Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship between Stress and Health-related Quality of Life is Mediated by Shoulder Pain, Shoulder Disorder, and Depression

The purpose of this study is to analyze the mediating effect of shoulder pain, shoulder disorder, and depression in the relationship between stress and health-related quality of life in middle-aged women using a serial mediation model. For this study, data was collected from middle-aged women aged between 35 and 64 living in Seoul, South Korea, from May 13, 2021 to May 23, 2021. Data regarding stress, health-related quality of life, shoulder pain, shoulder disorder, and depression were collected using a self-reported, structured survey. SPSS macro process (Model 6) was used, and the relationship between stress and health-related quality of life of participants were analyzed using serial mediation analysis using shoulder pain, shoulder disorder, and depression as variables. From the results of the study, it was observed that stress has a statistically direct impact on health-related quality of life. On performing serial mediation analysis, shoulder pain, shoulder disorder, and depression were found to be statistically significant, which predicts the relationship between stress and health-related quality of life; the variables showed an explanatory power of 33% for influencing the quality of life. Therefore, the relationship between stress and health-related quality of life was found to be partially mediated by shoulder pain, shoulder disorder, and depression. This study suggests the need for healthcare workers to develop a method, such as exercise intervention programs based on various degrees and types of physical activity, for improving the health-related quality of life and reducing stress caused by shoulder pain, shoulder disorder, and depression in middle-aged women.
RNIN-VIO: Robust Neural Inertial Navigation Aided Visual-Inertial Odometry in Challenging Scenes

In this work, we propose a tightly-coupled EKF framework for visual-inertial odometry with NIN (Neural Inertial Navigation) aided. Traditional VIO systems are fragile in challenging scenes with weak or confusing visual information, such as weak/repeated texture, dynamic environment, fast camera motion with serious motion blur, etc. It is extremely difficult for a vision-based algorithm to handle these problems. So we firstly design a robust deep learning based inertial network (called RNIN), using only IMU measurements as input. RNIN is significantly more robust in challenging scenes than traditional VIO systems. In order to take full advantage of vision-based algorithms in AR/VR areas, we further develop a multi-sensor fusion system RNIN-VIO, which tightly couples the visual, IMU and NIN measurements. Our system performs robustly in extremely challenging conditions, with high precision both in trajectories and AR effects. The experimental results of evaluation on dataset evaluation and online AR demo demonstrate the superiority of the proposed system in robustness and accuracy.
Spatio-Temporal Consistency for Semi-supervised Learning Using 3D Radar Cubes

Radar has been employed as a key component of perception modules for more than two decades. However, radar image labeling requires expert knowledge. At the same time, it is much more time-consuming than for general RGB images, which impedes further developments of radar. In order to alleviate the high-cost annotation problem in radar datasets, we present a novel, semi-supervised deep learning method based on the spatio-temporal consistency. This way we explore the potential of unlabeled radar frames to enhance performance. We utilize the consecutive radar frames from different timeline directions to encourage the model to learn the target motion. Moreover, the proposed self-weighted mechanism avoids over-fitting on certain predominant targets, by exploiting the supervised classification loss dynamically. We evaluate the proposed method on semantic segmentation and Vulnerable Road Users (VRUs) detection problems. The quantitative results compare favourably to the state-of-the-art and demonstrate the effectiveness of the proposed concepts. The ablation studies also show the effectiveness of the proposed components.
Corporate governance, institutional investor type and firm performance: Evidence from an emerging market

The study analyses the role of institutional investors in improving firm performance. Unlike in developed economies where firm ownership is widely dispersed, firms in emerging economies such as India have substantial promoter shareholdings (often in a majority or close to a majority). Given the promoter control of Indian companies, the role of institutional investors as external monitors is analysed. Following Brickley, Lease, and Smith (1988) and Almazan, Hartzell, and Starks (2005), the study categorises institutional investors as pressure-sensitive and pressure-insensitive institutional investors. Panel data for non-financial firms from India included in National Stock Exchange (NSE) 500 over the period 2008–2017 is studied using fixed-effects models. The study finds that the increased ownership of pressure-insensitive institutional investors is positively associated with firm performance. Also, the increased ownership of pressure-sensitive institutional investors is negatively associated with firm performance. These findings are consistent with the view that pressure-insensitive institutional investors are more effective monitors compared to pressure-sensitive institutional investors. The study offers insights into the role of institutional investors in economies where firms have a substantial promoter shareholding. The study documents that even with a substantial promoter shareholding and control, pressure-insensitive institutional investors aid in enhancing firm value
Utilization of supercritical carbon dioxide (SC-CO2) in lipids extraction from sewage sludge cake: A preliminary study

