Miracle-dz/UniFAR-FTUs huggingface dataset:
Polysaccharide-Based Nanogels to Overcome Mucus, Skin, Cornea, and Blood-Brain Barriers: A Review

Nanocarriers have been extensively developed in the biomedical field to enhance the treatment of various diseases. However, to effectively deliver therapeutic agents to desired target tissues and enhance their pharmacological activity, these nanocarriers must overcome biological barriers, such as mucus gel, skin, cornea, and blood-brain barriers. Polysaccharides possess qualities such as excellent biocompatibility, biodegradability, unique biological properties, and good accessibility, making them ideal materials for constructing drug delivery carriers. Nanogels, as a novel drug delivery platform, consist of three-dimensional polymer networks at the nanoscale, offering a promising strategy for encapsulating different pharmaceutical agents, prolonging retention time, and enhancing penetration. These attractive properties offer great potential for the utilization of polysaccharide-based nanogels as drug delivery systems to overcome biological barriers. Hence, this review discusses the properties of various barriers and the associated constraints, followed by summarizing the most recent development of polysaccharide-based nanogels in drug delivery to overcome biological barriers. It is expected to provide inspiration and motivation for better design and development of polysaccharide-based drug delivery systems to enhance bioavailability and efficacy while minimizing side effects.
INTERNET GAMING DISORDER AND PROBLEMATIC INTERNET USE: THE LINKS BETWEEN CYBERBULLYING, AGGRESSION, LONELINESS AND PSYCHIATRIC COMORBIDITIES.

AIMS To compare adolescents clinically diagnosed with Internet Gaming Disorder (IGD) and problematic internet use (PIU) in terms of cyberbullying, aggression, and loneliness. METHODS Male adolescent patients (N=124, 14.3±1.7 years) with Internet Addiction Scale (IAS) scores ≥50 were clinically interviewed for IGD in utilizing DSM-5 criteria. Patients without full IGD criteria were included as PIU comparisons. Clinical variables were assessed using the second version of the Revised Cyber Bullying Inventory, short-form of the UCLA Loneliness Scale, Buss Perry Aggression Questionnaire, Child Depression Inventory, and Screen for Child Anxiety Related Emotional Disorders. RESULTS Compared to individuals with PIU, those with IGD were significantly more likely to have attention-deficit hyperactivity disorder, higher social phobia scores, higher cyberbullying scores, higher loneliness scores, been a cyberbully, and been a cyberbully victim. CONCLUSION Male adolescents with IGD have higher rates of psychiatric comorbidity, perceived loneliness, cyberbullying, and being a victim of cyberbullying than those with PIU. Future studies could evaluate these predictors of transition from PIU to IGD in large cohort samples.
Energy-Efficient STAR-RIS-aided MU-MIMO System for Next-Generation Green URLLC

This paper investigates a novel simultaneous transmission and reflection reconfigurable intelligent surface (STAR-RIS) aided downlink (DL) ultra-reliable low-latency communications (URLLC) to deliver a green URLLC service for next-generation wireless networks. In particular, we focus on the problem of energy-efficient resource allocation design for a phase-shift coupled STAR-RIS-aided multi-user multiple-input-multiple output (MU-MIMO) system with optimal beamforming at the base-station (BS) and STAR-RIS under given requirements on the packet-error probability and latency. Owing to the non-convex and NP-hard nature of the formulated problem, we propose an alternating optimization framework which solves the problems of beamforming design at the BS and STAR-RIS independently in an iterative manner using pricing allocation and successive convex approximation approaches. Simulation results confirm that the STAR-RIS can significantly improve the energy efficiency by 30-40% when compared to conventional reflecting-only RIS while guaranteeing the strict reliability and latency requirements of URLLC.
Implementing Vision Transformer to Model Emotions Recognition from Facial Expressions

