Miracle-dz/UniFAR-FTUs huggingface dataset:
Children and Drug Trafficking in Brazil: Can International Humanitarian Law Provide Protections for Children Involved in Drug Trafficking?

Brazil has seen a rise in children in narco-trafficking due to increased conflicts between factions and local law enforcement. Mainstream media and scholars tend to frame actions of these factions as organized crime, ignoring the generalized violence the communities and children experience. The aim of this study is to conduct a scoping review to consider whether or not Brazilian children involved in drug trafficking can be classified as child soldiers. Drawing from the international definition of Armed Conflict in Article 3 of the Geneva Convention of 1949 and Article 1 of the Additional Protocol II, and comparing situations of realities faced by Brazilian children involved in narco-trafficking, we argue that their reality is analogous to that of child soldiers, as defined by the Paris Principles on the Involvement of Children in Armed Conflict 2007; thus, going beyond the organized crime definition. In characterizing them as child soldiers, we argue for improving the children’s ability to be reintegrated into society, with the collective help of the international community.
A Newly Identified Complication of Patellofemoral Arthroplasty: Case Report and Literature Review

Background Patellofemoral arthroplasty (PFA) is a surgical option for patients older than 40 years old who are affected by patellofemoral osteoarthritis. Regarding the complications of PFAs, few studies have investigated periprosthetic fractures. The purpose of this literature review was to highlight a previously overlooked complication of primary prosthetic surgery of the patellofemoral joint. Methods Three literature databases were searched for studies published between 2000 to 2020 using relevant keywords. A total of 4,942 articles were originally identified. After excluding duplicates and analysing the titles and abstracts, 20 studies were considered. From these, data regarding the number of cases, clinical outcomes and complications were extracted. Results Among the 20 selected articles, only one described periprosthetic fractures as a complication of PFAs. Herein, we also report an illustrative case of an unknown fracture complication. No cases in the literature were found that described the type of complications experienced by our patient during the postoperative period. Conclusions This review confirms the lack of data about clinical outcomes and fracture complications of PFAs. In primary prosthetic surgery of the patellofemoral joint, patient selection and close consideration of demographic factors (such as BMI and age) and intraoperative factors (such as patellar thickness and size of the trochlear component) play a key role in optimising pre-operative planning to avoid intraoperative periprosthetic fractures.
Risks and complications in rhinoplasty. A comparative study in structural vs preservation rhinoplasty

Introduction. Rhinoseptoplasty is considered the most challenging operation because many techniques have to be taken into consideration to achieve an optimal aesthetic and functional results. Rhinoseptoplasty techniques have been perfected over time, following two main surgical approaches: structural rhinoplasty (resection/ reconstruction) and conservative (preservation rhinoplasty). Methods. The authors present the risks and complications in a comparative study of 100 cases with patients in primary rhinoseptoplasty performed between 2019-2021: 50 cases in Structural Rhinoplasty and 50 cases in Preservation Rhinoplasty. The study presents two surgical concepts of rhinoplasty regarding the main advantages, disadvantages and indications of each type of rhinoseptoplasty surgery. Results and conclusions. Complications post-rhinoseptoplasty can be considered as perioperative, functional, anatomic (aesthetic) and psyhological. In this study 10 cases (10%) of primary rhinoplasty required revision surgery. The most frequent postoperative deformity is the “pollybeak” when a deep naso-frontal angle, cartilaginous hump and reduced tip projection are present preoperatively. The pollybeak was the indication in 4 cases (40%) of all revision rhinoplasties. Other frequent postoperative deformities are: wide nasal tip, retractions of the columella base and irregularities of the nasal dorsum. These deformities are very often combined and caused by a loss of septal support. Septorhinoplasty is a difficult procedure and the surgeon must have accurate anatomical knowledge and rich clinical experience. The risks for rhinoplasty-complications can be reduced with increasing experience. It is very important to make distinction between complication and mistake.
Sample processing by Bi‐FIB for in situ TOF‐SIMS imaging of buried interfaces

