Miracle-dz/UniFAR-FTUs huggingface dataset:
Adolescents Like Instagram! From Secret Dangers to an Educational Model by its Use Motives and Features: An Analysis of Their Mind Maps

This study investigates the adolescents’ perceptions toward Instagram as a social network site via their mind maps and tries to understand this social phenomenon that affect them by its use motives and features. It also offers a general profile of social network site use among adolescents. Data were collected from 540 adolescents majoring in high schools of Turkey. The participants created their mind maps on Instagram in the visual arts course. Qualitative data were resolved using thematic analysis. Results highlighted the popularity of Instagram among adolescents. According to their mental images on Instagram, we found four categories: “communication and interaction,” “knowledge acquisition,” “entertainment and sharing,” and “negative effects of Instagram. ” In addition to their positive perceptions toward Instagram, the majority of adolescents focused on the negative effects such as addiction, mood disorders, narcissistic acts, and ethics violations. Based on the findings, we also suggested a theoretical model for educational use of Instagram and directions for future research.
“Cell Phones Under the Table”: Meeting Students’ Needs to Reduce Off-Task Smartphone Use Through Faculty–Student Collaboration

While technology offers educators many affordances to provide students with rich educational experiences, literature and empirical experience indicates that students’ unstructured cell phone usage may have adverse impacts on student achievement and create a contagious climate of distraction. This research project seeks to understand students’ unstructured cell phone usage, faculty response, and foster improved student–faculty communication to determine concrete interventions to off-task smartphone usage. For the purposes of this study, we surveyed and interviewed faculty and undergraduate students at two small private universities in the United States. Findings suggest that students and faculty recognize the limitations of punitive cell phone policies and desire intervention. Giving students’ movement alternatives and offering faculty more training in using smartphones as educational tools may be acceptable solutions.
Lifeguard turnover in aquatic and recreation centres: Perspectives from managers

Employee turnover is the loss of talent in the workforce. High employee turnover is expensive and disruptive. Young employees are more likely to leave one job for a better one and are often less attached to an organisation while they are completing their education. The aquatics industry has been described as being in a crisis, experiencing unprecedented levels of turnover amongst lifeguards. A first important step is to understand the reasons for turnover amongst lifeguards. This study utilised semi-structured interviews with aquatic and recreation centre managers (N = 16; 69% female) to explore their insights about lifeguard turnover. A deductive content analysis determined that lifeguards leave their current position for four main reasons: lifeguarding being a temporary position, a negative working environment, pursuing employment in a higher paying lifeguard position and location. Consequently, centre managers need to consider short and long-term strategies to retain lifeguards.
Comparison of different SLAM approaches for a driverless race car

Abstract For the application of an automated, driverless race car, we aim to assure high map and localization quality for successful driving on previously unknown, narrow race tracks. To achieve this goal, it is essential to choose an algorithm that fulfills the requirements in terms of accuracy, computational resources and run time. We propose both a filter-based and a smoothing-based Simultaneous Localization and Mapping (SLAM) algorithm and evaluate them using real-world data collected by a Formula Student Driverless race car. The accuracy is measured by comparing the SLAM-generated map to a ground truth map which was acquired using high-precision Differential GPS (DGPS) measurements. The results of the evaluation show that both algorithms meet required time constraints thanks to a parallelized architecture, with GraphSLAM draining the computational resources much faster than Extended Kalman Filter (EKF) SLAM. However, the analysis of the maps generated by the algorithms shows that GraphSLAM outperforms EKF SLAM in terms of accuracy.
Knitted and screen printed carbon-fiber supercapacitors for applications in wearable electronics

The field of energy textiles is growing but continues to face two main challenges: (1) flexible energy storage does not yet exist in a form that is directly comparable with everyday fabrics including their feel, drape and thickness, and (2) in order to produce an “energy textile” as part of a garment, it must be fabricated in a systematic manner allowing for multiple components of e-textiles to be integrated simultaneously. To help address these issues, we have developed textile supercapacitors based on knitted carbon fibers and activated carbon ink. We show capacitances as high as 0.51 F cm−2 per device at 10 mV s−1, which is directly comparable with those of standard activated carbon film electrodes tested under the same conditions. We also demonstrate the performance of the device when bent at 90°, 135°, 180° and when stretched. This is the first report on knitting as a fabrication technique for integrated energy storage devices.
Work functions of binary compounds