Emotions are essential to social interaction between interlocutors. It provides essential meaning to social interaction. It is important to recognise emotions along with verbal cues to fully understand the true meaning of a conversation in a social interaction setting. Several techniques can be applied to recognise emotions in the social interaction setting automatically. Emotions can be recognised and interpreted from the interlocutor's facial cues (e.g., facial expression recognition task) by using a sensor such as a camera. Recognising emotions from facial cues has several problems to be solved. This research aims to model robust emotion recognition from facial cues to recognise emotions (particularly from Asian people), as there is only limited research done in this area. This research aims to propose an emotion recognition model from facial cues by implementing Vision Transformers architecture. The dataset implemented in this research was explicitly performed by local (i.e., Indonesian) actors (The Indonesian Mixed Emotion Dataset - IMED). The results show that the proposed model can achieve the best testing accuracy of 100% with the best training loss of 0.0001, with 0.53 hours of training times for 50 epochs.
SAN ROSSORE (ITALY) FORESTRY TEST SITE: METHODOLOGY FOR CALIBRATION AND VALIDATION OF CHRIS-PROBA DATA

Following the general trend to better understand the directional reflection properties of a surface, we present some results from CHRIS-PROBA images acquired during last year over the San Rossore (Italy) forestry test site. Particular attention is devoted to the description of the adopted methodology for calibrating and validating CHRIS-PROBA data and for obtaining images of spectral reflectance taking into account the atmospheric effects. Anisotropy Factor are estimated from experimental data and they are used in conjunction of literature data to study the spectral behaviour of multiangle remotely sensed data.
Machine-Type Communications in mmWave Ultra-Dense Networks: Performance Analysis

To cope with the unprecedented ubiquity of smart applications, Machine-Type Communication (MTC), the cellular communication backbone of the Internet of Things (IoT), has become an inevitable choice. In this paper, we investigate the achievable performance of MTC in an Ultra-Dense Network (UDN). To fully utilize the available resources in 5G and beyond networks, we exploit the propagation characteristics and excess bandwidth of the Millimeter wave (mmWave) band. Using tools from stochastic geometry, we provide a mathematical framework to evaluate the achievable Signal-to-Interference plus Noise Ratio (SINR) per user and the average capacity per Small Cell (SC) while considering the severe Inter-Cell Interference (ICI) of UDNs and the blockage effect in mmWave. The accuracy of the formu-lated analytical expressions is verified through extensive Monte-Carlo simulations. The obtained results show the existence of an optimal Small Cell (SC) density that maximizes the utilization of the deployed SCs.
ENVIRONMENTAL MANAGEMENT IN GEOTHERMAL DEVELOPMENT: CASE HISTORY FROM COSTA RICA

The great biological diversity of Costa Rica represents one of its biggest resources, and it’s a focal point of the country’s policies of environmental protection. For this reason the country is recognized worldwide as a leader in protecting the environment. This characteristic constitutes an important challenge for developing the geothermal energy according to these policies, due to a great part of the recognized resources that are associated to areas with different degrees of environmental protection. This document discusses the different environmental aspects related to the geothermal resources at the Miravalles Geothermal Field and Las Pailas Geothermal field, how the environmental management has been carried out and the results of this management so far. As a conclusion the feasibility of the sustainable development of geothermal projects can be shown as a tool for protecting the environment, but also as a means to recover the environmental quality in areas that have been previously affected by the human activity.
Simultaneous super-resolution, tracking and mapping

This paper proposes a new visual SLAM technique that not only integrates 6DOF pose and dense structure but also simultaneously integrates the color information contained in the images over time. This involves developing an inverse model for creating a super-resolution map from many low resolution images. Contrary to classic super-resolution techniques, this is achieved here by taking into account full 3D translation and rotation within a dense localisation and mapping framework. This not only allows to take into account the full range of image deformations but also allows to propose a novel criteria for combining the low resolution images together based on the difference in resolution between different images in 6D space. Several results are given showing that this technique runs in real-time (30Hz) and is able to map large scale environments in high-resolution whilst simultaneously improving the accuracy and robustness of the tracking.
Evaluation of Information Retrieval Systems Using Structural Equation Modelling

