Miracle-dz/UniFAR-FTUs huggingface dataset:
EAES: Effective Augmented Embedding Spaces for Text-based Image Captioning

Text-based Image Captioning has been a novel problem since 2020. This topic remains challenging because it requires the model to comprehend not only the visual context but also the scene texts that appear in an image. Therefore, the ways image and scene texts are embedded into the main model for training is crucial. Based on the M4C-Captioner model, this paper proposes the simple but effective EAES embedding module for effectively embedding images and scene texts into the multimodal Transformer layers. In detail, our EAES module contains two significant sub-modules: Objects-augmented and Grid feature augmentation. With the Objects-augmented module, we provide the relative geometry feature, representing the relation between objects and between OCR tokens. Furthermore, we extract the grid feature for an image with the Grid feature augmentation module and combine it with visual objects, which help the model focus on both salient objects and the general context of an image, leading to better performance. We use the TextCaps dataset as the benchmark to prove the effectiveness of our approach on five standard metrics: BLEU4, METEOR, ROUGE-L, SPICE and CIDEr. Without bells and whistles, our method achieves 20.21% on the BLEU4 metric and 85.78% on the CIDEr metric, 1.31% and 4.78% higher, respectively, than the baseline M4C-Captioner method. Furthermore, the results are incredibly competitive with other methods on METEOR, ROUGE-L and SPICE metrics.
Predictors of Early Neurological Deterioration Following Intravenous Thrombolysis: Difference between Risk Factors for Ischemic and Hemorrhagic Worsening

Background: Prevention of early neurological deterioration (END) is becoming an important therapeutic target in acute ischemic stroke management. The aim of the study is to ascertain the causes and predictors of early neurological deterioration following thrombolysis and determine the predictive value of IScore. Methods: In this single center prospective study, we analyzed clinical, imaging and outcome data in 168 patients thrombolyzed intravenously ≤4.5 hours from onset of stroke. Early neurological deterioration was defined as worsening ≥2 points in the NIHSS score at 24 hours. Results: END occurred in 34 patients (20%) and caused significantly worse short term outcome. Ischemic END (ENDi) (n = 23) was twice as common as symptomatic hemorrhage (ENDh) (n = 11). Ischemia progression (n = 15) was the most common cause. Early malignant edema was another major cause. On multivariate analysis, significant predictors (p <.05) were proximal artery occlusion [all END (p <.001), ENDi and ENDh], previous ischemic insults (all END) and raised diastolic blood pressure (ENDh). ENDi was more common in those with carotid artery occlusion, large vessel disease and previous ischemic insults. ENDh was more common in those with raised diastolic blood pressure and NIHSS-ASPECTS mismatch. For patients with NIHSS <14, IScore >105 and for NIHSS ≥14, IScore >175 was associated with higher risk of END. Conclusion: END occurs in one fifth of patients after intravenous thrombolysis; ENDi outnumbers ENDh. Proximal artery occlusion is a major predictor for END. Potentially modifiable risk factors include admission hyperglycemia and elevated blood pressures. Distinct factors characterize ENDh and ENDi and can guide prevention and management strategies. IScore identifies patients at risk for END.
A Dynamic Model for Estimating the Interaction of ROS–PUFA–Antioxidants in Rabbit

