Miracle-dz/UniFAR-FTUs huggingface dataset:
A Web Development System for Producing an Interactive Electronic Book

In light of technological advances and the massive amount of published information available (including both reliable, accurate information and much that is not accurate), researchers need to be able to go back to original books and research published in scientific journals. This would be much easier if there were an interactive system to facilitate communication between readers and researchers. Many times, while reading a book or research study, we have needed to ask about ambiguous points, but we had no fast means of interacting with the author or other readers. Nowadays, there are many e-books and interactive communications across sites and smartphone programs, but all of them are poor with regard to communication among the readers of those books. We have worked to create a new way to benefit from communication. Our system can create truly interactive e-books that can answer queries through the use of a chat program that integrates with every book. This allows an author to publish his or her books as well as a publishing house could, and it also provides a source of information that makes inquiries easy. The person who answers the questions (the author) is a trustworthy source. The site also provides a set of exercises at the end of each book for the user to answer and test his or her understanding of the book. In addition, the website offers a chance for readers to evaluate each book, in order to enable sorting by quality and to gather the best suggestions from users. We are working to ensure the ability to form an electronic interactive library that has the largest number of e-books and is an excellent reference for readers and researchers. We found that our project can give readers many advantages over other programs, that makes information exchange easier because it allows for communication among the readers of the books. As a result, it saves much of the reader’s time that would be spent searching for information.
Online Telemanipulation Framework on Humanoid for both Manipulation and Imitation

Teleoperation of the robot is a promising technology that brings the robot to the real life because the complex decision-making algorithm can be replaced by the supervision of the human operator. To teleoperate the high dimensional humanoid robot intuitively like moving the operator’s own body, a motion retargeting algorithm is required to bridge the kinematics and dynamics differences between the robot and the operator. We propose the telemanipulation framework for the upper body of the humanoid only using 6 Virtual Reality (VR) trackers. The framework consists of the pose calibration procedure, the motion mapping method, and the multi-task control using Hierarchical Quadratic Programming (HQP). To validate the effect of the proposed method, three experiments are conducted including a user study for analysis of the hand position mapping, a dual-arm telemanipulation task in a real robot, and a comparison of the mapping methods in visual similarity.
Versões impressas no papel e na memória: Abrigo de Menores, novembro de 1956

A partir de uma denúncia do jornal “A Verdade”, de Florianópolis, em de novembro de 1956, sobre o Abrigo de Menores do Estado de Santa Catarina, encontrada no arquivo dos Irmãos Maristas, administradores do Abrigo na época, desenvolvemos uma narrativa que apresenta o transcurso do processo de pesquisa envolvendo o tema da denúncia, e como diferentes versões a respeito do episódio foram sendo constituídas em processo de disputa, às vezes silencioso, sobre qual teria maior legitimidade enquanto expressão de uma memória que falasse pelos Abrigados a respeito do ocorrido. Nessa disputa analisamos os Jornais da cidade, os Maristas, e como se desenvolveu um diálogo cruzado permitindo-se perceber como a imprensa e os sujeitos sociais “interagem” no processo social dinâmico. E, através de entrevistas com ex-Abrigados contemporâneos ao evento, e que participaram do mesmo, pois “fugiram” do Abrigo e foram até a redação do Jornal cobrar retratação, identificamos que, na trama histórica, a as crianças, se fazem sujeitos ativos dos processos sociais.
A Hybrid Approach for Product Classification based on Image and Text Matching

: The classification of products generates a high effort for retail companies because products must be classified manually in many cases. To optimize the product data creation process, methods for automating product classification are necessary. An important component of product data records are digital product images. Due to the latest developments in pattern recognition, these images can be used for product classification. Artificial neural networks are already capable of classifying digital images with lower error rates than humans. But the enormous variety of products and frequent changes in the product assortment are big challenges for current methods for classifying product images automatically. In this paper, we present a system that automatically classifies products based on their images and their textual descriptions extracted from the images according to the Global Product Classification Standard (GPC) by using machine learning methods to find similarities in image and text datasets. Our experiments show that the manual effort required to classify product data can be significantly reduced by machine learning techniques.
Solidification of additives for zinc-contaminated silt

The soil and vegetation on the ground surface are affected when the zinc content in the soil is excessively high. It is of great importance to choose suitable additives for the solidification/stabilization treatment of zinc-contaminated silt soil. Research focus on the stress–strain, shear strength, and durability of dry–wet cycle for solidified soil contaminated with different contents of zinc is scarce. In this study, the strength, microscopic, and stability of solidified silt are examined and analyzed, and the solidification agent with the best effect is identified. The silt near the mouth of the Pearl River in China is collected, the different contents of zinc are added, and then 15% cement and 15% cement + 5% slag or 15% cement + 10% slag are added to the mixture for curing. The effects of solidification with different additives at the different zinc contents are determined through test, for example, unconfined compressive strength, leaching, scanning electron microscopy, triaxial undrained solidification, X-ray diffraction, and dry–wet cycling experiments. The results show that the admixture that contained 15% cement + 10% slag has a better effect on solidification/stabilization of zinc-contaminated silt. Thus, this study provides a reference for the treatment of zinc-contaminated soft soil.
The Association between Online Buying of Electronic Gadgets and Demographics