Sewage sludge containing a large number of lipids that can be recovered and utilised as a promising raw material in the production of biodiesel. Studies have been conducted to extract lipids from sludge using conventional solvent methods. However, all these conventional methods have some limitations such as extensive product separation and long extraction time (between 4 to 8 hours), which lead to high energy consumption. Supercritical carbon dioxide extraction (SFE) which utilises carbon dioxide (CO2) gas at its critical condition as solvent has been studied extensively in various fields for oil extraction especially for plant and vegetative. This is due to the shorter extraction time and the lipids can be easily separated from the extraction system. The present research has undertaken a comparison study of supercritical carbon dioxide (SC-CO2) utilisation in the extraction of lipids from sewage sludge against conventional soxhlet extraction of methanol and ethanol as solvent. The extraction of lipids from sewage sludge utilising SC-CO2 extraction was successfully being conducted with lipids yield of 0.69 % within 0.5 hours at the operating temperature of 50 °C and pressure of 20 MPa. The lipids were easily separated subsequently from the SFE system when CO2 is being released in gas form through the outlet valve during lipids collection. Whilst soxhlet extraction using methanol and ethanol as solvent (sludge: solvent ratio of 1:10) managed to extract 1.95 % and 2.81 % within 4 hours of extraction time at 60 °C, with the additional time needed to separate the lipids from solvent by evaporation.
Web-service promotion of SaaS service for mining design

The market of software for automating the processes of mining enterprises is represented by foreign solutions, which increases the dependence of Kazakhstani enterprises on third-party developers. The marketing strategy for promoting the domestic software product focus on conquering the market segment and increasing competitiveness.The study aims to develop a marketing strategy for promoting the national cloud service “3D-quarry” as a SaaS, taking into account the modern development of Kazakhstan and the globalization of the world’s economy. When writing the matrix of strategic analysis, an analysis of pricing models was used. The possibility of using various measures to promote the service was assessed. A marketing strategy for promoting software for subsoil use is proposed, including tactics of online and offline marketing. The choice of a pricing model for a SaaS product for specialized universities and small design organizations is substantiated. Within the SaaS framework, a set of indicators for evaluating the effectiveness of a marketing strategy is proposed. A comparative analysis of the payback period of the project when using different tariff plans is carried out. Planning horizon – 3 years, planned market share – 5%, conversion rate – 1%, expected payback period – 4.4 years.The developed pricing policy allows obtaining competitive advantages in comparison with the main representatives of the software market: in the segment of small design organizations – at the expense of an acceptable price, in the segment of educational institutions – at the expense of the freemium pricing model. Acknowledgment The study was carried out within the framework of the grant of the Ministry of Education and Science of the Republic of Kazakhstan on the topic IRN AP09561619 “Development of the core of the web service “3D-quarry”.
Cross-cultural Language Learning: Interpretative Engagement

Conceptualization of foreign language teaching as a cross-cultural interaction means engaging learners in various cultural mediations. Language use becomes a form of interpretative architecture of a target language. Understanding language use from a discursive perspective develops meta-pragmatic awareness and interpretative capacities of learners. The study answers the question of how to design the architecture of context analysis. This research aims to determine the effective ways of interpretative engagement of learners with aspects of pragmatics in the Ukrainian university setting. The study investigates how the process of interaction shapes the engagement of learners in practices of noticing, reflection, and comparison of cross-cultural situations. The data came from a case study on cross-cultural language learning within the second semester, 2021. The study analyzes the audio-recording of the classes, researcher notes, and post-course interviews of 24 participants. This research used a method of the content analysis. The study of the results, based on six categories (narrative analysis, discourse analysis, semiotic analysis, interpretative analyses, conversation analysis, and critical analysis), showed that the learners started to consider the nature of their cross-cultural mediation. The research proved that through such an interpretative engagement, students become engaged into working with languages and cultures. The study presents some recommendations for language teachers to create a meaning-making process from multiple perspectives.
Characteristic of the 2010-2020 Earthquakes in North Arm of Sulawesi based on Focal Mechanism and b-value

