Miracle-dz/UniFAR-FTUs huggingface dataset:
Plastic Recovery and Utilization: From Ocean Pollution to Green Economy

Due to their numerous merits (such as high durability, diverse applicability, ready-availability, low-cost, reusability, and so on), the presumably inevitable use of plastics makes their waste ubiquitously dispersed in our environment, especially in the oceans. The environmental damage posed, especially to the ecosystem, initiated the need for recourse control of these environmentally refractory pollutants. In this review, the various sources, classifications, fate, and control measures of plastic wastes were appraised. Further, of the three primary techniques for resource control, pyrolysis was reviewed in-depth, showing its relevance and superiority over others. Specific case studies showed that liquid and gaseous fuels derived from pyrolyzed plastics are a waste-to-wealth system that requires optimization and intensification. Such an approach would further help rid our planet of the numerous plastic wastes while improving our economy and achieving our energy demand. One approach identified to improve the current pyrolysis technology is catalysis. Further research should devise green methods for organic catalysis, which are environmentally benign.
Positive Psychological Coaching Tools and Techniques: A Systematic Review and Classification

Positive psychological coaching (PPC) has emerged as a popular “paradigm” for practitioners interested in the professional development of people. A recent review consolidated the literature on PPC and produced a 5-phase positive psychological coaching model aimed at facilitating professional growth. However, little is known about practically operationalizing each phase of the coaching process (i.e., how to facilitate each phase and which underlying tools and techniques could be employed to do so). As such, the purpose of this systematic review was to address this limitation by (a) determining which coaching tools and techniques are proposed within the coaching literature and (b) classifying the identified tools and techniques into the respective phases of PPC model. The investigation used a two-step approach by conducting a systematic literature review (to identify various PPC tools/techniques) followed by an iterative heuristic classification process (to assign these PPC tools/techniques to a known PPC model). The systematic literature review resulted in 24 peer-reviewed publications on positive psychological coaching, providing 117 different coaching tools that could be condensed into 18 overarching coaching techniques. The iterative classification process showed that most techniques and tools are useful in at least two phases. Interestingly, experts still vary in opinion on the timing and application of these specific techniques and tools within the positive psychological coaching process. This study provides researchers and practitioners with practical guidelines to facilitate a positive psychological coaching process.
Anthropometric Indicators as a Tool for Diagnosis of Obesity and Other Health Risk Factors: A Literature Review

Obesity is characterized by the accumulation of an excessive amount of fat mass (FM) in the adipose tissue, subcutaneous, or inside certain organs. The risk does not lie so much in the amount of fat accumulated as in its distribution. Abdominal obesity (central or visceral) is an important risk factor for cardiovascular diseases, diabetes, and cancer, having an important role in the so-called metabolic syndrome. Therefore, it is necessary to prevent, detect, and appropriately treat obesity. The diagnosis is based on anthropometric indices that have been associated with adiposity and its distribution. Indices themselves, or a combination of some of them, conform to a big picture with different values to establish risk. Anthropometric indices can be used for risk identification, intervention, or impact evaluation on nutritional status or health; therefore, they will be called anthropometric health indicators (AHIs). We have found 17 AHIs that can be obtained or estimated from 3D human shapes, being a noninvasive alternative compared to X-ray-based systems, and more accessible than high-cost equipment. A literature review has been conducted to analyze the following information for each indicator: definition; main calculation or obtaining methods used; health aspects associated with the indicator (among others, obesity, metabolic syndrome, or diabetes); criteria to classify the population by means of percentiles or cutoff points, and based on variables such as sex, age, ethnicity, or geographic area, and limitations.
Additive Value of Dynamic FDOPA PET/CT for Glioma Grading

Purpose: The aim of this study was to assess the value of the FDOPA PET kinetic parameters extracted using full kinetic analysis for tumor grading with neuronavigation-guided biopsies as reference in patients with newly-diagnosed gliomas. Methods: Fourteen patients with untreated gliomas were investigated. Twenty minutes of dynamic positron-emission tomography (PET) imaging and a 20-min static image 10 min after injection were reconstructed from a 40-min list-mode acquisition immediately after FDOPA injection. Tumors volume-of-interest (VOI) were generated based on the MRI-guided brain biopsies. Static parameters (TBRmax and TBRmean) and kinetic parameters [K1 and k2 using full kinetic analysis with the reversible single-tissue compartment model with blood volume parameter and the time-to-peak (TTP)] were extracted. Performances of each parameter for differentiating low-grade gliomas (LGG) from high-grade gliomas (HGG) were evaluated by receiver-operating characteristic analyses (area under the curve; AUC). Results: Thirty-two tumoral VOI were analyzed. K1, k2, and TTP were significantly higher for HGG than for LGG (median K1-value = 0.124 vs. 0.074 ml/ccm/min, p = 0.025, median k2-value = 0.093 vs. 0.063 min−1, p = 0.025, and median TTP-value = 10.0 vs. 15.0 min, p = 0.025). No significant difference was observed for the static parameters. The AUC for the kinetic parameters was higher than the AUC for the static parameters (respectively, AUCK1 = 0.787, AUCk2 = 0.785, AUCTTP = 0.775, AUCTBRmax = 0.551, AUCTBRmean = 0.575), significantly compared to TBRmax (respectively, p = 0.001 for K1, p = 0.031 for k2, and p = 0.029 for TTP). Conclusion: The present study suggests an additive value of FDOPA PET/CT kinetic parameters for newly-diagnosed gliomas grading.
Motives for Dropout Among Former Junior Elite Caribbean Track and Field Athletes: A Qualitative Investigation

