Miracle-dz/UniFAR-FTUs huggingface dataset:
The proliferation of noise pollution as an urban social problem in Wolaita Sodo city, Wolaita zone, Ethiopia

Abstract Noise pollution is an unwanted, unpleasant or disagreeable sound that causes discomfort to all living beings. Urban noise pollution is one of the problems of people who live in an urban area, which causes different health complications and social problems. The primary aim of this study was to explore the proliferation of noise pollution as an urban social problem and the community’s perception on noise pollution. We used a mixed-methods approach. Key informant interviews, in-depth interviews, focus group discussion, survey and documentary analysis were data collection methods used in the study. The study findings indicate that noise pollution affects social relations and quality of living environment, disturbs spoken communication and work performance, has a short and long effect on hearing capacity, disturbs mental health, decreases satisfaction on life, etc. The perception of the community on sources and effects of the problem is scrawny, and noise pollution is not considered as a serious problem by both the community members and the government officials in the city, but serious engagement is needed to solve the problems and to minimize their impacts. Mobilizing community representatives, influential persons, elites, activists, Medias and government officials should pay due attention to noise pollution to minimize the effect.
Adaptive Autonomous Navigation of Multiple Optoelectronic Microrobots in Dynamic Environments

The optoelectronic microrobot is an advanced light-controlled micromanipulation technology which has particular promise for collecting and transporting sensitive microscopic objects such as biological cells. However, wider application of the technology is currently limited by a reliance on manual control and a lack of methods for simultaneous manipulation of multiple microrobotic actuators. In this letter, we present a computational framework for autonomous navigation of multiple optoelectronic microrobots in dynamic environments. Combining closed-loop visual-servoing, SLAM, real-time visual detection of microrobots and obstacles, dynamic path-finding and adaptive motion behaviors, this approach allows microrobots to avoid static and moving obstacles, and perform a range of tasks in real-world dynamic environments. The capabilities of the system are demonstrated through micromanipulation experiments in simulation and in real conditions using a custom built optoelectronic tweezer system.
Robotic-Assisted Automatic Orientation and Insertion for Bronchoscopy Based on Image Guidance

Due to the large number and complex structure of bronchial branches, frequent orientation and insertions during bronchoscopy are likely to cause surgeon fatigue and errors. Therefore, we designed a robotic-assisted automatic intervention system (RAIS) based on image guidance, which aims to realize automatic orientation and insertion of bronchoscope, for improving the intelligence and efficiency of the bronchoscopy. To realize image guidance, we proposed a highly robust and accurate lumen center detection method, which combines deep learning-based object detection and histogram back-projection. With image guidance of lumen center, RAIS automatically completes the orientation and insertion of bronchoscope. The results of human phantom lung experiments show that the accuracy and recall of proposed lumen center method can respectively reach 94.12% and 86.23% when the bronchoscope is being localized by RAIS. Moreover, the results show that it is feasible to automate the orientation and insertion of bronchoscope using RAIS, which is more efficient than the manual operating the robot. The proposed RAIS could replace the surgeon in performing a large number of repetitive and simple tasks, which can efficiently reduce the workload of the surgeon and improve the safety and efficiency of the procedure.
The loss of Neg V → C in Middle English: 730

The timing of the loss of NegV1 in early English is compared with the loss of the negative particle ne and the rise of secondary negation. A verse corpus of Middle English verse is used, allowing comparison throughout thetime-span of the Middle English period. Neg VI in Old and Early Middle English is related to a strong but uninterpretable [+neg] feature on C°, which was checked by an interpretable [+neg] feature on Neg0, spelt out as ne. As the interpretable [+neg] feature formerly on Neg 0 became a Spec feature in NegP, a strong [+ neg] feature on C became unviable, since the negated verb's [+neg] feature was now uninterpretable and was eliminated before the verb could raise to check a strong feature on C°. It is shown that this development was not triggered by the loss of the negative particle ne, which followed the decline of NegV1. It is suggested that it may have been related to the rise of secondary negation, though data is insufficient to substantiate this possibility. In learnability terms, both the existence of the strong [+neg] feature on C 0 in early English and its loss were posited on the basis of syntactic evidence, rather than morphology. The formal expression of the prefix ne was not relevant to the loss of NegV1. Our claims are compared with the proposals of van Kemenade (2000) and Eyth6rsson (2002) with respect to negation in Early Germanic languages.
Vessel Trajectory Prediction in Maritime Transportation: Current Approaches and Beyond