Defining optimal nutrition in animals and humans remains a main scientific challenge. The objective of the work was to develop a dynamic model of reactive oxygen species (ROS)–polyunsaturated fatty acid (PUFA)–antioxidant homeostasis using the rabbit as a model. The problem entity was to evaluate the main metabolites generated from interactions between traits included in the conceptual model and identified by three main sub–models: (i) ROS generation, (ii) PUFA oxidation and (iii) antioxidant defence. A mathematical model (VENSIM software) that consisted of molecular stocks (INPUTs, OUTPUTs), exchange flows (intermediate OUTPUTs) and process rates was developed. The calibration was performed by using standard experimental data (Experiment 1), whereas the validation was carried out in Experiments 2 and 3 by using supra–nutritional dietary inputs (VIT E+ and PUFA+). The accuracy of the models was measured using 95% confidence intervals. Analytical OUTPUTs (ROS, PUFA, Vit E, Ascorbic acid, Iso–/NeuroProstanes, Aldehydes) were well described by the standard model. There was also good accuracy for the VIT E+ scenario, whereas some compensatory rates (Kc1–Kc4) were added to assess body compensation when high levels of dietary PUFA were administered (Experiment 3). In conclusion, the model can be very useful for predicting the effects of dietary treatments on the redox homeostasis of rabbits.
Geomagnetically Induced Current-Monitoring Method Based on High Voltage Wires for Transformers

Hall sensors have a relatively low withstand voltage but have been used at the neutral point of transformers to monitor geomagnetically induced currents (GICs). However, when introduced into monitoring devices via sensor wiring, high voltages at the transformer neutral point can lead to damage to electronic components and increase the risk of serious power grid accidents. For monitoring GICs from the neutral point of the transformer, this paper proposes a transformer GIC monitoring method based on high-voltage wire equipotentials and a transformer GIC power (GIC-Q) algorithm based on the proportional coefficient K value method. A transformer monitoring device based on the proposed methods was tested at a 500 kV substation in China. In addition, we verified the accuracy of the proposed method and validity of the monitoring data produced using geomagnetic disturbance data with a Kp-index of 4 from the Man Zhouli Geomagnetic Observatory Station.
Cloud-Based Decision Support System for Air Quality Management

Air quality is important for the protection of human health, the environment and our cultural heritage and it is an issue that will acquire increased significance in the future due to the adverse effects of climate change. Thus, it is important to not simply monitor air quality, but to make information immediately available to those responsible for monitoring the networks, to policy/decision makers, but also to the general population. Moreover, the development of information technologies over the last couple of decades has allowed the proliferation of real-time pollution monitoring. The work presented herein concerns the development of an effective way of monitoring environmental parameters using dedicated software. It offers a complete suite of applications that support environmental data collection management and reporting for air quality and associated meteorology. It combines modern technologies for the proper monitoring of air quality networks, which can consist of one or more measuring stations. Innovatively, it also focuses on how to effectively present the relevant information, utilizing modern technologies, such as cloud and mobile applications, to network engineers, policy/decision managers, and to the general public at large. It also has the capability of notifying appropriate personnel in the event of failures, overruns or abnormal values. The system, in its current configuration, handles information from six networks that include over 55 air pollution monitoring stations that are located throughout Greece. This practical application has shown that the system can achieve high data availability rates, even higher than 99% during the year.
Reviewing and Exploring the Qualitative Impacts That Different Market and Regulatory Measures Can Have on Encouraging Energy Communities Based on Their Organizational Structure

The emergence of energy communities represents a promising option to democratize the energy system by empowering consumers to take a more active role. This can aid in achieving energy and environmental goals as well as encouraging more equitable distribution of costs and revenues between all parties on the energy system. Despite this potential, energy communities are still a nascent solution, the success of which is heavily influenced by regulations. As a result, there are a wide variety of organizational structures for energy communities at this time. This paper provides a review of the policy landscape in Spain as it relates to energy communities. This work also presents a formalized method for characterizing different energy community structures and provides a qualitative assessment of the impacts of different measures to encourage energy communities with respect to their organizational structure. Findings suggest that many market-focused measures, including wholesale, local flexibility, capacity, and multisector market measures favor larger, more integrated communities, while regulatory, legal, and organizational measures, including peer-to-peer trading, aggregation, and self-consumption favor smaller, more distributed communities. Additionally, when developing policies to encourage the growth of energy communities, policymakers should be cognizant of the progression of policies in the context of the desired outcomes for energy community growth specific to the region or country and its goals.
Prevalence of Multidrug Resistant Gram-negative Bacteria in Tissues of Diseased Chicken in Chitwan District, Nepal