Anecdotal reports within the Caribbean track and field fraternity have revealed that there is a high level of athlete dropout from competitive sport at the junior-elite level, and a poor transition to senior-elite status. Consequently, this qualitative investigation explored the key motives that may have contributed toward the unsuccessful transitions and ensuing dropout of Caribbean track and field athletes during the junior to senior transition period. Eleven former junior-elite track and field athletes (four males, seven females; Mage = 29, SD ± 4.2 years) from four English-speaking Caribbean islands participated in semi-structured interviews. Following an inductive and deductive thematic analysis, four higher order themes were identified: (1) “there's not enough support”; (2) “felt pressure to make sure I committed”; (3) “it's always competitive here”; and (4) “battle with the injuries. ” For these former junior-elite Caribbean athletes, the decision on whether to continue within the sport was influenced by a combination of factors, although inadequate financial and organizational support had the most bearing on athletes' decision to drop out during the crucial transition years. Implications for consideration by key stakeholders and policymakers within the region are discussed.
Coupling Parameters for Modeling the Near-Field Heat Transfer Between Molecules

The behavior of near-field heat transfer between molecules at gaps which are small compared to wavelength of light is greatly influenced by non-radiative dipole-dipole interactions between the molecules. Here we derive the coupling parameters and estimate the near-field heat transfer between two molecules using coupled Drude oscillators. The predictions from this model are verified with results from standard fluctuational electrodynamics principles. The effect of orientation factor of the dipole moments in the molecules traditionally taken into consideration for analysis of resonance energy transfer between molecules but hitherto overlooked for near-field heat transfer is also discussed.
The Instability of Dimeric Fc-Fusions Expressed in Plants Can Be Solved by Monomeric Fc Technology

The potential therapeutic value of many proteins is ultimately limited by their rapid in vivo clearance. One strategy to limit clearance by metabolism and excretion, and improving the stability of therapeutic proteins, is their fusion to the immunoglobulin fragment crystallizable region (Fc). The Fc region plays multiple roles in (i) dimerization for the formation of “Y”-shaped structure of Ig, (ii) Fc-mediated effector functions, (iii) extension of serum half-life, and (iv) a cost-effective purification tag. Plants and in particular Nicotiana benthamiana have proven to be suitable expression platforms for several recombinant therapeutic proteins. Despite the enormous success of their use for the production of full-length monoclonal antibodies, the expression of Fc-fused therapeutic proteins in plants has shown limitations. Many Fc-fusion proteins expressed in plants show different degrees of instability resulting in high amounts of Fc-derived degradation products. To address this issue, we used erythropoietin (EPO) as a reporter protein and evaluated the efforts to enhance the expression of full-length EPO-Fc targeted to the apoplast of N. benthamiana. Our results show that the instability of the fusion protein is independent from the Fc origin or IgG subclass and from the peptide sequence used to link the two domains. We also show that a similar instability occurs upon the expression of individual heavy chains of monoclonal antibodies and ScFv-Fc that mimic the “Y”-shape of antibodies but lack the light chain. We propose that in this configuration, steric hindrance between the protein domains leads to physical instability. Indeed, mutations of critical residues located on the Fc dimerization interface allowed the expression of fully stable EPO monomeric Fc-fusion proteins. We discuss the limitations of Fc-fusion technology in N. benthamiana transient expression systems and suggest strategies to optimize the Fc-based scaffolds on their folding and aggregation resistance in order to improve the stability.
A Composite Lactide-Mineral 3D-Printed Scaffold for Bone Repair and Regeneration