The growing availability of maritime IoT traffic data and continuous expansion of the maritime traffic volume, serving as the driving fuel, propel the latest Artificial Intelligence (AI) studies in the maritime domain. Among the most recent advancements, vessel trajectory prediction is one of the most essential topics for assuring maritime transportation safety, intelligence, and efficiency. This paper presents an up-to-date review of existing approaches, including state-of-the-art deep learning, for vessel trajectory prediction. We provide a detailed explanation of data sources and methodologies used in the vessel trajectory prediction studies, highlight a discussion regarding the auxiliary techniques, complexity analysis, benchmarking, performance evaluation, and performance improvement for vessel trajectory prediction research, and finally summarize the current challenges and future research directions in this field.
Design of a Secured Database System Using Blockchain Technology

In this paper, a decentralized electronic voting system that provides inputs and outputs information support to admin/users in order to update their voting information while being capable of exhibiting different properties of blockchain security without the need for a third party. In this research, the Object Oriented Analysis and Design Methodology were adopted. The high level model of the proposed system was also designed and displayed in a format easily understandable to the user
A Tissue-Tended Mycophenolate-Modified Nanoparticle Alleviates Systemic Lupus Erythematosus in MRL/Lpr Mouse Model Mainly by Promoting Local M2-Like Macrophagocytes Polarization

Background Mycophenolate mofetil (MMF), for which the bioactive metabolite is mycophenolic acid (MPA), is a frequently used immunosuppressant for systemic lupus erythematosus (SLE). However, its short half-life and poor biodistribution into cells and tissues hinder its clinical efficacy. Our dextran mycophenolate-based nanoparticles (MPA@Dex-MPA NPs) have greatly improved the pharmacokinetics of MMF/MPA. We here tested the therapeutic efficacy of MPA@Dex-MPA NPs against SLE and investigated the underlying mechanism. Methods The tissue and immune cell biodistributions of MPA@Dex-MPA NPs were traced using live fluorescence imaging system and flow cytometry, respectively. Serological proinflammatory mediators and kidney damage were detected to assess the efficacy of MPA@Dex-MPA NPs treatments of MRL/lpr lupus-prone mice. Immune cell changes in the kidney and spleen were further analyzed post-treatment via flow cytometry. Bone marrow-derived macrophages were used to investigate the potential mechanism. Results MPA@Dex-MPA NPs exhibited superior therapeutic efficacy and safety in the MRL/lpr mice using significantly lower administration dosage (one-fifth) and frequency (once/3 days) compared to MMF/MPA used in ordinary practice. The overall prognosis of the mice was improved as they showed lower levels of serological proinflammatory mediators. Moreover, kidney injury was alleviated with reduced pathological signs and decreased urine protein-creatinine ratio. Further investigations of the underlying mechanism revealed a preferential penetration and persistent retention of MPA@Dex-MPA NPs in the spleen and kidney, where they were mostly phagocytosed by macrophages. The macrophages were found to be polarized towards a CD206+ M2-like phenotype, with a downregulation of surface CD80 and CD40, and reduced TNF-α production in the spleen and kidney and in vitro. The expansion of T cells was also significantly inhibited in these two organs. Conclusion Our research improved the efficacy of MPA for MRL/lpr mice through synthesizing MPA@Dex-MPA NPs to enhance its tissue biodistribution and explored the possible mechanism, providing a promising strategy for SLE therapy.
Permute and conjugate: the conjugacy problem in relatively hyperbolic groups