A new semiempirical model for predicting the work function of binary compounds is proposed. The model is a modification of the Gordy and Thomas relation and is applicable to binary compounds. The work functions of binary compounds, φAB are found to be primarily determined by the properties of the element of low work function, A, perturbed by the other element of high work function, B, according to φAB=φA + (1.41/dA)[(2φA − φB − 0.34)/(φA + φB − 0.68)]. Experimental values tabulated by Fomenko are compared with the predicted work functions, and the quantitative agreement is good in spite of the simplicity of the model.A new semiempirical model for predicting the work function of binary compounds is proposed. The model is a modification of the Gordy and Thomas relation and is applicable to binary compounds. The work functions of binary compounds, φAB are found to be primarily determined by the properties of the element of low work function, A, perturbed by the other element of high work function, B, according to φAB=φA + (1.41/dA)[(2φA − φB − 0.34)/(φA + φB − 0.68)]. Experimental values tabulated by Fomenko are compared with the predicted work functions, and the quantitative agreement is good in spite of the simplicity of the model.
Nano-Neurotheranostics: Impact of Nanoparticles on Neural Dysfunctions and Strategies to Reduce Toxicity for Improved Efficacy

Nanotheranostics is one of the emerging research areas in the field of nanobiotechnology offering exciting promises for diagnosis, bio-separation, imaging mechanisms, hyperthermia, phototherapy, chemotherapy, drug delivery, gene delivery, among other uses. The major criteria for any nanotheranostic-materials is 1) to interact with proteins and cells without meddling with their basic activities, 2) to maintain their physical properties after surface modifications and 3) must be nontoxic. One of the challenging targets for nanotheranostics is the nervous system with major hindrances from the neurovascular units, the functional units of blood-brain barrier. As blood-brain barrier is crucial for protecting the CNS from toxins and metabolic fluctuations, most of the synthetic nanomaterials cannot pass through this barrier making it difficult for diagnosing or targeting the cells. Biodegradable nanoparticles show a promising role in this aspect. Certain neural pathologies have compromised barrier creating a path for most of the nanoparticles to enter into the cells. However, such carriers may pose a risk of side effects to non-neural tissues and their toxicity needs to be elucidated at preclinical levels. This article reviews about the different types of nanotheranostic strategies applied in nervous dysfunctions. Further, the side effects of these carriers are reviewed and appropriate methods to test the toxicity of such nano-carriers are suggested to improve the effectiveness of nano-carrier based diagnosis and treatments.
Systemic Review on Transcranial Electrical Stimulation Parameters and EEG/fNIRS Features for Brain Diseases

Background Brain disorders are gradually becoming the leading cause of death worldwide. However, the lack of knowledge of brain disease’s underlying mechanisms and ineffective neuropharmacological therapy have led to further exploration of optimal treatments and brain monitoring techniques. Objective This study aims to review the current state of brain disorders, which utilize transcranial electrical stimulation (tES) and daily usable noninvasive neuroimaging techniques. Furthermore, the second goal of this study is to highlight available gaps and provide a comprehensive guideline for further investigation. Method A systematic search was conducted of the PubMed and Web of Science databases from January 2000 to October 2020 using relevant keywords. Electroencephalography (EEG) and functional near-infrared spectroscopy were selected as noninvasive neuroimaging modalities. Nine brain disorders were investigated in this study, including Alzheimer’s disease, depression, autism spectrum disorder, attention-deficit hyperactivity disorder, epilepsy, Parkinson’s disease, stroke, schizophrenia, and traumatic brain injury. Results Sixty-seven studies (1,385 participants) were included for quantitative analysis. Most of the articles (82.6%) employed transcranial direct current stimulation as an intervention method with modulation parameters of 1 mA intensity (47.2%) for 16–20 min (69.0%) duration of stimulation in a single session (36.8%). The frontal cortex (46.4%) and the cerebral cortex (47.8%) were used as a neuroimaging modality, with the power spectrum (45.7%) commonly extracted as a quantitative EEG feature. Conclusion An appropriate stimulation protocol applying tES as a therapy could be an effective treatment for cognitive and neurological brain disorders. However, the optimal tES criteria have not been defined; they vary across persons and disease types. Therefore, future work needs to investigate a closed-loop tES with monitoring by neuroimaging techniques to achieve personalized therapy for brain disorders.
Metal Material, Properties and Design Methods of Porous Biomedical Scaffolds for Additive Manufacturing: A Review