Orthopedic tumor resection, trauma, or degenerative disease surgeries can result in large bone defects and often require bone grafting. However, standard autologous bone grafting has been associated with donor site morbidity and/or limited quantity. As an alternate, allografts with or without metallic or polyether-etherketone have been used as grafting substitutes. However, these may have drawbacks as well, including stress shielding, pseudarthrosis, disease-transmission, and infection. There is therefore a need for alternative bone substitutes, such as the use of mechanically compliant three-dimensional (3D)-printed scaffolds. Several off-the-shelf materials are available for low-cost fused deposition 3D printing such as polylactic acid (PLA) and polycaprolactone (PCL). We have previously described the feasibility of 3D-printed PLA scaffolds to support cell activity and extracellular matrix deposition. In this study, we investigate two medical-grade filaments consistent with specifications found in American Society for Testing and Materials (ASTM) standard for semi-crystalline polylactide polymers for surgical implants, a pure polymer (100M) and a copolymeric material (7415) for their cytocompatibility and suitability in bone tissue engineering. Moreover, we assessed the impact on osteo-inductive properties with the addition of beta-tricalcium phosphate (β-TCP) minerals and assessed their mechanical properties. 100M and 7415 scaffolds with the additive β-TCP demonstrated superior mesenchymal stem cells (MSCs) differentiation detected via increased alkaline phosphatase activity (6-fold and 1.5-fold, respectively) and mineralized matrix deposition (14-fold and 5-fold, respectively) in vitro. Furthermore, we evaluated in vivo compatibility, biosafety and bone repair potential in a rat femur window defect model. 100M+β-TCP implants displayed a positive biosafety profile and showed significantly enhanced new bone formation compared to 100M implants evidenced by μCT (39 versus 25% bone volume/tissue volume ratio) and histological analysis 6 weeks post-implantation. These scaffolds are encouraging composite biomaterials for repairing bone applications with a great potential for clinical translation. Further analyses are required with appropriate evaluation in a larger critical-sized defect animal model with long-term follow-up.
A Novel Paradigm to Design Personalized Derived Images of Art Paintings Using an Intelligent Emotional Analysis Model

With the development of artificial intelligence (AI), it is imperative to combine design methods with new technologies. From the perspective of the personalized design of derived images of art paintings, this study analyzes the new user demand generated by the current situation and background of personalized design, puts forward a new method of derivative design based on AI emotion analysis, verifies the feasibility of the new method by constructing a personalized design system of derived images of art paintings driven by facial emotion features, and explores the method of combining AI emotion recognition, emotion analysis, and personalized design. This study provides new ideas for the design of art derivatives for the future with massive personalized demand. Thinking and practicing from the perspective of the development of new technology will promote the change of design paradigms in the digital age.
The Perils of Misspecified Priors and Optional Stopping in Multi-Armed Bandits

The connection between optimal stopping times of American Options and multi-armed bandits is the subject of active research. This article investigates the effects of optional stopping in a particular class of multi-armed bandit experiments, which randomly allocates observations to arms proportional to the Bayesian posterior probability that each arm is optimal (Thompson sampling). The interplay between optional stopping and prior mismatch is examined. We propose a novel partitioning of regret into peri/post testing. We further show a strong dependence of the parameters of interest on the assumed prior probability density.
Treatment of Intracranial Aneurysms Using the New Silk Vista Flow Diverter: Safety Outcomes at Short-Term Follow-Up

Background: Flow diverters are widely used as the first endovascular treatment option for complex brain aneurysms due to their high percentage of occlusion and low morbi-mortality. The Silk Vista device is a new generation of flow diverters designed to facilitate full visibility, improve apposition to the vessel wall, and enhance navigability. Indeed, its greatest advantage is that it enables the easier navigation of stents between 3.5 and 4.75 mm through a 0.021 microcatheter. The objective of this study was to evaluate the safety and effectiveness of Silk Vista systems for treating cerebral aneurysms. Methods: This prospective observational study included 25 consecutive patients with 27 wide-necked unruptured aneurysms treated with SILK Vista who were retrospectively analyzed for safety and efficacy. Results: Endovascular treatment was successfully performed in all patients. The final morbidity and mortality rates were both 0.0%. Short-term (3–5 months) angiographic follow-up revealed 21 complete occlusions and 6 near-complete occlusions. No significant parent artery stenosis was observed. Conclusions: This report demonstrates the efficacy of Silk Vista in treating brain aneurysms, although longer experiences should be carried out to confirm our results.
A Deep Learning Algorithm to Predict Hazardous Drinkers and the Severity of Alcohol-Related Problems Using K-NHANES