For increasing productivity in poultry, antibiotics are overused. This increased use in antibiotics has raise the prevalence of Multidrug resistant (MDR) bacteria in poultry. Treatment of chicken infected with MDR bacteria is difficult to achieve, thereby increasing treatment cost and productivity cost. MDR bacteria of poultry can also infect humans if they are not handled properly. Thus, the purpose of this study was to find bacteria responsible for infecting chicken and prevalence of MDR bacteria in diseased chicken. Out of total 516 diseased chicken, 212(41.09%) chicken were infected by bacteria. The prevalence of E. coli (63.2%) was high in diseased chicken followed by Salmonella spp. (12.26%), Pseudomonas spp. (5.2%) and, Pasteurella spp. (4.7%). Out of total number of isolates, the prevalence of MDR was 42.5 %. This study also showed that Pasteurella spp. isolates had high MDR with prevalence of 50%. It is thus concluded that there was high prevalence of MDR bacteria among diseased chicken in Chitwan district.
RTL Conversion Method From Pipelined Synchronous RTL Models Into Asynchronous Ones

In this paper, we propose a conversion method from pipelined synchronous Register Transfer Level (RTL) models into pipelined asynchronous RTL models with bundled-data implementation. To know data-path resources controlled by each pipeline stage, the proposed method generates a control data flow graph (CDFG) from synchronous RTL models. After generating the CDFG, the proposed method generates asynchronous RTL models by analyzing each pipeline stage on the CDFG, assigning asynchronous control modules, and connecting the control modules to the data-path resources. In addition, we also propose optimization methods during the conversion. In the experiment, we converted four pipelined synchronous RTL models into pipelined asynchronous ones. In addition, we performed logic synthesis for the converted asynchronous RTL models to check the quality of the asynchronous RTL models. The synthesized asynchronous circuits without the optimization methods could reduce the energy consumption by 1.47% on average compared to synchronous circuits. Moreover, the optimization methods could reduce the energy consumption by 15.12% on average compared to synchronous circuits. Furthermore, the optimization methods reduced the energy consumption by up to 34.72% compared to asynchronous circuits without the optimization methods.
Emotional Culture as a Context of Education: Why Emotional Culture is Important for Pedagogy?

In the article, I search for the connection between emotions culture and education by examining the affective reproduction of culture. Building on the tradition of Émile Durkheim, in the works by Arlie Russell Hochschild and Steven Gordon the concept of emotional culture is (re)constructed. Emotional culture is understood as the specific complex of emotion vocabularies, feeling rules, and beliefs about emotions. Emotions and their meaning provide a socio-psychological mechanism that controls/develops individuals and groups. In the text, it is argued that the concept of emotional culture adds a distinctive conceptual tool for studying different educational contexts and environments. To examine this argument, the article is divided into three parts. First, an overview of the concepts and theories that underlie the term of emotional culture is given. In the second part, the concept is analyzed in the light of modern cultural studies. The article closes by pointing out pedagogical implications, especially those connected with emotional education.
Sociodemographic and clinical characteristics of a sample of patients with major depressive disorder

Introduction: The World Health Organization (WHO) recently reported that depression is a major cause of disability worldwide, with more than 320 million people affected globally (World Health Organization, 2017). Aim of the work: is to describe sociodemographic characteristics in a sample of patients diagnosed with major depressive disorder. Patients and methods: 51 Patients were referred from the outpatient psychiatric clinics of Minia governorate, Minia University hospitals outpatient psychiatric clinic, Minia psychiatric hospital and the study was held in Minia university hospitals during the period from December 1, 2018 to October 1, 2019. Results: the mean age of the sample was 35.44 ± 10.402 years, ranging from 18 to 55 years. Nearly half of the participants were females (55.6%). More than a half of them (57.8%) were married, while (31.3%) were single. Rural residents (53.3%) were more common than urban (46.7 %). The most common educational level was high-education (31.1%) followed by technical education (26.7%). Full time employees were (53.3%) followed by unemployed and not looking for work (31.1%). The majority of patients (73.3%) reported significant environmental stressor or precipitant prior to the onset of depression. Conclusion: depression is more common in third decade of life, more common in females more than males and highly-related to significant life stressors.
Effects of perceived value on satisfaction and revisit intention: Domestic vs. international tourists