Design an implant similar to the human bone is one of the critical problems in bone tissue engineering. Metal porous scaffolds have good prospects in bone tissue replacement due to their matching elastic modulus, better strength, and biocompatibility. However, traditional processing methods are challenging to fabricate scaffolds with a porous structure, limiting the development of porous scaffolds. With the advancement of additive manufacturing (AM) and computer-aided technologies, the development of porous metal scaffolds also ushers in unprecedented opportunities. In recent years, many new metal materials and innovative design methods are used to fabricate porous scaffolds with excellent mechanical properties and biocompatibility. This article reviews the research progress of porous metal scaffolds, and introduces the AM technologies used in porous metal scaffolds. Then the applications of different metal materials in bone scaffolds are summarized, and the advantages and limitations of various scaffold design methods are discussed. Finally, we look forward to the development prospects of AM in porous metal scaffolds.
Neural Autoantibodies in Cerebrospinal Fluid and Serum in Clinical High Risk for Psychosis, First-Episode Psychosis, and Healthy Volunteers

The pathophysiological role of neural autoantibodies in acute psychotic disorders is receiving increased attention. However, there is still an ongoing debate, whether predominantly psychotic manifestations of autoimmune encephalitides exist that may remain undetected and, thus, untreated. Furthermore, it is discussed if such conditions can be diagnosed based on serum antibody results or if a reliable diagnosis requires additional cerebrospinal fluids (CSF) results. In this study, we screened pairs of serum and CSF samples from antipsychotic-naïve individuals with first-episode schizophrenic psychosis (FEP, n = 103), clinical high risk for psychosis (CHR, n = 47), and healthy volunteers (HV, n = 40) for eight different antibodies against various antigens that have been shown to be associated with autoimmune encephalitides: N-methyl-D-aspartate receptor (NMDAR, NR1 subunits only), glutamic acid decarboxylase (GAD65), leucine-rich glioma inactivated protein 1 (LGI1), contactin-associated protein-like 2 protein (CASPR2), α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) subunit 1, AMPAR subunit 2, γ-aminobutyric acid-B receptors (GABABR), and glycine receptors. All patients were within the norm with regards to a careful neurological examination, a magnetic resonance imaging (MRI) of the brain, an electroencephalogram (EEG), and routine blood pathology. All CSF samples were autoantibody-negative. In three serum samples of individuals with FEP, we detected low-titer CASPR2 immunoglobulin (Ig) G antibodies (≤1:160, n = 2) and non-IgG antibodies against NMDAR (n = 1) (overall serum-autoantibody prevalence in FEP: 2.91%). However, the IgG titers were below the laboratory cut-off defined for positivity, and non-IgG antibodies are of no clinical relevance. This suggests that there were no cases of autoimmune encephalitis in our cohort. Our results highlight the importance and the high specificity of CSF analysis to reliably detect autoantibodies. They confirm the hypothesis that pure psychotic manifestations of antibody-associated autoimmune encephalitides without any additional neuropsychiatric findings are very rare. However, special attention must be paid to those presenting with atypical mental illnesses with additional neurological symptoms, evidence of clinically-significant cognitive involvement, profound sleep-wake perturbations, seizures, electroencephalographic, or magnetic resonance imaging pathologies to be able to identify cases with autoimmune-mediated psychiatric syndromes.
Glial Cell-Based Vascular Mechanisms and Transplantation Therapies in Brain Vessel and Neurodegenerative Diseases

