Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards the Development of a Device for Assessing the Pliability of Burn Scars

Burn injuries requires post-accident medical treatment. However, the treatment of burns does not end with first aid because scarred skin must be managed for many years, and in some circumstances, for life. The methods used to evaluate the state of a burn scar based, for instance, on Patient and Observer Scar Assessment Scale or similar ones, often lacks in univocally assessing the scarred skin’s state of health. As a result, the primary aim of this research is to design and build a prototype that can support the doctor during scar assessment, and eventually therapy, by providing objective information on the state of the lesion, particularly the value of skin pliability. The developed tool is based on the depressomassage treatment probe named LPG, currently used to treat burn scars in a number of hospitals. It consists of a non-invasive massage technique using a mechanical device to suction and mobilize scar tissue and is used as a post-operative treatment to speed up the healing process to make the mark of the scar less visible. The prototype is specifically designed to be manufactured using Additive Manufacturing and was validated comparing its performances against the ones of a certified instrument (i.e., the Romer Absolute ARM with RS1 probe). Validation was carried out by designing and developing a tool to put the RS1 probe in the same measurement conditions of the new prototype probe. Tests performed to assess the performance of the devised prototype show that the probe developed in this work is able to provide measurements with a sufficient degree of accuracy (maximum error ±0.1 mm) to be adopted for a reliable estimation of the pliability value in a hospital environment.
Physics-Based Computational Approaches to Compute the Viscoelasticity of Semiflexible Filamentous Biomaterials

This mini-review highlights recent advances on computational approaches that have been used in the characterisation of the viscoelastic response of semiflexible filamentous biomaterials. Special attention is given to the multiscale and coarse-grained approaches that might be used to model the mechanical properties of systems which involve biopolymer assemblies, for instance, actin, collagen, vimentin, microtubules, DNA, viruses, silk, amyloid fibrils, and other protein-based filaments. Besides the basic features of the most commonly used models for semiflexible filaments, I present a brief overview of the numerical approaches that can be used to extract the viscoelasticity of dilute and concentrated solutions, as well as systems with cross-linked networks. Selected examples of simulations that attempt to retrieve the complex shear moduli at experimentally relevant time and length scales, i.e., including not only the fully formed filaments and networks but also their self-assembly kinetics, are also considered.
Development of Non-Uniform Radiation Solution Methods for Atmospheric Re-Entry Using Detailed Thermal Modeling

Abstract : The line-by-line accurate spectral radiation solver SPRADIAN was integrated with the multi-temperature hypersonic flow-solver NH7Air for the purpose of predicting the radiation incident on the surface of a hypersonic re-entry vehicle. Atomic and molecular radiation mechanisms are considered for chemical species present in an Earth atmosphere re-entry. A new numerical method of radiation propagation is presented that is capable of accurately predicting the radiation propagation through a non-uniform radiation field. This method also introduces a unique treatment of the internal energy of each chemical species, independently tracking the vibrational temperatures of all molecular species. The new radiation propagation method is validated against the industry standard tangent-slab method for a uniform radiating slab. Results are also presented for the 1636 second trajectory point of the NASA FIRE-II experiment. For the FIRE-II case, the results of the new method is compared to the results of the tangent-slab analysis, and with the values measured in the experiment.
ENSURE: A Deep Learning Approach for Enhancing Situational Awareness in Surveillance Applications With Ubiquitous High-Dimensional Sensing