The interpretation of the experimental data collected by testing systems across input datasets and model parameters is of strategic importance for system design and implementation. In particular, finding relationships between variables and detecting the latent variables affecting retrieval performance can provide designers, engineers and experimenters with useful if not necessary information about how a system is performing. This paper discusses the use of Structural Equation Modelling (SEM) in providing an in-depth explanation of evaluation results and an explanation of failures and successes of a system; in particular, we focus on the case of Information Retrieval.
Primary and secondary intrusions in double-diffusively stable vertical gradients

The purpose of this paper is to show that molecularly-driven double-diffusive intrusions can produce signiﬁcant lateral and vertical double-diffusive mixing even when the initial temperature and salinity are both stably stratiﬁed in the vertical. Assuming uniform density-compensated horizontal gradients and periodic disturbances, three-dimensional direct numerical simulations (DNS) for the fastest growing intrusion show that the latter equilibrates due to the generation of salt ﬁngers which reduce the driving buoyancy pressure gradient. The DNS also provided statistical data for a new parameterization of the salt ﬁnger ﬂuxes which includes the effects of shear and variable vertical gradients.Thisparameterizationmakesitfeasibletonumericallyinvestigatethesubharmonicinstabilities oftheequilibriumDNSsolution. Linearizedcalculationswithparameterizedsaltﬁngersshowthat theverticalandhorizontalwavelengthofthefastestgrowingsecondaryinstabilityareapproximately threeandfourteentimesthatoftheprimaryintrusion.Nonlinearsimulationsshowthattheequilibrium lateralandverticaldouble-diffusiveﬂuxesofthesecondarymodeareanorderofmagnitudelarger thanthoseoftheprimaryintrusion.Numericallydetermineddependencesoftheintrusionlateral velocityontheverticalwavelengtharecomparedtopreviousnumericalandexperimentalwork.
DAQM-Based Load Balancing Scheme for High Performance Computing Platforms

—This paper addresses the load balancing problem, which is one of the key issues in high-performance computing (HPC) platforms. A novel method, called decentralized active queue management (DAQM), is proposed to provide a fair task distribution in a heterogeneous computing environment for HPC platforms. An implementation of the DAQM is presented, which consists of an ON-OFF queue control and a utility maximization-based coordination scheme. The stability of the queue control scheme and the convergence of the algorithm for utility maximization have been assessed by rigorous analysis. To demonstrate the performance of the developed queueing control system, numerical simulations are carried out and the obtained results conﬁrm the efﬁciency and the viability of the developed scheme.
Behind the Canvas: A Human-AI Workflow for Tracing 19th-Century Photographers and Studio Backdrops

Painted backdrops in 19th-century photography can provide critical provenance clues that are of interest to historians, mu-seum professionals, and collectors. Yet, the absence of specialized tools leaves researchers to rely on labor-intensive manual methods. To address this challenge, we introduce BackTrace , a human-AI collaborative system that helps users discover and organize historical photographs sharing similar painted backdrops. Our system allows users to iteratively improve search results by providing feedback to the system, and subsequently create public “collections” that can aid in future research.
Edinburgh Research Explorer Over-and underestimation of motor ability after a stroke

We administered a discrepancy-based measure of anosognosia for hemiplegia (AHP) to a group of 42 right-brain-damaged (RBD) and left-brain-damaged (LBD) stroke patients with varying levels of functional motor ability. In addition to the expected (anosognosic) pattern of overestimation of motor function in some RBD patients, we found an equal and opposite underestimation in some others, both RBD and LBD. We also found that around a quarter of self-estimation error could be predicted directly from actual ability, such that patients with poorer motor function tended to overestimate, and vice versa. This pattern suggests that some misestimation is attributable simply to statistical regression. However, even after adjusting for this regression effect, levels of overestimation were significantly greater in RBD patients, while LBD patients were more likely to underestimate their motor ability.
Proximal Average Approximated Incremental Gradient Method for Composite Penalty Regularized Empirical Risk Minimization