Neurodevelopmental and neurodegenerative diseases (NDDs) with severe neurological/psychiatric symptoms, such as cerebrovascular pathology in AD, CAA, and chronic stroke, have brought greater attention with their incidence and prevalence having markedly increased over the past few years. Causes of the significant neuropathologies, especially those observed in neurological diseases in the CNS, are commonly believed to involve multiple factors such as an age, a total environment, genetics, and an immunity contributing to their progression, neuronal, and vascular injuries. We primarily focused on the studies of glial involvement/dysfunction in part with the blood-brain barrier (BBB) and the neurovascular unit (NVU) changes, and the vascular mechanisms, which have been both suggested as critical roles in chronic stroke and many other NDDs. It has been noted that glial cells including astrocytes (which outnumber other cell types in the CNS) essentially contribute more to the BBB integrity, extracellular homeostasis, neurotransmitter release, regulation of neurogenic niches in response to neuroinflammatory stimulus, and synaptic plasticity. In a recent study for NDDs utilizing cellular and molecular biology and genetic and pharmacological tools, the role of reactive astrocytes (RACs) and gliosis was demonstrated, able to trigger pathophysiological/psychopathological detrimental changes during the disease progression. We speculate, in particular, the BBB, the NVU, and changes of the astrocytes (potentially different populations from the RACs) not only interfere with neuronal development and synaptogenesis, but also generate oxidative damages, contribute to beta-amyloid clearances and disrupted vasculature, as well as lead to neuroinflammatory disorders. During the past several decades, stem cell therapy has been investigated with a research focus to target related neuro-/vascular pathologies (cell replacement and repair) and neurological/psychiatric symptoms (paracrine protection and homeostasis). Evidence shows that transplantation of neurogenic or vasculogenic cells could be achieved to pursue differentiation and maturation within the diseased brains as expected. It would be hoped that, via regulating functions of astrocytes, astrocytic involvement, and modulation of the BBB, the NVU and astrocytes should be among major targets for therapeutics against NDDs pathogenesis by drug and cell-based therapies. The non-invasive strategies in combination with stem cell transplantation such as the well-tested intranasal deliveries for drug and stem cells by our and many other groups show great translational potentials in NDDs. Neuroimaging and clinically relevant analyzing tools need to be evaluated in various NDDs brains.
New insights into the qualitative phenolic profile of Ficus carica L. fruits and leaves from Tunisia using ultra-high-performance liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry and their antioxidant activity

Ficus carica L. fruits have been consumed from the earliest times, and other parts of the tree have been used for traditional medicinal purposes. Nowadays, the beneficial properties of this and other Ficus species are attributed to the presence of key phytochemicals. To increase our knowledge about this topic, the present study has conducted phenolic profiling of the leaves and whole fruits from two Tunisian cultivars, ‘Temri’ and ‘Tounsi’, using reversed-phase ultra-high-performance liquid chromatography (RP-UHPLC) coupled to two detection systems: diode-array detection (DAD) and quadrupole time-of-flight (QTOF) mass spectrometry (MS). UV-Vis absorption was a valuable tool for classifying phenolic compounds into families, while MS using electrospray ionization (ESI) and MS/MS allowed the molecular formula to be established and structural information to be obtained. The total phenol content and the antioxidant activity were also assessed. As a result, in the negative ionization mode 91 phenolic compounds were characterized including hydroxybenzoic acids, hydroxycinnamic acids, hydroxycoumarins and flavanoids (flavonols, flavones, flavanones, flavanonols, flavanols and isoflavones). This work was complemented by the detection of other 18 phenolic compounds in the positive ionization mode, including anthocyanins and furanocoumarins. To the best of our knowledge, this is the first time most of these compounds have been tentatively reported in F. carica. These results indicate the complexity of this family of secondary metabolites in F. carica, as well as the potential of this analytical method for characterization purposes. In conclusion, the qualitative phenolic profile, total phenolic content and antioxidant activity differed especially between leaves and fruits.
Pediatric Challenges in Robot-Assisted Kidney Transplantation