Judicious processing of High-Dimensional Sensing (HDS) data streams is often the first step in a data-driven decision-support system. However, how one goes about processing large amounts of incoming HDS data streams for enhancing situational awareness (SA) is a non-trivial, and often challenging task due to the interwoven nature of operational environments, especially in complex surveillance applications (e.g., predictive policing, urban reconnaissance). Toward addressing this challenge, a novel data processing framework called ENSURE (ENhanced Situational Understanding with Ubiquitous-sensing REsources) is presented. In particular, by using density-based clustering in tandem with variable length sequence decoding methods, ubiquitous HDS data streams are clustered and then processed for early identification of ‘events’ and their sequences of interest to a (surveillance) task at hand. Then, by leveraging notions in data association, ENSURE ‘tracks’ the occurrence of such event sequences and their evolution over time to ‘perceive’ and ‘comprehend’ what’s happening in the operational environment. Therefore, ENSURE can be interpreted as an information fusion approach for HDS systems for object recognition, classification, tracking, and decision-making tasks. Use of ENSURE is illustrated via a simulated experiment to provide insights into its behavior, performance and sensitivity to parameters.
Significant Mobility of Novel Heteroaggregates of Montmorillonite Microparticles with Nanoscale Zerovalent Irons in Saturated Porous Media

This study conducted laboratory column experiments to systematically examine the transport of novel heteroaggregates of montmorillonite (Mt) microparticles with nanoscale zerovalent irons (nZVIs) in saturated sand at solution ionic strengths (ISs) ranging from 0.001 to 0.2 M. Spherical nZVIs were synthesized using the liquid phase reduction method and were attached on the plate-shaped Mt surfaces in monolayer. While complete deposition occurred for nZVIs in sand, significant transport was observed for Mt-nZVI heteroaggregates at IS ≤ 0.01 M despite the transport decrease with an increasing loading concentration of nZVIs on Mt. The increased mobility of Mt-nZVI heteroaggregates was because the attractions between nZVIs and sand collectors were reduced by the electrostatic repulsions between the Mt and the collector surfaces, which led to a decreased deposition in the sand columns. Complete deposition occurred for the Mt-nZVI heteroaggregates at IS ≥ 0.1 M due to a favorable deposition at Derjaguin–Landau–Verwey–Overbeek (DLVO) primary energy minima. Interestingly, a large fraction of the deposited heteroaggregates was released by reducing IS because of a monotonic decrease of interaction energy with separation distance for the heteroaggregates at low ISs (resulting in repulsive forces), in contrast to the irreversible deposition of nZVIs. Therefore, the fabricated heteroaggregates could also have high mobility in subsurfaces with saline pore water through continuous capture and release using multiple injections of water with low ISs. Our study was the first to examine the transport of heteroaggregates of a plate-like particle with spherical nanoparticles in porous media; the results have important implications in the use of nanoscale zerovalent iron for in situ soil and groundwater remediation.
Dynamic Event-Triggered Integral Sliding Mode Adaptive Optimal Tracking Control for Uncertain Nonlinear Systems

In this paper, we study the event-triggered integral sliding mode optimal tracking problem of nonlinear systems with matched and unmatched disturbances. The goal is to design an adaptive dynamic programming-based sliding-mode controller, which stabilizes the closed-loop system and guarantees the optimal performance of the sliding-mode dynamics. First, in order to remove the effects of the matched uncertainties, an event-triggered sliding mode controller is designed to force the state of the systems on the sliding mode surface without Zeno behavior. Second, another event-triggered controller is designed to suppress unmatched disturbances with a nearly optimal performance while also guaranteeing Zeno-free behavior. Finally, the benefits of the proposed algorithm are shown in comparison to several traditional triggering and learning-based mechanisms.
Gaz de bosons et de fermions condensés : phases de Fulde-Ferrell-Larkin-Ovchinnikov et quasicondensats

La premiere partie de cette these concerne les phases inhomogenes FFLO. Celles-ci peuvent apparaitre dans les supraconducteurs ou les gaz d'atomes froids fermioniques en presence d'une difference homogene de potentiels chimiques entre les deux etats de spin. Nous regardons la competition entre les differentes phases FFLO pres de la transition. A 2D, nous utilisons une approche de type Ginzburg-Landau pour predire une cascade de transitions entre des phases inhomogenes de plus en plus complexes. A 3D ou la transition FFLO est du premier ordre, nous presentons une methode numerique de resolution des equations quasiclassiques d'Eilenberger basee sur un developpement de Fourier. Nous determinons ainsi les phases inhomogenes de plus basse energie. Dans la seconde partie, nous etendons la theorie perturbative de Bogoliubov aux quasicondensats dans une representation densite-phase. Nous obtenons des predictions pour differentes observables.
Analysis of the Mechanism of Ground Fissures in the Nairobi–Malaba Railway Rift Valley Area in Kenya