The north arm of Sulawesi has a fairly high level of seismicity. The North Sulawesi arm is bounded in the south by the Palu-Koro Fault, the northern part is bounded by the North Sulawesi Trench and the Molluca Sea Thrust in the east. Therefore, this study aims to analyze the characteristic of the 2010-2020 earthquakes in the north arm of Sulawesi by analyzing the earthquake’s focal mechanism and mapping the b-value using the maximum likelihood method. From this study, we obtained the focal mechanism consist of thrust and strike-slip, this is due to the activity of faults and subduction zones in the North arm of Sulawesi such as the Palu-koro fault, the Gorontalo Fault, North Sulawesi Trench, Molucca Sea Collision, and several other faults that affect the seismicity of this region. The variation of the b-value ranging from 0.5-1.1 These studies indicate that thrust fault regions have lower b-values, while strike-slip fault regions have intermediate b-values. Meanwhile, areas with active volcanoes tend to have high b-values. The results of this research can be used as a basis for decision making related to earthquake mitigation in this area in the future.
A Reinforcement Learning based Energy Management System for a PV and Battery Connected Microgrid System

Design of a standalone renewable system to meet the load demand is always complex, as renewable sources are intermittent in nature, which causes overloading on the distribution transformer. However, incorporating a battery system in the design would help in improving the efficiency and mitigate the problem of fluctuating voltages and line loadings. In this paper, a grid-connected PV and battery systems are designed with an objective to manage the energy distribution and meet the load demand. Without the need to know the priori system dynamics, a Q-learning algorithm is used for controlling the battery charge and discharge characteristics (state of charge) based on the load demand and power generated from the PV system. An allocation scheme is developed for the effective usage of the energy sources as well as to increase the life cycle of the battery. Thus, the proposed strategy not only maintains the state of charge of the storage unit but also allocates the usage of the PV source.
Covariant Space-Time Line Elements in the Friedmann-Lemaitre-Robertson-Walker Geometry

Most quantum gravity theories endow space-time with a discreet nature by space quantization on the order of Planck length (lp ). This discreetness could be demonstrated by confirmation of Lorentz invariance violations (LIV) manifested at length scales proportional to lp. In this paper, space-time line elements compatible with the uncertainty principle are calculated for a homogeneous, isotropic expanding Universe represented by the Friedmann-Lemaitre-Robertson-Walker solution to General Relativity (FLRW or FRW metric). To achieve this, the covariant geometric uncertainty principle (GeUP) is applied as a constraint over geodesics in FRW geometries. A generic expression for the quadratic proper space-time line element is derived, proportional to Planck length-squared and dependent on two contributions. The first is associated to the energy-time uncertainty, and the second depends on the Hubble function. The results are in agreement with space-time quantization on the expected length orders, according to quantum gravity theories and experimental constraints on LIV.
Cultural capital and elite university attendance in China

Abstract This article investigates the association between cultural capital and the likelihood of attending an elite university within the Chinese socio-educational context. Drawing on data from the Beijing College Students Panel Survey, we show that (1) objectified cultural capital is negatively correlated with the likelihood of attending an elite university whereas embodied cultural capital shows a positive effect; (2) both types of cultural capital enhance the proficiencies of extracurricular activities, which, however, are negatively associated with different quantiles of the National College Entrance Examination (NCEE) score; (3) learning capabilities can be strengthened by both types of cultural capital, but they cannot guarantee the attendance of an elite university since they only raise the middle and lower quantiles of the NCEE score; (4) only embodied cultural capital helps one attend an elite university by virtue of the channel of the NCEE exemption.
SYNERGISTIC EFFECT OF SILVER NITRATE AND PHOTON FLUX DENSITY ON THE IN-VITRO MULTIPLICATION OF BANANA (CV. GRAND NAIN, AAA)

The present study was aimed to investigate the effect of photon flux density and silver nitrate either alone or in combination on in-vitro micro-propagation of banana cv. Grand Nain (AAA). Five different concentrations of silver nitrate (0 to 68 μM) and PFD (0-55 μmol m s) were assessed. Plantlets were grown in culture room at 24±2°C with 16±8 h photoperiod. Highest number of bud formation was observed in explant cultured in bud establishment medium (MBE) medium supplemented with AgNO3 (34 μM) and placed under dark condition. Additionally maximum bud break was observed in the pre developed buds exposed to PFD of 45 μmolms. Maximum shoot and root elongation was observed in shoot elongation medium supplemented with AgNO3 (34 μM) under 50 μmolm s of photon flux density. Light quality also affected the total chlorophyll and phenolic content. Incorporation of silver nitrate in the culture medium reduced tissue browning and precocious rooting. Darkness and low light intensity significantly reduce precocious rooting in buds and resulted in albino effect in elongated shoots. However, high light intensity increased shoot proliferation and shoot elongation. The results obtained could be valuable for rapid and mass multiplication of banana to fulfilling the demand of Cavendish sub-group. Simultaneously the substitution of fluorescent lights with light emitting diode (LED) will be cost effective and result in cost saving of annual electricity consumption. The LED lighting system seemed to be the most suitable in terms of propagation efficiency, and plantlet quality.
Nurse capacity building strategy in health services in hospitals