Focused ion beam (FIB) is commonly used as a standard machining technique in failure analysis, quality control, reverse engineering, material research, and so on, for the samples having microstructures and nanostructures. FIB combined with time‐of‐flight secondary ion mass spectrometry (TOF‐SIMS), so‐called FIB‐TOF, has attracted attention as a method to determine the three‐dimensional (3D) chemical distributions of complex samples. In general, a highly focused Ga+ ion beam is used for FIB, however, the FIB‐milled area is limited and it was difficult to expand the Ga‐FIB to hundreds of micron length scale for sample fabrication. In order to overcome the drawback, we proposed the Bi‐FIB approach for large scale sample cross‐sectioning. Although the possibility of Bi‐FIB has been reported, there were almost no performance examinations as well as practical applications. In this study, therefore, the authors summarize the comparison of milling rate and milling damage between Ga‐FIB and Bi‐FIB. As a result, it was found that Bi‐FIB can provide a higher milling rate with thinner milling damage. Finally, the Bi‐FIB approach was applied to the interfacial analysis of all‐solid‐state battery (ASSB) material. With this approach, the detailed chemical distributions at the interface were discovered, leading to the better understanding of battery behaviors.
Can Fashion Aesthetics be Studied Empirically? The Preference Structure of Everyday Clothing Choices

Despite fashion being one of the most common and accessible aesthetic activities in everyday life, very few empirical studies of clothing selection and preferences exist. To address this empirical gap, an online survey of 500 participants was constructed. A four-factor preference structure, Everyday Clothing Preference Factors (ECPF), emerged, consisting of essential, comfortable, feminine, and trendy styles. Further analysis revealed the preference for each of these four factors to be associated with clothing colors and individual differences. The transferability of ECPF across three preference judgment types (clothing one likes and owns, clothing one likes but does not own, and clothing one owns but does not like) revealed the robustness of the preference structure, through which a short version of ECPF was created. The paper concludes by discussing the implications and impact of scientifically studying fashion as an object of aesthetics and empirical study.
Sulfur-Containing Metabolites from Marine and Terrestrial Fungal Sources: Origin, Structures, and Bioactivities

Organosulfur natural products (NPs) refer to the different kinds of small molecular-containing sulfur (S) elements. Sulfur-containing NPs tightly link to the biochemical processes and play an important role in the pharmaceutical industry. The majority of S-containing NPs are generally isolated from Alliaceae plants or bacteria, and those from fungi are still relatively rare. In recent years, an increasing number of S-containing metabolites have been discovered in marine and terrestrial fungi, but there is no comprehensive and targeted review to summarize the studies. In order to make it more straightforward to better grasp the fungal-derived S-containing NPs and understand the particularity of marine S-containing NPs compared to those from terrestrial fungi, we summarized the chemical structures and biological activities of 89 new fungal-derived S-containing metabolites from 1929 when the penicillin was discovered to the present in this current review. The structural and bioactive diversity of these S-containing metabolites were concluded in detail, and the preliminary mechanism for C-S bond formation in fungi was also discussed briefly.
GIWRF-SMOTE: Gini impurity-based weighted random forest with SMOTE for effective malware attack and anomaly detection in IoT-Edge

ABSTRACT The Internet of Things (IoT) is a smart technology that has switched the conventional way of living into smart living. As their usage becomes unavoidable, malware attacks in IoT networks have also increased. Many investigations and studies have proposed different methods to detect malware attacks, but these measures have some performance degradation in terms of accuracy, error, and lack of comprehensiveness. The cloud-based IoT infrastructure further creates latency and security problems. The machine learning (ML)-based edge computing can overcome these complications by automating the responses and moving the computation nearer to the network edge, where data is created. In this work, the performance of various prominent ML algorithms, such as logistic regression (LR), naive Bayes (NB), support vector machine (SVM), decision tree (DT), random forest (RF), and k-nearest neighbor (KNN), has been compared to predict malware attack accurately in IoT-edge environment. To enhance the prediction accuracy of the ML algorithms, the unbalanced data is converted into balanced data using the synthetic minority oversampling technique (SMOTE) and optimum features are selected using the Gini impurity-based weighted RF feature selection technique (GIWRF). The investigational results show that among six ML algorithms, RF with GIWRF attained the highest accuracy of 99.39%. GRAPHICAL ABSTRACT
Depressive Symptoms as a Mediator between Excessive Daytime Sleepiness and Suicidal Ideation among Chinese College Students