Modelled on efficient algorithms for solving the conjugacy problem in hyperbolic groups, we define and study the permutation conjugacy length (PCL) function. This function estimates the length of a short conjugator between words u and v , up to taking cyclic permutations. This function might be bounded by a constant, even in the case when the standard conjugacy length function is unbounded. We give applications to the complexity of the conjugacy problem, estimating conjugacy growth rates, and languages. Our main result states that for a relatively hyperbolic group, the PCL function is bounded by the PCL function of the parabolic subgroups.
Electronic Word of Mouth Analysis of Brand Attachment on MSME Products

This study aims to determine the effect of electronic word of mouth (eWOM) on brand attachment on MSME products. The technique used in this research was non-probability sampling with the purposive sampling method. The data collection technique in this research was a questionnaire distributed to 197 respondents via a google form. The data analysis used was f-test analysis, t-test, and simple linear regression analysis. Based on the results of the t-test, it was found that the t-count on the electronic word of mouth variable was 5.491 with a significance level of 0.000 and t-table = 1.972 with the probability of t being sig <0.05 for the brand attachment variable. Meanwhile, based on the f-test results, the calculated F value was 30,152 with a significance level of 0.000 and F table = 3.89. The probability of 30,152 is greater than 0.05 and the calculated F value > F table showing that electronic word of mouth had a positive and significant effect on the brand attachment variable. The results of the study indicate that the presence of eWOM in a product can affect the brand attachment of an MSME product. The form of eWOM on social media can be seen when producers/sellers post on social media about product-related information, followers will respond (mention, comment, repost). At that time, the brand awareness of the product will increase.
Economic sanctions, repression capacity, and human rights

Abstract What is the relationship between economic sanctions and the human rights conditions of target countries? We suggest a two-stage mechanism to explain how sanctions deteriorate the human rights condition in the target country. In the repressive capacity stage, sanctions increase the capacity the target government can use for political repression. We introduce the concepts of political corruption, judicial dependence, and the government's media censorship as political repression tools of target governments. In the violation stage, the increased capacity to repress leads to worsening the target’s human rights condition. We also find that, while human rights sanctions are not likely to increase political repression in the target country, non-human rights sanctions are more likely to increase the political repression therein. Furthermore, such increased capacity for repression, specifically political corruption and judiciary dependence, in the target country adversely affected the human rights condition.
Elucidation of the Probable Ovarian-Dependent Mechanism of the Estrogenic Effects of <i>Buccholzia coriacea</i> and Progesterone Effects of <i>Cogniauxia pololeana</i> in the Rat

The present study was carried out with the objective of evaluating, in castrated rats, the utero trophic, hormonal and biochemical activities of aqueous extracts of Buchholzia coriacea (BC) and Cogniauxia podolaena (CP) leaves. Each extract administered at the dose of 600 mg/Kg in castrated rats did not cause a significant change in the fresh weight/dry weight ratio of the uterus compared to castrated rats given distilled water. However, those re-ceiving 17-β-estradiol as a reference product showed a significant (p < 0.5) increase in this ratio. These results indicate the absence of uterotrophic effects of both extracts in the ovariectomized rat compared with the effects of 17-β estradiol. In addition, the extracts did not cause significant changes in estrogen or progesterone levels in treated rats, as observed with 17-β-estradiol. In addition, the determination of protein and total cholesterol in the uterus of castrated rats treated with each extract did not show significant variation from controls. At the time, castrated rats treated with 17-β-estradiol showed a significant increase (p < 0.5) in uterine protein level and a significant decrease (p < 0.5) in total cholesterol level. Only the blood protein level was significantly increased in the castrated rats that received the extracts. These results suggest that the respective estrogenic and progesterone effects of the extracts of the two plants may be ovarian-dependent, these plants would not contain phytohormones. the Probable Ovarian-Dependent Mechanism
Integrated Fertilization with Bagasse Vermicompost Changes the Microbiome of Mencía Must and Wine