Nurses are at the forefront of health services and even have a major influence in determining the degree of quality of health services in hospitals. So that the knowledge, skills and attitudes of nurses need to be improved, especially in the professional aspects of health service delivery. The purpose of this study was to describe and analyze the capacity building of nurses in health services in hospitals. Method; this research is qualitative with a case study approach. The focus of the research is the extent to which the steps of the nurse capacity building process in health services in hospitals. The instrument used in this study was the researcher himself. Data collection by interview, observation and literature review. Data analysis using; condensing data, presenting data, and drawing conclusions or verification. The results showed that the capacity-building process carried out by the hospital had gone well, but it needed to be improved in terms of spiritual and technological abilities for nurses so that it would improve the quality of health services. Conclusion; that in improving health services, capacity building for nurses is needed by adding the concept of a spiritual and technological approach.
Gaggle: Visual Analytics using Interactive Multi-Model Steering

— Recent multi-model visual analytics systems make use of multiple machine learning models to better ﬁt the data. This has been shown to be an improvement over traditional single-model approach in which systems rely on a single, pre-deﬁned model that may lack the ﬂexibility needed to capture nuances in the data. However, while multi-model visual analytic systems can be effective, their added complexity poses usability concerns as users are required to interact with the parameters of multiple models. In this paper, we present Gaggle, a multi-model visual analytics system that utilizes the advantages of steering multiple models while hiding the added complexity from the user. Speciﬁcally, user interaction with Gaggle is similar to existing single-model systems, in that users can demonstrate groups of similar data points for classiﬁcation or partial ordering of data points for ranking models. Based on these user interactions, Gaggle generates multiple models but only presents the best model based on user preferences. As a result, this multi-model steering approach allows the user to beneﬁt from the increased accuracy of multiple models while retaining the ease-of-use of a single-model system. To evaluate Gaggle, we conducted a controlled user study. The result conﬁrms our hypothesis that Gaggle is easy to use and users can discover accurate models without being burdened with keeping track of multiple models. This ﬁnding suggests a possible new approach for visual analytics systems that we discuss in the paper.
Impacts of Homophone Normalization on Semantic Models for Amharic

Amharic is the second-most spoken Semitic language after Arabic and serves as the official working language of the government of Ethiopia. In Amharic writing, there are different characters with the same sound, which are called homophones. The current trend in Amharic NLP research is to normalize homophones into a single representation. This means, instead of character 11We have used the IPA notation for Amharic character transliteration, , and , the character will be used; instead of , and , the character will be replaced; and so on. This was done by the assumption that they are repetitive alphabets as they have the same sound. However, the impact of homophone normalization for Amharic NLP applications is not well studied. When one homophone character is substituted by another, there will be a meaning change and it is against the Amharic writing regulation. For example, the word is “poverty” while means “salvage”. These two words are homophones, but they have different meanings. To study the impacts of homophone normalization, we develop different general-purpose pre-trained embedding models for Amharic using regular and normalized homophone characters. We fine-tune the pre-trained models and build some Amharic NLP applications. For PoS tagging, a model that employs a regular FLAIR embedding model performs better, achieving an F1-score of 77%. For sentiment analysis, the model from regular RoBERTa embedding outperforms the other models with an F1-score of 60%. For IR systems, we achieve an F1-score of 90% using the normalized document. The results show that normalization is highly dependent on the NLP applications. For sentiment analysis and PoS tagging, normalization has negative impacts while it is essential for IR. Our research indicates that normalization should be applied with caution and more effort towards standardization should be given.
An Empirical Analysis of the Development of Russian Innovation Economy — Based on the Solow Growth Model

Russia's long-term dependence on the development model of the resource economy can achieve the construction of the "oil curse", and the innovative economy has become an inevitable choice for its economic development. Measures to optimize the environment and mechanisms for innovation. In order to travel the actual situation of Russia's innovative economic development, this article uses the Solow model to formulate time data from 2000 to 2018, constructs an economic development model of Russian economic innovation, and constructs an economic development model of technological innovation. The results show that Russia's technological innovation has a negative growth effect, and there are still upcoming events in the development of Russia's innovation economy.