The purpose of this study was to verify the mediating role of depressive symptoms between excessive daytime sleepiness and suicidal ideation in college students. Of the 6944 participants, 2609 (37.6%) were male and 4335 (62.4%) were female. College students with excessive daytime sleepiness (p < 0.001) and those with depressive symptoms (p < 0.001) were more likely to have suicidal ideation. Moreover, both excessive daytime sleepiness (β = 0.14, 95% CI: 1.01–1.32) and depressive symptoms (β = 1.47, 95% CI: 3.80–5.00) were associated with suicidal ideation. The effect size of the mediating role of depressive symptoms in excessive daytime sleepiness to suicidal ideation was 50.41% for the entire sample, 58.33% for males, and 42.98% for females. Depressive symptoms partially mediated the relationship between excessive daytime sleepiness and suicidal ideation. The timely assessment of depressive symptoms in college students with excessive daytime sleepiness, and intervention, may reduce their risk of suicidal ideation.
Transcriptomic Analysis of Distal Parts of Roots Reveals Potentially Important Mechanisms Contributing to Limited Flooding Tolerance of Canola (Brassica napus) Plants

Since most of the root metabolic activities as well as root elongation and the uptake of water and mineral nutrients take place in the distal parts of roots, we aimed to gain insight into the physiological and transcriptional changes induced by root hypoxia in the distal parts of roots in canola (Brassica napus) plants, which are relatively sensitive to flooding conditions. Plants were subject to three days of root hypoxia via lowering oxygen content in hydroponic medium, and various physiological and anatomical features were examined to characterize plant responses. Untargeted transcriptomic profiling approaches were also applied to investigate changes in gene expression that took place in the distal root tissues in response to hypoxia. Plants responded to three days of root hypoxia by reducing growth and gas exchange rates. These changes were accompanied by decreases in leaf water potential (Ψleaf) and root hydraulic conductivity (Lpr). Increased deposition of lignin and suberin was also observed in the root tissues of hypoxic plants. The transcriptomic data demonstrated that the effect of hypoxia on plant water relations involved downregulation of most BnPIPs in the root tissues with the exception of BnPIP1;3 and BnPIP2;7, which were upregulated. Since some members of the PIP1 subfamily of aquaporins are known to transport oxygen, the increase in BnPIP1;3 may represent an important hypoxia tolerance strategy in plants. The results also demonstrated substantial rearrangements of different signaling pathways and transcription factors (TFs), which resulted in alterations of genes involved in the regulation of Lpr, TCA (tricarboxylic acid) cycle-related enzymes, antioxidant enzymes, and cell wall modifications. An integration of these data enabled us to draft a comprehensive model of the molecular pathways involved in the responses of distal parts of roots in B. napus. The model highlights systematic transcriptomic reprogramming aimed at explaining the relative sensitivity of Brassica napus to root hypoxia.
Morphology of Lymphoid Tissue in the Lungs of Guinea Pigs Infected with Mycobacterium bovis against the Background of Vaccine Immunity and the Action of Betulin and Its Derivatives

Tuberculosis caused by Mycobacterium bovis is a serious problem for animal and human health worldwide. A promising concept for the design of anti-tuberculosis drugs is the conjugation of an immunogenic fraction isolated from bacterial vaccines with a stimulating component. Taking this principle as a basis, conjugates based on BCG antigens with betulin and its derivatives (betulonic and betulinic acids) were designed. The aim of this research was to study the morphological changes in the lymphoid tissue associated with the bronchial mucosa lungs (BALT) in guinea pigs sensitized with experimental conjugates using a model of experimental tuberculosis. The results showed a significant decrease in the BALT response, expressed by a decrease in the diameter of lymphatic follicles and a decrease in their activity when exposed to conjugates based on BCG antigens with betulin and, especially, with betulonic acid, with a visually greater number of plasma cells observed in the lung tissues of guinea pigs of these groups. The absence of tuberculous foci and low BALT activity in the lungs of animals treated with betulin and betulonic acid are probably associated with the activation of humoral immunity under the action of these conjugates.
A New Feature Extraction Method for EMG Signals

