample included a total of 215 participants, of whom 110 exercised regularly (for at least 45 min, three times a week), while 105 engaged in no physical exercise. Regular exercisers were found to score significantly higher on life satisfaction, self-esteem, and self-efficacy scales as compared to non-exercisers. These scores also increased significantly with age and prolonged exercise history. A moderate and positive correlation was detected between life satisfaction, self-esteem, and self-efficacy among regular exercisers, while non-exercisers showed low to moderate correlations. The findings suggest that regular exercise can enhance life satisfaction, self-esteem, and self-efficacy in the elderly male population. Such effects appear to be associated with greater age and lifetime exercise history, highlighting the value of regular physical exercise in improving the quality of life among older adults.
ANALYSIS OF THE EFFECT OF PAYROLL SYSTEM AND PATIENT SAFETY CULTURE ON NURSE PERFORMANCE WITH JOB SATISFACTION AS THE INTERVENING VARIABLE IN INPATIENT ROOM PREMIER BINTARO HOSPITAL TANGERANG SELATAN

This study is based on fluctuations in the risk of patients falling in the 2020 – 2021 period and the dynamics of performance problems in 2021 reflect problems regarding the performance of nurses in inpatient rooms in serving patients. The purpose of this study was to obtain evidence of the influence of the salary system and patient safety culture on the performance of nurses in inpatient rooms, with job satisfaction as an intervening variable. The research design used a cross sectional study, and made 135 nurses as the unit of analysis. The results of the study prove that the salary system and patient safety culture have a positive and significant direct effect on job satisfaction and performance, job satisfaction has a positive and significant direct effect on performance, and job satisfaction has a positive role in mediating the payroll system and patient safety culture on performance. By creating a sense of satisfaction for nurses with all aspects related to their work, they will be better able to present quality work results and achieve according to the standards set by the organization.
Mechanical and biological performance of biphasic calcium phosphate typed bone substitute for high tibia osteotomy

An ideal scaffold for high tibia osteotomy (HTO) surgery should possess a suitable degradation rate, acceptable mechanical strength, and biocompatibility. Biphasic calcium phosphate (BCP) is one of the choices that have been used to address these issues. Previously, BCP could adjust the ratio between hydroxyapatite (HA) and beta-tricalcium phosphate (β-TCP) to tailor the degradation and mechanical strength properties for each application. This paper aims to discover a new method for fabricating BCP scaffolds that can precisely control the purity of HA and β-TCP and adjust the HA/ β-TCP ratio to find the best condition suitable for HTO patients.
MOSCAMED-Guatemala - an evolution of ideas.

The Moscamed Programme in Guatemala began in 1975 with Medfly pupae imported from Vienna and reared in a vacant aircraft hanger in Guatemala City. From these humble beginnings some 26 years ago, the programme has evolved into the largest Medfly control and eradication effort in the Americas, if not the world. While its present status is of some importance, what needs to be emphasized is the evolution of technologies, ideas, and methodologies that played a major role in the changes that have taken place. Over many years, science and technology has provided the pathways to improve the methods used in insect detection, control, and insect mass-rearing. But it is the operational programme that has facilitated the widespread use and further development of those technologies. Subjecting the technologies to routine usage in field programmes promotes further refinement and a concerted effort to seek other technologies,ideas,and concepts that can be adopted and adapted to the task at hand. The Guatemala Medfly Programme has been a catalyst in the effort to develop and refine fruit fly control and eradication tools.
Hypoxia and the regulation of myeloid cell metabolic imprinting: consequences for the inflammatory response

Inflamed and infected tissue sites are characterised by oxygen and nutrient deprivation. The cellular adaptations to insufficient oxygenation, hypoxia, are mainly regulated by a family of transcription factors known as hypoxia‐inducible factors (HIFs). The protein members of the HIF signalling pathway are critical regulators of both the innate and adaptive immune responses, and there is an increasing body of evidence to suggest that the elicited changes occur through cellular metabolic reprogramming. Here, we review the literature on innate immunometabolism to date and discuss the role of hypoxia in innate cell metabolic reprogramming, and how this determines immune responses.
Variety of Antibody Responses to BNT162b2 and BBIBP-CorV Vaccinations Against COVID-19 Infections in Baghdad and Fallujah, Iraq

The huge impact of COVID-19 worldwide led to the rapid development of vaccines with inadequate data about its longevity, effectivity, and safety. This study aims to evaluate the effectiveness and safety of COVID-19 vaccines available in Iraq and to measure longevity of created antibody response among different time points of both Pfizer-BioNTech and Sinopharm vaccines in Baghdad and Fallujah, Iraq. A two-axis method was used: the first was cross sectional study on the vaccination state for COVID-19 in Baghdad and Fallujah, using an online survey contained questions about city, vaccine type, side effect, pre and post infections, and chronic diseases. The second part involved a prospective observational study of the vaccine’s immunological effectiveness and stability in 60 serum samples from completely vaccinated individuals (second dose) of Pfizer or Sinopharm along different time points (1 - 6 months) by measuring the SARS-CoV-2 Anti-RBD-IgG concentration and evaluating its correlation with pre-infection with COVID-19. Among different types of vaccines available in Iraq, people in Baghdad and Fallujah preferred Pfizer vaccine over other available types, particularly those with chronic diseases. No statistically significant difference was noticed between IgG concentrations at different points of time, IgG concentrations in Pfizer vaccinated individuals were more elevated than Sinopharm, and all of Pfizer vaccinated people showed positive results. Our study established a synergistic impact between recent COVID-19 infection and vaccination, leading to increased levels of IgG antibodies, notably in individuals who received the Pfizer vaccine. Additionally, our findings demonstrate that IgG concentrations remained stable in vaccinated individuals even six months after completing the vaccination with second dose.
A Comparative Study on Deep Learning Models for COVID-19 Forecast