During the rainy season from March to May 2018, four ground fissures were generated in the rift valley area along the first phase of the Nairobi–Malaba Railway in Kenya, among which the ground fissures B3 highway, DK76, and DK77 were larger in scale, which seriously endangered the safety of the railway. According to the author’s previous study, the ground fissure B3 highway belongs to a typical fault-type fissure, and the ground fissures DK76 and DK77 are qualitatively concluded to be generated under the groundwater erosion of collapsible soils. To quantitatively summarize the mechanism of ground fissures, DK76 and DK77, physical model tests on the overlying soil properties, compactness, the intersection angle between hidden cracks and the water flow direction, the height of confined water level, and the groundwater flow rate are conducted to analyze the effect of these factors on the formation and expansion of ground fissures. The test results show that the soil with strong collapsibility under the action of underground erosion produces fissures, collapses, and holes similar to those in the rift valley area along the first phase of the Nairobi–Malaba Railway in Kenya; the loose overburden is conducive to the occurrence of surface collapse; the collapse of the soil surface is the most severe when the underlaid cracks are parallel to the water flow direction; the higher confined water level and faster inflow rate will aggravate the collapse of the overlying soil layer.
3D Virtual Reality Smartphone Training for Chemotherapy Drug Administration by Non-oncology Nurses: A Randomized Controlled Trial

Chemotherapy agents are cytotoxic materials. Thus, there is a need for the operators to be familiar with the knowledge and procedures before operation. We conducted a randomized controlled trial investigating the effectiveness of an immersive 3D VR teaching of chemotherapy administration operated in a smartphone coupled with a visual and audio device. We adopted a two-arm single-blind design and recruited 83 nurses, and they were randomized using a cluster approach. The VR group learned chemotherapy administration through VR, while the controlled group learned through document reading. The Knowledge and Attitude of Chemotherapy Administration (KACA) was administrated before the intervention, while the Objective Structured Clinical Examination (OSCE) and the Checklist of Action Accomplishment (CAA) were administrated one month after the intervention. The VR group scored higher than the controlled group in the CAA (95.69 ± 5.37 vs. 91.98 ± 9.31, p = 0.02) and the OSCE (73.07 ± 10.99 vs. 67.44 ±10.65, p = 0.02). Stepwise regression demonstrated that service years, an education level of undergraduate or above, and VR exposure contributed positively to the OSCE score (adjusted R2 = 0.194, p = 0.028). The use of VR improves the learning efficacy of chemotherapy administration in non-oncology nurses. We recommend using VR as a teaching tool for chemotherapy administration and other chemotherapy-related skills in a VR learning group with senior nurses with higher education levels as advisors. The study provides an approach to online training, especially during the COVID-19 pandemic. (CONSORT 2010 guidelines, registry number: NCT 04840732).
Resource for FRET-Based Biosensor Optimization

After the development of Cameleon, the first fluorescence resonance energy transfer (FRET)-based calcium indicator, a variety of FRET-based genetically encoded biosensors (GEBs) have visualized numerous target players to monitor their cell physiological dynamics spatiotemporally. Many attempts have been made to optimize GEBs, which require labor-intensive effort, novel approaches, and precedents to develop more sensitive and versatile biosensors. However, researchers face considerable trial and error in upgrading biosensors because examples and methods of improving FRET-based GEBs are not well documented. In this review, we organize various optimization strategies after assembling the existing cases in which the non-fluorescent components of biosensors are upgraded. In addition, promising areas to which optimized biosensors can be applied are briefly discussed. Therefore, this review could serve as a resource for researchers attempting FRET-based GEB optimization.
In Vitro Propagation of Volkamer Lemon using Nodal Cutting Segments