Surface Electromyography (sEMG) is an important tool for gesture recognition. Features and classification methods have to be carefully selected to be successful in the recognition of electromyografic signals. In most of the sEMG studies, time and frequency domain features have been extracted and classified with a single classifier. But neither one feature nor one classifier alone has achieved high classification accuracies. Using a feature and classifier combination would be a solution for this problem, and increase the accuracies. As a contribution to this field, a new time domain EMG feature is suggested and its classification performance is examined for feature and classifier combinations in this study. According to the results of this study, the new feature has high classification accuracy, and when it is used with AR and ST features, the average of the classification accuracy reaches 99.57% for multiple SVM classifier. Besides, the new feature+AR+ ST feature combination shows high classification accuracy for single classifier, and this eliminates the need for multiple classifiers.
Performance of a Vector-Controlled PMSM Drive without Using Current Sensors

The current sensorless vector-controlled permanent-magnet synchronous motor (PMSM) drive using a single sensor (i.e., speed sensor) is presented in this work. The current sensors are removed, and the estimated currents are used to close the current loop to minimize the drive cost and make it fault-tolerant against current sensor failure. A classical vector-control PMSM drive requires at least three sensors, i.e., two current sensors and one speed/position sensor. This paper presents a new current estimation technique that is free from inverter switching states, an integrator, and differentiator terms. The drive is suitable for retrofit applications, as it does not require any additional hardware. The reference voltages (vds and vqs) are used to estimate the rotor reference frame currents (i.e., iqs and ids). The presented algorithm depends on the stator resistance (Ɍs). The online Ɍs estimation algorithm is used for compensation to overcome the effect of the Ɍs on the estimated currents. The sensitivity analysis for the currents against the speed is verified and presented. The speed loop is closed with actual speed information, which will try to maintain the reference speed under any circumstances. The proposed current sensorless PMSM drive was validated using MATLAB/Simulink and also verified on a hardware prototype. The presented technique was verified for various operation conditions, and some of the extensive results are presented.
A Generic AI-Based Technique for Assessing Student Performance in Conducting Online Virtual and Remote Controlled Laboratories

Due to the COVID-19 pandemic and the development of educational technology, e-learning has become essential in the educational process. However, the adoption of e-learning in sectors such as engineering, science, and technology faces a particular challenge as it needs a special Laboratory Learning Management System (LLMS) capable of supporting online lab activities through virtual and controlled remote labs. One of the most challenging tasks in designing such LLMS is how to assess a student’s performance while an experiment is being conducted and how stuttering students can be automatically detected while experimenting and providing the appropriate assistance. For this, a generic technique based on Artificial Intelligence (AI) is proposed in this paper for assessing student performance while conducting online labs and implemented as a performance evaluation module in the LLMS. The performance evaluation module is designed to automatically detect the student performance during the experiment run time and triggers the LLMS virtual assistant service to provide struggling students with the appropriate help when they need it. Also, the proposed performance assessment technique is used during the lab exam sessions to support the automatic grading process conducted by the LLMS Auto-Grading Module. The proposed performance evaluation technique has been developed based on analyzing the student’s mouse dynamics to work generally with any type of simulation or control software used by virtual or remote controlled laboratories; without the need for special interfacing. The study has been applied to a novel dataset built by the course instructors and students simulating a circuit on TinkerCad. Using mouse dynamics fetching, the system extracts features and evaluates them to determine if the student has built the experiment steps in the right way or not. A comparison study has been developed between different Machine Learning (ML) models and a number of performance metrics are calculated. The study confirmed that Artificial Neural Network (ANN) and Support Vector Machine (SVM) are the best models to be used for automatically evaluating student performance while conducting the online labs with a precision reaching up to 91%.
3D Composite PDMS/MWCNTs Aerogel as High-Performing Anodes in Microbial Fuel Cells