Electronic commerce is the process by which buying and selling of goods and services is done by making use of the internet. Today, any item can be purchased through ecommerce. This research paper aims to study the association between online buying of electronic gadgets and demographics. To achieve the objective, primary data is collected with the help of questionnaire. Data is analyzed by making use of statistical tool and the inference has been drawn that there exists a significant relationship between online buying of electronic gadgets and demographics.
On a Problem in Graph Theory

Suppose there are n towns every pair of which are connected by a single one-way road (roads meet only at towns). Is it possible to choose the direction of the traffic on all the roads so that if any two towns are named there is always a third from which the two named can be reached directly by road?
Air Power, International Organizations, and Civilian Casualties in Afghanistan

Can the presence of international organizations reduce civilian deaths caused by aerial bombing? This commentary examines this question in the specific context of the U.S.-led war in Afghanistan. We evaluate this based on interviews conducted with members of international organizations that were present in Afghanistan during the conflict, existing intergovernmental organizations, nongovernmental organizations, and government reports, and with quantitative data on civilian casualties between 2008 and 2013. We conclude that there is tentative evidence from Afghanistan that international organizations can in fact reduce the severity of civilian killings that result from the use of air power. However, there is much need for greater data sharing to more fully answer this important question.
Advances in Infectious Disease Vaccine Adjuvants

Vaccines are one of the most significant medical interventions in the fight against infectious diseases. Since their discovery by Edward Jenner in 1796, vaccines have reduced the worldwide transmission to eradication levels of infectious diseases, including smallpox, diphtheria, hepatitis, malaria, and influenza. However, the complexity of developing safe and effective vaccines remains a barrier for combating many more infectious diseases. Immune stimulants (or adjuvants) are an indispensable factor in vaccine development, especially for inactivated and subunit-based vaccines due to their decreased immunogenicity compared to whole pathogen vaccines. Adjuvants are widely diverse in structure; however, their overall function in vaccine constructs is the same: to enhance and/or prolong an immunological response. The potential for adverse effects as a result of adjuvant use, though, must be acknowledged and carefully managed. Understanding the specific mechanisms of adjuvant efficacy and safety is a key prerequisite for adjuvant use in vaccination. Therefore, rigorous pre-clinical and clinical research into adjuvant development is essential. Overall, the incorporation of adjuvants allows for greater opportunities in advancing vaccine development and the importance of immune stimulants drives the emergence of novel and more effective adjuvants. This article highlights recent advances in vaccine adjuvant development and provides detailed data from pre-clinical and clinical studies specific to infectious diseases. Future perspectives into vaccine adjuvant development are also highlighted.
Three-Hour Argon Inhalation Has No Neuroprotective Effect after Open Traumatic Brain Injury in Rats

In vivo studies of the therapeutic effects of argon in traumatic brain injury (TBI) are limited, and their results are contradictory. The aim of this study was to evaluate the effect of a three-hour inhalation of argon (70%Ar/30%O2) after an open TBI on the severity of the neurological deficit and the degree of brain damage in rats. The experiments were performed on male Wistar rats (n = 35). The TBI was simulated by the dosed open brain contusion injury. The animals were divided into three groups: sham-operated (SO, n = 7); TBI + 70%N2/30%O2 (TBI, n = 14); TBI + 70%Ar/30%O2 (TBI + iAr, n = 14). The Neurological status was assessed over a 14-day period (using the limb-placing and cylinder tests). Magnetic resonance imaging (MRI) scans and a histological examination of the brain with an assessment of the volume of the lesions were performed 14 days after the injury. At each of the time points (days 1, 7, and 14), the limb-placing test score was lower in the TBI and TBI + iAr groups than in the SO group, while there were no significant differences between the TBI and TBI + iAr groups. Additionally, no differences were found between these groups in the cylinder test scores (day 13). The volume of brain damage (tissue loss) according to both the MRI and histological findings did not differ between the TBI and TBI + iAr groups. A three-hour inhalation of argon (70%Ar/30%O2) after a TBI had no neuroprotective effect.
Contrast-enhanced ultrasound Liver Imaging Reporting and Data System: Lights and shadows in hepatocellular carcinoma and cholangiocellular carcinoma diagnosis