Despite the availability of a considerable body of research examining large-scale hotels, small-scale accommodations like traditional guesthouses have been overlooked. Using the hierarchy of effects model, this paper seeks to investigate and compare the effects of perceived value dimensions (e.g. functional value, emotional value, and social value) on the satisfaction and revisit intentions of domestic and international tourists. Drawing upon quantitative data collected from guests of selected traditional guesthouses in the heritage city of Kashan, Iran, this study employed partial least squares, structural equation modelling, and multi-group analysis to test several research hypotheses. The findings of the study revealed significant differences in the effects of emotional and social values on satisfaction and the direct and indirect effects of social value on domestic and international tourists’ revisit intentions through satisfaction. The results, therefore, emphasised the importance of functional and emotional values for international tourists, with the social value being more important for enhancing the satisfaction and revisit intentions of domestic tourists. Significant theoretical contributions and practical implications are provided in the conclusion section of the study.
Micronutrient Improvement of Epithelial Barrier Function in Various Disease States: A Case for Adjuvant Therapy

The published literature makes a very strong case that a wide range of disease morbidity associates with and may in part be due to epithelial barrier leak. An equally large body of published literature substantiates that a diverse group of micronutrients can reduce barrier leak across a wide array of epithelial tissue types, stemming from both cell culture as well as animal and human tissue models. Conversely, micronutrient deficiencies can exacerbate both barrier leak and morbidity. Focusing on zinc, Vitamin A and Vitamin D, this review shows that at concentrations above RDA levels but well below toxicity limits, these micronutrients can induce cell- and tissue-specific molecular-level changes in tight junctional complexes (and by other mechanisms) that reduce barrier leak. An opportunity now exists in critical care—but also medical prophylactic and therapeutic care in general—to consider implementation of select micronutrients at elevated dosages as adjuvant therapeutics in a variety of disease management. This consideration is particularly pointed amidst the COVID-19 pandemic.
Assessment Methods for Comparing Shared Mobility and Conventional Transportation Modes in Urban Areas

Shared mobility is an innovative and sustainable approach to passenger transportation, which has only recently emerged. In urban areas car-sharing, bike-sharing and other special vehicles (e.g., scooters) are popular. For greater distances, ridesharing is considered as a great option beside own private car usage or public transportation. We elaborated an assessment to analyse mobility modes. The research consists of two main parts. First, a wide spectrum of key variables is identified. We classified the variables among the following indicators: flexibility, comfort, and dynamic characteristics. These indicators support mode choice decisions. The second part is the model of service level. In the model, we included parameters to represent the importance of certain attributes. The model can be used to support mode choice decisions. We applied the method to analyse a simple urban mobility palette and place shared mobility within it. We found that shared mobility modes can be placed between private car usage and public transportation according to the aggregated indicators.
The value of Artificial Intelligence on the detection of pathologies in chest radiographs compared with High Resolution Multi slice Computed Tomography