Proximal average (PA) is an approximation technique proposed recently to handle non-smooth composite regularizer in empirical risk minimization problem. For nonsmooth composite regularizer, it is often difficult to directly derive the corresponding proximal update when solving with popular proximal update. While traditional approaches resort to complex splitting methods like ADMM, proximal average provides an alternative, featuring the tractability of implementation and theoretical analysis. Nevertheless, compared to SDCA-ADMM and SAG-ADMM which are examples of ADMM-based methods achieving faster convergence rate and low per-iteration complexity, existing PA-based approaches either converge slowly (e.g. PA-ASGD) or suffer from high per-iteration cost (e.g. PA-APG). In this paper, we therefore propose a new PA-based algorithm called PA-SAGA, which is optimal in both convergence rate and per-iteration cost, by incorporating into incremental gradient-based framework.
Risk Management and Employees Accident Minimization at Work Place

he purpose of this study was to examine the impact of risk management on T employees' accident minimization at the work place. Data were collected through the use of self-structured closed questionnaire. The research adopted a descriptive survey design. A total of 100 respondents were selected for the purpose of the study using the stratified sampling method. The Pearson Product Moment Correlation and Regression Analysis were used to test the hypotheses generated for the study at 0.05 alpha levels. Findings revealed that there is a relationship between frequency and each of the identified risk factors accessed. The findings further revealed that risk management has influence on employees' accident minimization at the workplace. It was also found that employees' training reduces employees' accident at the workplace. It is recommended that employer should assume their part to teach employees' about risk management, work related safety and wellbeing techniques at working environment. This will help them in enhancing work environment security and maintain a strategic distance from the expanding numbers in mischance at working environment.
Comparative studies on four calcified structures for age determination of roach Rutilus rutilus in Ulungur Lake,Xinjiang Uigur Autonomous Region,China

This paper deals with the interpretability and agreement of age readings from a suite of calcified structures(scales,lapilli,opercula and cleithra),and the consistency of age interpretations for roach Rutilus rutilus(Linnaeus,1758) from Ulungur Lake,in North Xinjiang Uigur Autonomous Region,China.Among these calcified structures,the largest ages observed on scales,opercula and the sectioned lapilli were 6+ years old,while 5+ years on the asteriscus,whole lapilli and cleithra.The sectioned lapillus was demonstrated as the best structure for ageing roach with the clearest annuli,the highest interpretability(94.0 %,n=306) and the highest agreement(95.1 %,n=288)between two times age readings by the same reader.The interpretability of scales and opercula reaches 92.0 %(n=287) and 90.8 %(n=87),respectively,and the agreement between two times age readings using the scales and opercula by the same reader reaches 87.5 %(n=264) and 86.1 %(n=79),respectively.There wound be achieve a better result if the scales and the opercula were used together in age determination for that the scales are fit for aging those individuals less than 4 years old and the opercula are suitable for aging those individuals 4 years old and above.The cleithrum had the lowest interpretability(78.2 %,n=87) and agreement between two times age readings(55.7 %,n=68) because in most cases,it was uninterpretable as there were no annuli or did not display a clear pattern of annuli on it.The interpretability of the whole lapilli and the ateriscus are 90.0 %(n=330) and 80.1 %(n=330),respectively.However,they are only suitable for age estimation of those individuals less than 4 years old because the annuli on those of the older individuals will become less distinct with age increase.
Costs and Benefits of Financial Regulation: Short-selling Bans and Transaction Taxes Costs and Benefits of Financial Regulation: Short-selling Bans and Transaction Taxes