The COVID-19 pandemic has led to a global health crisis with significant morbidity, mortality, and socioeconomic disruptions. Understanding and predicting the dynamics of COVID-19 are crucial for public health interventions, resource allocation, and policy decisions. By developing accurate models, informed public health strategies can be devised, resource allocation can be optimized, and virus transmission can be reduced. Various mathematical and computational models have been developed to estimate transmission dynamics and forecast the pandemic’s trajectories. However, the evolving nature of COVID-19 demands innovative approaches to enhance prediction accuracy. The machine learning technique, particularly the deep neural networks (DNNs), offers promising solutions by leveraging diverse data sources to improve prevalence predictions. In this study, three typical DNNs, including the Long Short-Term Memory (LSTM) network, Physics-informed Neural Network (PINN), and Deep Operator Network (DeepONet), are employed to model and forecast COVID-19 spread. The training and testing data used in this work are the global COVID-19 cases in the year of 2021 from the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University. A seven-day moving average as well as the normalization techniques are employed to stabilize the training of deep learning models. We systematically investigate the effect of the number of training data on the predicted accuracy as well as the capability of long-term forecast in each model. Based on the relative L2 errors between the predictions from deep learning models and the reference solutions, the DeepONet, which is capable of learning hidden physics given the training data, outperforms the other two approaches in all test cases, making it a reliable tool for accurate forecasting the dynamics of COVID-19.
Multimodal Teaching of Japanese Newspaper Reading

Withthedeepeningofteachingreformandthedevelopmentofnetwork technology,singleteachingmodehasbeendifﬁculttoadapttotheneedsofmodern teaching.Asakindofteachingtheory,multimodalteachingbelievesthatstudents shouldbestimulatedtoparticipateinlanguagelearningthroughvariousways andteachingresources.Basedonthetheoryofmultimodalteaching,thispaper discussesthepracticalapplicationofmultimodalteachinginclassroomteaching, andreﬂectsontheeffectivenessoftheteachingmethod. Inordertomaximize theteachingeffect,itisnecessarytoavoidtheabuseofmodalresourcesinthe teachingprocess.
A Three-Phase Overlapping Winding–Based Wireless Charging System for Transportation Applications

This article proposes a two-layer overlapping winding–based three-phase wireless vehicle charging system with a coil span of 180°. This coil structure offers higher coupling and balance inductance matrices between the transmitter and receiver and improves system efficiency. The system performance improvement has been validated through detailed analysis and simulation results and compared with the benchmark for the same electrical parameters, air gap, and coil volume. Finite element analysis–based simulation results were presented for a 7.7-kW wireless power transfer (WPT) over a 200-mm air gap. An experimental prototype of the proposed system is developed operating at the resonant frequency of 86 kHz with a 200-mm air gap between the coils to validate the design. Both the simulation and experimental results showed a significant increase in efficiency and coupling compared to the conventional WPT systems.
Markerless motion capture system for stroke gait analysis

Stroke patients commonly suffered from motor impairments, and gait analysis is crucial for the effective guidance of poststroke rehabilitation. However, most existing 3D gait analysis systems require the attachment of optical markers to the body, and the systems are costly and spatially intensive. These restricted the use of the systems in general hospitals and communities. To address this issue, this study developed an affordable and markerless system to examine the gait characteristics of stroke patients, which was constructed by depth camera of Microsoft Azure Kinect, instrumented walkway, and analysis software. Spatiotemporal and kinematic parameters were measured directly, while kinetic parameters were derived via inverse dynamics using a 14-segment human body model. Sixteen healthy individuals and eight stroke patients were recruited for tests. The results showed that due to weakened lower limb strength in stroke patients, their peak joint moments, joint angles, and joint angular velocities decreased compared with healthy individuals. Consequently, stroke patients walked with reduced stride length, cadence, and single support time. Furthermore, the differences between the paretic and non-paretic sides of stroke patients were primarily observed at the knee joint (peak joint angle, angular velocity, and moment were significantly smaller compared to the non-paretic side) during swing phase. This suggests that rehabilitation training for stroke patients should place importance on knee joint. These findings demonstrate the significant potential of the present system in the gait analysis for stroke patients.
Understanding Patient Perspectives on Medication Adherence in Asthma: A Targeted Review of Qualitative Studies

Abstract Adherence to asthma medications is generally poor and undermines clinical outcomes. Poor adherence is characterized by underuse of inhaled corticosteroids (ICS), often accompanied by over-reliance on short-acting β2-agonists for symptom relief. To identify drivers of poor medication adherence, a targeted literature search was performed in MEDLINE and EMBASE for articles presenting qualitative data evaluating medication adherence in asthma patients (≥12 years old), published from January 1, 2012 to February 26, 2018. A thematic analysis of 21 relevant articles revealed several key themes driving poor medication adherence, including asthma-specific drivers and more general drivers common to chronic diseases. Due to the episodic nature of asthma, many patients felt that their daily life was not substantially impacted; consequently, many harbored doubts about the accuracy of their diagnosis or were in denial about the impact of the disease and, in turn, the need for long-term treatment. This was further compounded by poor patient-physician communication, which contributed to suboptimal knowledge about asthma medications, including lack of understanding of the distinction between maintenance and reliever inhalers, suboptimal inhaler technique, and concerns about ICS side effects. Other drivers of poor medication adherence included the high cost of asthma medication, general forgetfulness, and embarrassment over inhaler use in public. Overall, patients’ perceived lack of need for asthma medications and medication concerns, in part due to suboptimal knowledge and poor patient-physician communication, emerged as key drivers of poor medication adherence. Optimal asthma care and management should therefore target these barriers through effective patient- and physician-centered strategies.