Kidney transplantation is universally recognized as the gold standard treatment in patients with End-stage Kidney Disease (ESKD, or according to the latest nomenclature, CKD stage 5). Robot-assisted kidney transplantation (RAKT) is gradually becoming preferred technique in adults, even if applied in very few centra, with potentially improved clinical outcomes compared with open kidney transplantation. To date, only very few RAKT procedures in children have been described. Kidney transplant recipient patients, being immunocompromised, might be at increased risk for perioperative surgical complications, which creates additional challenges in management. Applying techniques of minimally invasive surgery may contribute to the improvement of clinical outcomes for the pediatric transplant patients population and help mitigate the morbidity of KT. However, many challenges remain ahead. Minimally invasive surgery has been consistently shown to produce improved clinical outcomes as compared to open surgery equivalents. Robot-assisted laparoscopic surgery (RALS) has been able to overcome many restrictions of classical laparoscopy, particularly in complex and demanding surgical procedures. Despite the presence of these improvements, many challenges lie ahead in the surgical and technical–material realms, in addition to anesthetic and economic considerations. RALS in children poses additional challenges to both the surgical and anesthesiology team, due to specific characteristics such as a small abdominal cavity and a reduced circulating blood volume. Cost-effectiveness, esthetic and functional wound outcomes, minimal age and weight to undergo RALS and effect of RAKT on graft function are discussed. Although data on RAKT in children is scarce, it is a safe and feasible procedure and results in excellent graft function. It should only be performed by a RAKT team experienced in both RALS and transplantation surgery, fully supported by a pediatric nephrology and anesthesiology team. Further research is necessary to better determine the value of the robotic approach as compared to the laparoscopic and open approach. Cost-effectiveness will remain an important subject of debate and is in need of further evaluation as well.
Machine Learning-Based Ultrasomics Improves the Diagnostic Performance in Differentiating Focal Nodular Hyperplasia and Atypical Hepatocellular Carcinoma

Background The typical enhancement patterns of hepatocellular carcinoma (HCC) on contrast-enhanced ultrasound (CEUS) are hyper-enhanced in the arterial phase and washed out during the portal venous and late phases. However, atypical variations make a differential diagnosis both challenging and crucial. We aimed to investigate whether machine learning-based ultrasonic signatures derived from CEUS images could improve the diagnostic performance in differentiating focal nodular hyperplasia (FNH) and atypical hepatocellular carcinoma (aHCC). Patients and Methods A total of 226 focal liver lesions, including 107 aHCC and 119 FNH lesions, examined by CEUS were reviewed retrospectively. For machine learning-based ultrasomics, 3,132 features were extracted from the images of the baseline, arterial, and portal phases. An ultrasomics signature was generated by a machine learning model. The predictive model was constructed using the support vector machine method trained with the following groups: ultrasomics features, radiologist’s score, and combination of ultrasomics features and radiologist’s score. The diagnostic performance was explored using the area under the receiver operating characteristic curve (AUC). Results A total of 14 ultrasomics features were chosen to build an ultrasomics model, and they presented good performance in differentiating FNH and aHCC with an AUC of 0.86 (95% confidence interval [CI]: 0.80, 0.89), a sensitivity of 76.6% (95% CI: 67.5%, 84.3%), and a specificity of 80.5% (95% CI: 70.6%, 85.9%). The model trained with a combination of ultrasomics features and the radiologist’s score achieved a significantly higher AUC (0.93, 95% CI: 0.89, 0.96) than that trained with the radiologist’s score (AUC: 0.84, 95% CI: 0.79, 0.89, P < 0.001). For the sub-group of HCC with normal AFP value, the model trained with a combination of ultrasomics features, and the radiologist’s score remain achieved the highest AUC of 0.92 (95% CI: 0.87, 0.96) compared to that with the ultrasomics features (AUC: 0.86, 95% CI: 0.74, 0.89, P < 0.001) and radiologist’s score (AUC: 0.86, 95% CI: 0.79, 0.91, P < 0.001). Conclusions Machine learning-based ultrasomics performs as well as the staff radiologist in predicting the differential diagnosis of FNH and aHCC. Incorporating an ultrasomics signature into the radiologist’s score improves the diagnostic performance in differentiating FNH and aHCC.