Background: Over the last few years, there has been increasing interest in the use of deep learning algorithms to assist with abnormality detection on medical images. Aim of this study was to investigate the performance of Artificial Intelligence on the detection of pathologies in chest radiographs compared with high resolution multi slice Computed Tomography. Methods : this prospective study was done on 200 cases, who underwent automatic detection of chest disease based on chest radiography in a comprehensive survey on computer-aided detection systems, focuses on the artificial intelligence technology applied in chest radiography to detect the presence of different pathologies, including pleural effusion, pneumothorax, pneumonia, pulmonary masses, and nodules in AP and PA -view chest radiographs using modern digital radiography. Using high resolution multi slice Computed Tomography (16/64/128 detector) for chest examination for abnormality detected by artificial intelligence technology. Axial scanning extending from base of the neck down below the diaphragm with coronal & sagittal reformate images . Results: The mean age of patients was 46.3 years. 123 patients (61.5 %) were males and 77 patients (38.5 %) were female. There was a statistically significant difference between CAD and MDCT diagnosed by radiologist according to sensitivity, p<0.001. Conclusion: In spite CAD system has established fair accuracy, the need of more accurate algorithm is necessary to determine if it can replicate MDCT and radiologist observation of abnormality on chest X-rays
Gaussian Processes for Advanced Motion Control*

Machine learning techniques, including Gaussian processes (GPs), are expected to play a significant role in meeting speed, accuracy, and functionality requirements in future data-intensive mechatronic systems. This paper aims to reveal the potential of GPs for motion control applications. Successful applications of GPs for feedforward and learning control, including the identification and learning for noncausal feedforward, position-dependent snap feedforward, nonlinear feedforward, and GP-based spatial repetitive control, are outlined. Experimental results on various systems, including a desktop printer, wirebonder, and substrate carrier, confirmed that data-based learning using GPs can significantly improve the accuracy of mechatronic systems.
Life history mapping: Exploring journeys into and through housing and homelessness

This article illustrates the value of in-depth life history interviews using life mapping in qualitative research. We draw on our recent research into people’s experiences of homelessness, where all 39 participants were currently, or recently, homeless. Using the life mapping method, participants generated a visual representation of their transitions across housing and homelessness, beginning in childhood and ending in the present day. We critically discuss the potential for life mapping to move beyond rehearsed stories, briefly note further associated benefits, and acknowledge some potential drawbacks. We argue that the method can confer considerable depth and reflection, going beyond a traditional qualitative interview, and is especially valuable when examining sensitive topics.
Technical Feasibility of Supervision of Stretching Exercises by a Humanoid Robot Coach for Chronic Low Back Pain: The R-COOL Randomized Trial

Adherence to exercise programs for chronic low back pain (CLBP) is a major issue. The R-COOL feasibility study evaluated humanoid robot supervision of exercise for CLBP. Aims are as follows: (1) compare stretching sessions between the robot and a physiotherapist (control), (2) compare clinical outcomes between groups, and (3) evaluate participant perceptions of usability and satisfaction and therapist acceptability of the robot system. Prospective, randomized, controlled, single-blind, 2-centre study comparing a 3-week (3 hours/day, 5 days/week) physical activity program. Stretching sessions (30 minutes/day) were supervised by a physiotherapist (control) or the robot. Primary outcome: daily physical activity time (adherence). Secondary outcomes: lumbar pain, disability and fear and beliefs, participant perception of usability (system usability scale) and satisfaction, and physiotherapist acceptability (technology acceptance model). Clinical outcomes were compared between groups with a Student t-test and perceptions with a Wilcoxon test. Data from 27 participants were analysed (n = 15 control and n = 12 robot group). Daily physical activity time did not differ between groups, but adherence declined (number of movements performed with the robot decreased from 82% in the first week to 72% in the second and 47% in the third). None of the clinical outcomes differed between groups. The median system usability scale score was lower in the robot group: 58 (IQR 11.8) points vs. 87 (IQR 9.4) in the control group at 3 weeks (p < 0.001). Median physiotherapist rating of the technology acceptance model was <3 points, suggesting a negative opinion of the robot. In conclusion, adherence to robot exercise reduced over time; however, lumbar pain, disability, or fear and beliefs did not differ between groups. The results of the participant questionnaires showed that they were willing to use such a system, although several technical issues suggested the KERAAL system could be improved to provide fully autonomous supervision of physical activity sessions.