BACKGROUND Contrast-enhanced ultrasound (CEUS) is considered a secondary examination compared to computed tomography (CT) and magnetic resonance imaging (MRI) in the diagnosis of hepatocellular carcinoma (HCC), due to the risk of misdiagnosing intrahepatic cholangiocarcinoma (ICC). The introduction of CEUS Liver Imaging Reporting and Data System (CEUS LI-RADS) might overcome this limitation. Even though data from the literature seems promising, its reliability in real-life context has not been well-established yet. AIM To test the accuracy of CEUS LI-RADS for correctly diagnosing HCC and ICC in cirrhosis. METHODS CEUS LI-RADS class was retrospectively assigned to 511 nodules identified in 269 patients suffering from liver cirrhosis. The diagnostic standard for all nodules was either biopsy (102 nodules) or CT/MRI (409 nodules). Common diagnostic accuracy indexes such as sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were assessed for the following associations: CEUS LR-5 and HCC; CEUS LR-4 and 5 merged class and HCC; CEUS LR-M and ICC; and CEUS LR-3 and malignancy. The frequency of malignant lesions in CEUS LR-3 subgroups with different CEUS patterns was also determined. Inter-rater agreement for CEUS LI-RADS class assignment and for major CEUS pattern identification was evaluated. RESULTS CEUS LR-5 predicted HCC with a 67.6% sensitivity, 97.7% specificity, and 99.3% PPV (P < 0.001). The merging of LR-4 and 5 offered an improved 93.9% sensitivity in HCC diagnosis with a 94.3% specificity and 98.8% PPV (P < 0.001). CEUS LR-M predicted ICC with a 91.3% sensitivity, 96.7% specificity, and 99.6% NPV (P < 0.001). CEUS LR-3 predominantly included benign lesions (only 28.8% of malignancies). In this class, the hypo-hypo pattern showed a much higher rate of malignant lesions (73.3%) than the iso-iso pattern (2.6%). Inter-rater agreement between internal raters for CEUS-LR class assignment was almost perfect (n = 511, k = 0.94, P < 0.001), while the agreement among raters from separate centres was substantial (n = 50, k = 0.67, P < 0.001). Agreement was stronger for arterial phase hyperenhancement (internal k = 0.86, P < 2.7 × 10-214; external k = 0.8, P < 0.001) than washout (internal k = 0.79, P < 1.6 × 10-202; external k = 0.71, P < 0.001). CONCLUSION CEUS LI-RADS is effective but can be improved by merging LR-4 and 5 to diagnose HCC and by splitting LR-3 into two subgroups to differentiate iso-iso nodules from other patterns.
Comparative Analysis of Gene Correlation Networks of Breast Cancer Patients Based on Mutations in TP53

Breast cancer is one of the most prevalent cancers in females, with more than 450,000 deaths each year worldwide. Among the subtypes of breast cancer, basal-like breast cancer, also known as triple-negative breast cancer, shows the lowest survival rate and does not have effective treatments yet. Somatic mutations in the TP53 gene frequently occur across all breast cancer subtypes, but comparative analysis of gene correlations with respect to mutations in TP53 has not been done so far. The primary goal of this study is to identify gene correlations in two groups of breast cancer patients and to derive potential prognostic gene pairs for breast cancer. We partitioned breast cancer patients into two groups: one group with a mutated TP53 gene (mTP53) and the other with a wild-type TP53 gene (wtTP53). For every gene pair, we computed the hazard ratio using the Cox proportional hazard model and constructed gene correlation networks (GCNs) enriched with prognostic information. Our GCN is more informative than typical GCNs in the sense that it indicates the type of correlation between genes, the concordance index, and the prognostic type of a gene. Comparative analysis of correlation patterns and survival time of the two groups revealed several interesting findings. First, we found several new gene pairs with opposite correlations in the two GCNs and the difference in their correlation patterns was the most prominent in the basal-like subtype of breast cancer. Second, we obtained potential prognostic genes for breast cancer patients with a wild-type TP53 gene. From a comparative analysis of GCNs of mTP53 and wtTP53, we found several gene pairs that show significantly different correlation patterns in the basal-like breast cancer subtype and obtained prognostic genes for patients with a wild-type TP53 gene. The GCNs and prognostic genes identified in this study will be informative for the prognosis of survival and for selecting a drug target for breast cancer, in particular for basal-like breast cancer. To the best of our knowledge, this is the first attempt to construct GCNs for breast cancer patients with or without mutations in the TP53 gene and to find prognostic genes accordingly.
Effects of posture and vibration magnitude on seat to head transmissibility during exposure to fore-and-aft vibration