Porous 3D composite materials are interesting anode electrodes for single chamber microbial fuel cells (SCMFCs) since they exploit a surface layer that is able to achieve the correct biocompatibility for the proliferation of electroactive bacteria and have an inner charge transfer element that favors electron transfer and improves the electrochemical activity of microorganisms. The crucial step is to fine-tune the continuous porosity inside the anode electrode, thus enhancing the bacterial growth, adhesion, and proliferation, and the substrate’s transport and waste products removal, avoiding pore clogging. To this purpose, a novel approach to synthetize a 3D composite aerogel is proposed in the present work. A 3D composite aerogel, based on polydimethylsiloxane (PDMS) and multi-wall carbon nanotubes (MWCNTs) as a conductive filler, was obtained by pouring this mixture over the commercial sugar, used as removable template to induce and tune the hierarchical continuous porosity into final nanostructures. In this scenario, the granularity of the sugar directly affects the porosities distribution inside the 3D composite aerogel, as confirmed by the morphological characterizations implemented. We demonstrated the capability to realize a high-performance bioelectrode, which showed a 3D porous structure characterized by a high surface area typical of aerogel materials, the required biocompatibility for bacterial proliferations, and an improved electron pathway inside it. Indeed, SCMFCs with 3D composite aerogel achieved current densities of (691.7 ± 9.5) mA m−2, three orders of magnitude higher than commercial carbon paper, (287.8 ± 16.1) mA m−2.
Nanoporous Carbon Produced by Ball Milling

A nanoporous structure was produced in the samples of graphite after ball milling at ambient temperature. The specific internal surface area of the micropores, as determined using the t-plot method, is higher than the external surface area of particles and mesopores. Phase transformations from hexagonal to turbostratic, and to amorphous structures were investigated using x-ray diffraction analysis and transmission electron microscopy. Formation of the nanoporous structure is associated with that of the disordered carbon. The disordered and nanoporous structure is probably fullerene-like in nature.
Molecular Phylogenetics of the Orchid Genus Spathoglottis (Orchidaceae: Collabieae) in Peninsular Malaysia and Borneo

Phylogenetic relationships of the orchid genus Spathoglottis (Orchidaceae: Collabieae) in Peninsular Malaysia and Borneo were inferred using the internal transcribed spacer of a nuclear ribosomal DNA (nrITS), a plastid gene maturaseK (matK) and the plastid region trnL-F. Eleven species and three infraspecific taxa of Spathoglottis were examined, with two outgroup species, were included in the phylogenetic analysis. The combined plastid and nuclear data revealed Spathoglottis as monophyletic. From the maximum likelihood, maximum parsimony and Bayesian analyses, Spathoglottis is divided into four major groups which are, (1) the Dwarf Purple Spathoglottis, (2) the Dwarf Yellow Spathoglottis, (3) the Large Purple Spathoglottis, and (4) the Large Yellow Spathoglottis. The split in the Dwarf and Large Spathoglottis groups might reflect an early differentiation of plant size, flower colours and flower size. Phylogeny reconstruction of the orchid genus Spathoglottis also exhibited strong support towards the taxonomic delimitation of the two mostly debated taxa in the genus, S. aurea and S. microchilina.
Testing for spurious regression in a panel data model with the individual number and time length growing

Abstract This article shows a test for the spurious regression problem in a panel data model with a growing individual number and time series length. In the estimation, tapers are used and the integrated order for the remainder disturbance is extended to a real number; at the same time, the spurious regression problem can be detected without prior knowledge. Through Monte Carlo experiments, we examine the consistent estimators by various sizes of time length and individual number, in which the remainder disturbance is assumed to be either stationary or non-stationary. In addition, the asymptotic normality properties are discussed with a quasi log-likelihood function. From the power tests we can see that the estimators are quite successful and powerful.