Purpose: The number of patients with alcohol-related problems is steadily increasing. A large-scale survey of alcohol-related problems has been conducted. However, studies that predict hazardous drinkers and identify which factors contribute to the prediction are limited. Thus, the purpose of this study was to predict hazardous drinkers and the severity of alcohol-related problems of patients using a deep learning algorithm based on a large-scale survey data. Materials and Methods: Datasets of National Health and Nutrition Examination Survey of South Korea (K-NHANES), a nationally representative survey for the entire South Korean population, were used to train deep learning and conventional machine learning algorithms. Datasets from 69,187 and 45,672 participants were used to predict hazardous drinkers and the severity of alcohol-related problems, respectively. Based on the degree of contribution of each variable to deep learning, it was possible to determine which variable contributed significantly to the prediction of hazardous drinkers. Results: Deep learning showed the higher performance than conventional machine learning algorithms. It predicted hazardous drinkers with an AUC (Area under the receiver operating characteristic curve) of 0.870 (Logistic regression: 0.858, Linear SVM: 0.849, Random forest classifier: 0.810, K-nearest neighbors: 0.740). Among 325 variables for predicting hazardous drinkers, energy intake was a factor showing the greatest contribution to the prediction, followed by carbohydrate intake. Participants were classified into Zone I, Zone II, Zone III, and Zone IV based on the degree of alcohol-related problems, showing AUCs of 0.881, 0.774, 0.853, and 0.879, respectively. Conclusion: Hazardous drinking groups could be effectively predicted and individuals could be classified according to the degree of alcohol-related problems using a deep learning algorithm. This algorithm could be used to screen people who need treatment for alcohol-related problems among the general population or hospital visitors.
Highly Dynamic Alloying and Dealloying in the Model System Gold–Silicon (AuSi)

Technological progress largely depends on innovative alloys; however, new discoveries are often hampered by a lack of knowledge concerning potential dynamics of alloying processes. Here we introduce an enabling tool for structured investigations on fast reactions between alloying constituents. The technique is based on laser-induced periodic surface structures (LIPSS), a phenomenon universally suited for the realization of massive heating and cooling rates in systems to be analyzed. Exemplified on the model system AuSi, LIPSS is demonstrated to induce alloying processes between Au and Si in submicron spatial confinements and with nanosecond temporal resolution. The light-triggered process causes Au migration through silicon at rates in the order of meters per second. Quenched intermediate states provide insights into the structure of premature AuSi alloys as well as reactions in this system unknown so far, such as the photothermal dealloying of gold from silicon.
Morphological, Structural, and Functional Networks Highlight the Role of the Cortical-Subcortical Circuit in Individuals With Subjective Cognitive Decline

Subjective cognitive decline (SCD) is considered the earliest stage of the clinical manifestations of the continuous progression of Alzheimer’s Disease (AD). Previous studies have suggested that multimodal brain networks play an important role in the early diagnosis and mechanisms underlying SCD. However, most of the previous studies focused on a single modality, and lacked correlation analysis between different modal biomarkers and brain regions. In order to further explore the specific characteristic of the multimodal brain networks in the stage of SCD, 22 individuals with SCD and 20 matched healthy controls (HCs) were recruited in the present study. We constructed the individual morphological, structural and functional brain networks based on 3D-T1 structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rs-fMRI), respectively. A t-test was used to select the connections with significant difference, and a multi-kernel support vector machine (MK-SVM) was applied to combine the selected multimodal connections to distinguish SCD from HCs. Moreover, we further identified the consensus connections of brain networks as the most discriminative features to explore the pathological mechanisms and potential biomarkers associated with SCD. Our results shown that the combination of three modal connections using MK-SVM achieved the best classification performance, with an accuracy of 92.68%, sensitivity of 95.00%, and specificity of 90.48%. Furthermore, the consensus connections and hub nodes based on the morphological, structural, and functional networks identified in our study exhibited abnormal cortical-subcortical connections in individuals with SCD. In addition, the functional networks presented more discriminative connections and hubs in the cortical-subcortical regions, and were found to perform better in distinguishing SCD from HCs. Therefore, our findings highlight the role of the cortical-subcortical circuit in individuals with SCD from the perspective of a multimodal brain network, providing potential biomarkers for the diagnosis and prediction of the preclinical stage of AD.
DELLA-NAC Interactions Mediate GA Signaling to Promote Secondary Cell Wall Formation in Cotton Stem

Gibberellins (GAs) promote secondary cell wall (SCW) development in plants, but the underlying molecular mechanism is still to be elucidated. Here, we employed a new system, the first internode of cotton, and the virus-induced gene silencing method to address this problem. We found that knocking down major DELLA genes via VIGS phenocopied GA treatment and significantly enhanced SCW formation in the xylem and phloem of cotton stems. Cotton DELLA proteins were found to interact with a wide range of SCW-related NAC proteins, and virus-induced gene silencing of these NAC genes inhibited SCW development with downregulated biosynthesis and deposition of lignin. The findings indicated a framework for the GA regulation of SCW formation; that is, the interactions between DELLA and NAC proteins mediated GA signaling to regulate SCW formation in cotton stems.