Citrus is one of the most important commodity worldwide, owing to its tremendous nutritional value, and acceptable as fresh edible food. This study was conducted at the Desert Research Center (DRC) in Cairo, Egypt, during the period 2013-2017. An efficient in vitro propagation system for Volkamer lemon (Citrus volkameriana) was established. The effect of various combination of two plant growth regulators (cytokinin and auxin) was evaluated on the proliferation efficiency of citrus plant via in vitro propagation technique. The sterilized stem nodal segments of the given species were planted vertically on MS culture medium augmented with various combinations of BAP at 0.0, 0.5, 1.0, 1.5, 2.0, 2.5, and 3.0 mg/l and NAA at 0.0, 0.1, and 0.2 mg/l, and especially at BAP×NAA at 2.0 ×0.1 mg/l respectively proved to be the best for bud induction. The survival percentage of stem node segment frequency was 100%, especially when MS medium was supplemented with BAP in a range 1.03.0 mg/l. The best shoot initiation was obtained on MS medium augmented with BAP and NAA at 2.0 and 0.1 mg/l, each in turn, which recorded the highest mean value (3.99 shoots/ explant). Higher number of elongated shoots was obtained on MS medium with BAP and NAA at 3.0 and 0.1 mg/l, in order. The higher multiplication rate was recorded on MS medium containing BAP and NAA at either 2.0 or 2.5 mg/l for the former and 0.05 mg/l for the latter. The shoots were then rooted on MS medium containing IBA and NAA at 1.5 and 0.2 mg/l consecutively, with high rooting percentage (100%). The plantlets survival ex vitro swas (80%) when plantlets were transferred to plastic pots containing a mixture of sand and peatmoss (1:1). In conclusion, this study provides reproducible technique for micropropagation of Volkamer Lemon.
Understanding Location Privacy of the Point-of-Interest Aggregate Data via Practical Attacks and Defenses

Location-based services have significantly affected mobile users’ everyday life, and location privacy has become essential. Some applications (e.g., location-based recommendation, mobility analytics) do not need the raw location data, and the service providers adopt aggregation to protect users’ location traces. However, some works show that even these aggregation data may disclose users’ location privacy when additional prior knowledge is available to an adversary. We consider the location privacy problem in the presence of Location Uniqueness, a property by which some geographical locations can be re-identified based on the aggregated point-of-interest information. We first study whether existing protection mechanisms are adequate for defending against this type of attack. Then we present two practical attacks for inferring users’ actual locations based on the POI aggregates. A secure POI aggregate release mechanism is proposed for defending against this type of re-identification attack and achieving differential privacy at the same time. We conduct extensive experiments on real-world datasets. The results show that the existing protection mechanisms cannot provide sufficient protection against location re-identification attacks. The proposed attacks can significantly improve the inference performance, and the proposed protection mechanism achieves satisfactory performance.
Allocation of Regional Logistics Hubs and Assessing Their Contribution to Saudi Arabia’s Logistics Performance Index Ranking

In 2016, Saudi Arabia published its vision for the year 2030, which is based on the Kingdom’s geographical, financial, social and religious potentials. Developing the logistics sector and improving the Kingdom’s ranking in the World Bank’s Logistics Performance Index (LPI) to the twenty-fifth rank was one of the most targeted success factors. Unfortunately, Saudi Arabia’s rank in this index has declined over the past years, until it reached the fifty-fifth rank as per the last published LPI report. This research proposes a set of logistics hubs (LHs) which are located at key multi-logistics areas within the regional trading zones of the country. A spatial model was implemented on a macro level to integrate multi-logistical, infrastructural and natural geographic information system (GIS) layers, and highlight their intersections as initial feasible areas. Subsequently, an optimization model based on integer linear programming (ILP) was used to maximize the number of allocated LHs and minimize the overall distances between allocated LHs and international trading nodes considering multiple factors. More than 80 selected subject matter experts (SMEs) from 9 different countries have participated in World Bank’s driven surveys that assess the contribution of the LHs’ allocation proposal on Saudi Arabia’s LPI ranking. An improvement of about 10% in the LPI overall score with a 20 rank promotion has been estimated as per the SMEs responses. These results demonstrate that investing in logistics infrastructure and ranking in LPI are perfectly, positively and highly related.
A Nudge-Inspired AI-Driven Health Platform for Self-Management of Diabetes