Winemaking is a well-known process that includes several steps in the production of grape must and wine. Grape marc, or bagasse, is a byproduct of wine production that can be vermicomposted and used as organic fertilizer. Grape marc vermicompost has microbial communities that are richer and more stable than grape marc alone, and its addition to a vineyard’s terroir can improve grape yields and wine quality. Here we compare the must and wine microbiota of Mencía from grapevines treated with and without (standard fertilization) vermicompost derived from Mencía grape marc. Mencía is a high-quality red wine broadly grown in Galicia, Spain, and is appreciated for its fresh acidity and fruity flavors. When Mencía grapevines are treated with vermicompost derived from its grape marc, Mencía vines increase their grape production, and the final wine improves its organoleptic properties. Metataxonomic analyses of the bacterial 16S rRNA and fungal ITS gene regions showed that Mencía must and wine have the distinct taxonomic composition (phyla, genera and ASVs—amplicon sequence variants) of bacterial and fungal groups. Must and wine bacteriotas and mycobiotas show no significant variation in alpha-diversity, while wine bacteriotas and mycobiotas show significant differences in microbial structure (beta-diversity) between treated and control grapevines. Likewise, the functional diversity and predicted metabolic pathways (biosynthesis, degradation/utilization/assimilation, generation of precursor metabolites and energy, macromolecule modification and superpathways) of the must and wine microbiota also show significant changes. Our study proposes that changes in the abundance of microbial taxa and the metabolic processes they undergo during winemaking may improve Mencía’s organoleptic properties and productivity.
An experimental comparison of the widely used pre‐trained deep neural networks for image classification tasks towards revealing the promise of transfer‐learning

The easiest way to propose a solution based on deep neural networks is using the pre‐trained models through the transfer‐learning technique. Deep learning platforms provide various pre‐trained deep neural networks that can be easily applied for image classification tasks. So, “Which pre‐trained model provides the best performance for image classification tasks? ” is a question that instinctively comes to mind and should be shed light on by the research community. To this end, we propose an experimental comparison of the six popular pre‐trained deep neural networks, namely, (i) VGG19, (ii) ResNet50, (iii) DenseNet201, (iv) MobileNetV2, (v) InceptionV3, and (vi) Xception by employing them through the transfer‐learning technique. Then, the proposed benchmark models were both trained and evaluated under the same configurations on two gold‐standard datasets, namely, (i) CIFAR‐10 and (ii) Stanford Dogs to benchmark them. Three evaluation metrics were employed to measure performance differences between the employed pre‐trained models as follows: (i) Accuracy, (ii) training duration, and (iii) inference time. The key findings that were obtained through the conducted a wide variety of experiments were discussed.
Performativity and representativeness of trans Brazilian people on YouTube: gender affirmation as a spectacle

ABSTRACT From the analysis of videos, we sought to understand the specificities of the gender affirmation of trans people born and/or residing in Brazil who create and produce content on YouTube with the objective of sharing snapshots of their lives, mainly related to their gender identity(ies). This is qualitative research in which twenty-nine videos by eight different people were collected and analyzed through the method of netnography and later discussed in light of post-structuralist studies such as Queer Theory, feminist, and transfeminist studies. The existence of specific content patterns was perceived in the videos that contained trans themes, creating a transnormative on YouTube, with its own segments, in addition to the idealization and performativity of the bodies of cis and trans people. Also, the research gave a unique view of the impressions that those YouTubers had about Brazilian health services on gender affirmation technologies and the medical and psychological processes they have experienced or understand to be necessary. YouTube is also an environment where subjective expressions and knowledge are shared, creating a new space of visibility and trans representation, in addition to enabling the construction of a community between those who create the content and the viewers.
Social Acceptance: Mapping the Perspectives of Stakeholder in the Development of Geothermal Power Plants in West Sumatra, Indonesia