Established at the initiative of the Swiss Bankers' Association, the Swiss Finance Institute is a private foundation funded by the Swiss banks and Swiss Stock Exchange. It merges 3 existing foundations: the International Center FAME, the Swiss Banking School and the Stiftung "Banking and Finance" in Zurich. With its university partners, the Swiss Finance Institute pursues the objective of forming a competence center in banking and finance commensurate to the importance of the Swiss financial center. It will be active in research, doctoral training and executive education while also proposing activities fostering interactions between academia and the industry. The Swiss Finance Institute supports and promotes promising research projects in selected subject areas. It develops its activity in complete symbiosis with the NCCR FinRisk. Science Foundation (SNSF). FinRisk constitutes an academic forum that fosters cutting-edge finance research, education of highly qualified finance specialists at the doctoral level and knowledge transfer between finance academics and practitioners. It is managed from the University of Zurich and includes various academic institutions from Geneva, Lausanne, Lugano, St.Gallen and Zurich. For more information see www.nccr-finrisk.ch. Abstract We quantify the effects of financial regulation in an equilibrium model with delegated portfolio management. Fund managers trade stocks and bonds in an order-driven market, subject to transaction taxes and constraints on short-selling and leverage. Results are obtained on the equilibrium properties of portfolio choice, trading activity, market quality and price dynamics under the different regulations. We find that these measures are neither as beneficial as some politicians believe nor as damaging as many practitioners fear.
University of Birmingham The need for supportive mental wellbeing interventions in bladder cancer patients

Objectives There is an increased awareness of the effect of a bladder cancer diagnosis and its treatments on the mental wellbeing of patients. However, few studies have evaluated the efficacy, feasibility and acceptability of interventions to improve this mental wellbeing. This systematic review is the first phase of the Medical Research Council Framework for developing complex interventions and provides an overview of the published mental wellbeing interventions that could be used to design an intervention specific for BC patients. Methods This review was conducted in accordance with the PRISMA guidelines in January 2019 and studies were identified by conducting searches for Medline, the Cochrane Central Register of Controlled Trials and Ovid Gateway. All included studies met the following criteria: mental wellbeing interventions of adults with medically confirmed diagnosis of any type of urological cancer, reported outcomes for specific HRQoL domains including psychological factors. The quality of evidence was assessed according to Down and Black 27-item checklist.
Sustainable financing of HIV/AIDS and the economic impact in Africa: Evidence from a dynamic life cycle horizon of Uganda

Although HIV/AIDS has been tamed medically into a chronic disease through advances in treatment drugs, the full economic costs of keeping people on treatment and implementing prevention measures are still not fully quantified and are still unfolding. This paper assesses the long-term economic impact of domestic and external sources of financing HIV responses using a dynamic computable general equilibrium model. Taking Uganda as a case study for analysis, our study shows that increasing government HIV funding facilitates higher GPD growth and lower government debt relative to the baseline. Earmarked taxes and foreign-aid are potential sources of fiscal space for HIV.
Dynamics of Soil Water and Salinity Under Subsurface Drainage of a Coastal Area With High Groundwater Table in Spring and Rainy Season

Timing subsurface drainage (SD) at two critical periods to coincide with melting of frozen soil water and the rainy season may effectively lower the groundwater table and increase the leaching of salts. A field experiment was set up in the eastern coastal saline area of Hebei Province, China, to assess the effects of SD on soil water and salinity. Subsurface drainage significantly prevented the rise of the groundwater table during melting of frozen soil water, and thus considerably reduced salinity across soil layers, especially in the 30 cm layer. In the rainy season, the SD effectively held the water depth to within 1 m, preventing waterlogging by more than two‐thirds and more than doubling the leaching of salts from the soil surface. The contents of Na+, Mg2+, Cl− and SO42− under SD reduced substantially (7.1–18.8%) after rainfall events and the mobility of ions was in the order Na+ > Cl− > SO42− > Mg2+. For the remaining period of the year when subsurface drainage was not carried out, the soil salinity generally increased but the salinity and groundwater table in areas under SD were slightly lower than those in the control area. Copyright © 2016 John Wiley & Sons, Ltd.
The effect of private investment in technology on economic structure

We investigate the effect of private investment in technology on economic structure. An export sophistication index - the Economic Complexity Index - is used as a proxy for economic structure. The use of economic complexity is due to it is an adequate measure of per capita income growth. A federal law fostering private investment in research and development is used as an instrument for investment in technology. Data are on investment in technology for Brazilian municipalities from 2002 to 2016. Results showed the federal law was effective and private investment in technology has a positive effect on economic structure. We concluded investment in technology should be promoted, especially by laws that incentives this kind of investment and aiming economic structure improvements. (JEL: O11; O32; F43)