Diabetes mellitus is a serious chronic disease that affects the blood sugar levels in individuals, with current predictions estimating that nearly 578 million people will be affected by diabetes by 2030. Patients with type II diabetes usually follow a self-management regime as directed by a clinician to help regulate their blood glucose levels. Today, various technology solutions exist to support self-management; however, these solutions tend to be independently built, with little to no research or clinical grounding, which has resulted in poor uptake. In this paper, we propose, develop, and implement a nudge-inspired artificial intelligence (AI)-driven health platform for self-management of diabetes. The proposed platform has been co-designed with patients and clinicians, using the adapted 4-cycle design science research methodology (A4C-DSRM) model. The platform includes (a) a cross-platform mobile application for patients that incorporates a macronutrient detection algorithm for meal recognition and nudge-inspired meal logger, and (b) a web-based application for the clinician to support the self-management regime of patients. Further, the platform incorporates behavioral intervention techniques stemming from nudge theory that aim to support and encourage a sustained change in patient lifestyle. Application of the platform has been demonstrated through an illustrative case study via two exemplars. Further, a technical evaluation is conducted to understand the performance of the MDA to meet the personalization requirements of patients with type II diabetes.
Comparison of the Newton–Raphson Method and genetic algorithm solutions for nonlinear aircraft trim analysis

As the number of unknowns in trim analysis increases, the problem becomes more complicated, and traditional methods begin to fail. Common problems with conventional methods may be an ill-conditioned matrix, rounding errors, and division by zero. Furthermore, these methods are likely to find the local optimum, not the global optimum. In such cases, hybrid use with intelligent methods such as genetic algorithms is recommended. In this study, a flight situation that the Newton–Raphson method has for difficulty in solving is selected for a six-degree-of-freedom nonlinear trim analysis. Trim analysis was performed using the Newton–Raphson method, genetic algorithm, and by their hybrid use, respectively. The Newton–Raphson method had convergence problems despite very good initial guesses. The genetic algorithm was able to solve the same problem by itself. The unknowns in trim analysis, such as deflection angles of an elevator, a rudder, and an aileron, have physical limits, whereas the constraints make conventional methods more complicated, and the ability to use these limits in the genetic algorithm narrows the solution space and reduces the computation time. The hybrid use of the GA and Newton–Raphson method significantly increased the performance of the Newton–Raphson method and eliminated the convergence problem. It has been shown that a 6-degree-of-freedom trim problem, which traditional numerical methods such as the Newton–Raphson method have for difficulty in solving, can be solved easily and effectively with the hybrid use of the GA and the Newton–Raphson method. The strength of the proposed hybrid method to solve a highly nonlinear trim problem was demonstrated.
Effects of Shock Waves on Impact Velocity of Cold Spray Particles

The modeling of the cold gas dynamics spray process is conducted. The Navier-Stokes equations are solved for the gas flow, including turbulence model equations. The model is validated with experimental measurements for flows with and without shock waves. It predicts accurately the gas flow for both cases. A one-dimensional model is used to track the particles injected in the flow. It is shown that the effects of the shock wave present in front of the substrate are not negligible for small diameter particles and have a direct influence on their impact velocity. The spray stand-off distance is shown to have a direct effect on the flow structure and on the impact velocity of the particles. It is shown that the one-dimensional approach is not sufficient for the particle analysis.