The Indonesian government is pushing for an increase in the development of geothermal power plants. West Sumatra is one of twenty provinces in Indonesia that have geothermal potential. The government has given the company permission to develop geothermal potential in two districts in West Sumatra. Phase I development has been successfully carried out in South Solok Regency, while Solok Regency has experienced problems. Social acceptance is one of the determining factors for the success of the project development. This article aims to look at the perspectives of stakeholders around the geothermal field, and analyze the social acceptance of a geothermal power plant project in West Sumatra. This research uses case study research method. Data collection is done by interview, observation, and document studies (such as Environmental Impact Assessment documents, government regulations on geothermal, and local media news). The results show that there are variations in stakeholder perspectives regarding geothermal power plants. Public acceptance of the geothermal power plant in South Solok Regency is relatively good because the company positions the surrounding community as partners. Social acceptance at the project site in Solok Regency was relatively weak and there was a resistance movement. Socio-political acceptance (by various stakeholders such as the Provincial Government, Regency Government, Nagari Government, and Regional House of Representatives) tends to be substantial due to the multiplier effect of development. This study has limitations in looking at the dynamics of local politics, which are the determinants of support, and the readiness of the Regional Government to face the rejection phenomenon at the local level. This is an input for further research, because in this study it was found that social acceptance requires the support and readiness of the Regional Government. So that the rejection by the local community can be resolved, so that the extraction of electrical energy goes according to the government's target, and the rights of the local community in the project site area are fulfilled.
Research on Tire/Road Peak Friction Coefficient Estimation Considering Effective Contact Characteristics between Tire and Three-Dimensional Road Surface

In the field of transportation, the accurate estimation of tire–road peak friction coefficient (TRPFC) is very important to improve vehicle safety performance and the efficiency of road maintenance. The existing estimation algorithms rarely consider the influence of road roughness and road texture on the estimation results. This paper proposes an estimation method of TRPFC considering the effective contact characteristics between the tire and the three-dimensional road. In the longitudinal and lateral directions of tire–road contact, the model is optimized by incorporating the effective contact area ratio coefficient into the LuGre tire model. The optimized model characterizes the road texture by road power spectrum and establishes the relationship between road texture and tire force. In the vertical direction of tire–road contact, the force transfer between tire and road is represented by a new multi-point contact method. By combining the above models with the normalization method and the unscented Kalman filter (UKF), the timely and accurate estimation of the peak friction coefficient of the tire and the 3D road is realized. Simulation and real vehicle experiments verify the effectiveness of the estimation algorithm.
Aplicación móvil como apoyo en la práctica de la destreza operatoria aritmética de estudiantes de secundaria

En el presente artículo se propone una aplicación gamificada móvil que promueva la resolución de ejercicios aritméticos empleando solo el conjunto de los números naturales. Para el desarrollo de la investigación, se empleó una metodología descriptiva mixta. Y para validar la aplicación, se realizaron pruebas de funcionamiento y de usabilidad. Estas últimas con una muestra aleatoria de 50 estudiantes que cursaban los tres años de la educación básica (secundaria), a quienes se les explicó vía remota el uso de la aplicación, y durante una semana la emplearon para practicar su destreza operatoria. Los estudiantes respondieron el cuestionario “Escala de usabilidad de sistemas” (SUS), también vía remota. Entre los resultados destaca que la aplicación tuvo un buen nivel de aceptación, de acuerdo con la escala de evaluación propuesta por la literatura (68-80.3). Además, al revisar la satisfacción del usuario, la eficiencia, efectividad, tasa de errores y memorabilidad, se encontró que los estudiantes de la muestra consideraron a la aplicación con una alta eficiencia: no encontraron errores al usar la aplicación, les resultó muy intuitiva y comentaron que ir desbloqueando los niveles contribuyó a que estuvieran motivados y concentrados, debido a que buscan estar en los primeros niveles de la tabla de liderato. Se concluye que las mecánicas y dinámicas empleadas de la gamificación permitieron al estudiante practicar su destreza operatoria.