An experimental study has been conducted on the vibration simulator, developed as a mockup of a railway vehicle. In this paper, the effect of variations in the posture and vibration magnitude on head motions in three translational directions (fore-and-aft, lateral and vertical) are studied with seat vibration in fore-and-aft direction. Thirty healthy male subjects are exposed to random vibration with three vibration magnitudes of 0.4, 0.8 and 1.2 m/s2 r.m.s. over the frequency range 1–20 Hz. The data results are analyzed in terms of seat-to-head transmissibility (STHT) in two sitting postures; backrest and forward lean. Vibration measurements of the head motions are made with an apparatus (bite-bar). The study confirms that the measured responses to single fore-and-aft axis vibration have shown notable cross-axis responses. An increase in the excitation magnitude consistently revealed a decrease in the response peak magnitude and the corresponding resonant frequency, particularly in the presence of a back support. Such non-linear behavior has been interpreted as a non-linear softening effect in the muscle tension under increasing intensity of vibration. The use of a back support significantly alters the biodynamic responses of the seated body, which is attributable to the constraint due to the backrest support.
Impact of Maternal Education and Age on Weight of Child at Birth: Use of Multinomial Logistic Model

The World Health Organization (WHO) prescribed 2.5 kilograms to 4.2 kilograms as the standard for normal birth weight (NBW) and every child whose birth weight is below the lowest bound is regarded as low birth weight (LBW) while above the highest bound is regarded as macrosomia. The odds for a LBW child to die as reported is about 40 times high when compared to a NBW child and these overwhelming death records are higher in developing countries. Therefore, urgent research about the causes of LBW especially in developing countries is very necessary and this motivated this research in Nigeria. In this paper, the Multinomial Logistic Regression (MLR) model was applied to secondary data from the 2018 Nigerian Demographic and Health Survey (NDHS) report to predict the probability of giving birth to NBW and macrosomia babies referenced to LBW babies. The maternal education level and age were considered as the predictor variables. The data was naturally stratified by maternal education level, that is (1 = Higher Education, 2 = Secondary Education, 3 = Primary Education, and 4 = No Education). The equal sample allocation technique which assigns equal stratum sample sizes (ni = 200 for the ith maternal education level) was adopted. The 800 sample size was reduced to 735 after screening for outliers in the maternal age variable. Considering the 54 LBW babies, 57% (0.5741) were from mothers with no education. The results showed that maternal education level and age have causal effects on child birth weight in Nigeria. Younger mothers (less than 28years) are 96.5% likely to have LBW babies while mothers who attained a minimum of primary, secondary, and higher education are 88.00%, 82.00%, and 57.90% likely to have NBW babies respectively when compared to those with no formal education. The research recommends that mothers should acquire at least primary school education and early child marriage (less than 28years) of the girl child should be discouraged.
A Region-based Training Data Segmentation Strategy to Credit Scoring

The rating of users requesting financial services is a growing task, especially in this historical period of the COVID-19 pandemic characterized by a dramatic increase in online activities, mainly related to e-commerce. This kind of assessment is a task manually performed in the past that today needs to be carried out by automatic credit scoring systems, due to the enormous number of requests to process. It follows that such systems play a crucial role for financial operators, as their effectiveness is directly related to gains and losses of money. Despite the huge investments in terms of financial and human resources devoted to the development of such systems, the state-of-the-art solutions are transversally affected by some well-known problems that make the development of credit scoring systems a challenging task, mainly related to the unbalance and heterogeneity of the involved data, problems to which it adds the scarcity of public datasets. The Region-based Training Data Segmentation (RTDS) strategy proposed in this work revolves around a divide-and-conquer approach, where the user classification depends on the results of several sub-classifications. In more detail, the training data is divided into regions that bound different users and features, which are used to train several classification models that will lead toward the final classification through a majority voting rule. Such a strategy relies on the consideration that the independent analysis of different users and features can lead to a more accurate classification than that offered by a single evaluation model trained on the entire dataset. The validation process carried out using three public real-world datasets with a different number of features. samples, and degree of data imbalance demonstrates the effectiveness of the proposed strategy. which outperforms the canonical training one in the context of all the datasets.
SoC Estimation for Lithium-ion Batteries: Review and Future Challenges

Energy storage emerged as a top concern for the modern cities, and the choice of the lithium-ion chemistry battery technology as an effective solution for storage applications proved to be a highly efficient option. State of charge (SoC) represents the available battery capacity and is one of the most important states that need to be monitored to optimize the performance and extend the lifetime of batteries. This review summarizes the methods for SoC estimation for lithium-ion batteries (LiBs). The SoC estimation methods are presented focusing on the description of the techniques and the elaboration of their weaknesses for the use in on-line battery management systems (BMS) applications. SoC estimation is a challenging task hindered by considerable changes in battery characteristics over its lifetime due to aging and to the distinct nonlinear behavior. This has led scholars to propose different methods that clearly raised the challenge of establishing a relationship between the accuracy and robustness of the methods, and their low complexity to be implemented. This paper publishes an exhaustive review of the works presented during the last five years, where the tendency of the estimation techniques has been oriented toward a mixture of probabilistic techniques and some artificial intelligence.