Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing Individual UAV Path Planning With Parallel Multi-Swarm Treatment Coronavirus Herd Immunity Optimizer (PMST-CHIO) Algorithm

This paper introduces the PMST-CHIO, a novel variant of the Coronavirus Herd Immunity Optimizer (CHIO) algorithm, exclusively tailored for individual unmanned aerial vehicle (UAV) path planning in complex 3D environments. While acknowledging and building upon the foundational principles derived from UAV swarm path planning research, the PMST-CHIO distinctively focuses on optimizing the trajectory of single UAVs. It innovatively integrates a parallel multi-swarm treatment mechanism, enhancing the standard CHIO’s exploration and exploitation capabilities significantly. This mechanism diverges from the swarm-based approaches by deploying multiple instances of the CHIO optimizer, each functioning autonomously within its sub-swarm, thereby facilitating independent path planning for individual UAVs. These multiple CHIO instances or CHIO candidates, operate in concert to determine the optimal and collision-free routes, taking into account the unique characteristics of individual UAVs and the intricacies of the service area. The algorithm incorporates two key mechanisms: 1) global exploitation, employing the best solution identified by the highest performing CHIO candidate across the swarms; and 2) strategic shift from parallel multi-swarm exploration to focused exploration by the top-performing CHIO candidate after a specific iteration threshold is reached. This adaptation significantly improves the algorithm’s global search efficiency, convergence behavior, and navigational accuracy under challenging environments. Extensive simulations and comparative studies validate that the PMST-CHIO can effectively overcome the limitations of the standard CHIO algorithm, yielding safer, shorter, and more compliant flight paths for individual UAVs in intricate 3D landscapes.
Case report: vesiculopustular eruption of transient myeloproliferative disorder of the newborn with Down syndrome

Neonates with Down Syndrome (DS) have a greater predisposition to Transient Myeloproliferative Disorder (TMD), a hematologic disorder with transient proliferation of immature cells in peripheral blood and bone marrow. Some neonates with TMD present with skin manifestations characterized by diffuse erythematous papules, with crusts, vesicles and pustules, usually with early and prominent facial involvement. Despite the spontaneous remission of TMD over several months, some cases may need support care and, occasionally, chemotherapy. It is described the case of a newborn with Down Syndrome phenotype, male, that manifested such characteristics in the fifth day of life, and the instituted propaedeutics in a Neonatal Intensive Care Unit. The diagnosis is both clinical and laboratorial, and therefore was based in typical features. The used treatment involved conservatory measures of skin and mucosal care, avoiding trauma. It was observed an improvement of all lesions within one month of life. As a result, it is demonstrated the importance of differential diagnosis given the need for regular clinical follow up and eventually chemotherapy.
Wearable Tactile Display Based on Thermal Expansion of Nichrome Wire

A wearable tactile display needs to be compact and lightweight, and ideally should be able to present vibration, force, and temperature information to the hand. In many contexts spatially distributed tactile information is needed such as when identifying the shape of objects. In this paper, a multi-element tactile display is described based on the thermal expansion and contraction of nichrome wire. The device comprises elastic rods that are pulled by nichrome wires (30 μm in diameter). When an electrical current is applied to the wire, displacement of the elastic rod occurs with thermal elongation of the wire. The wire cools quickly and vibration results. The nichrome wire that is the basis of this display overcomes many of the material restrictions associated with shape memory alloys that have often been used for thermally driven tactile displays. Experiments that characterized the performance of the tactile display indicated that perceptible vibrations up to 320 Hz can be presented. Psychophysical studies revealed that both position and movement cues can be displayed effectively with the device. A miniaturized version of this display for wearable applications has been built and undergone preliminary evaluation.
Acceleration of Hyperspectral Skin Cancer Image Classification through Parallel Machine-Learning Methods

Hyperspectral imaging (HSI) has become a very compelling technique in different scientific areas; indeed, many researchers use it in the fields of remote sensing, agriculture, forensics, and medicine. In the latter, HSI plays a crucial role as a diagnostic support and for surgery guidance. However, the computational effort in elaborating hyperspectral data is not trivial. Furthermore, the demand for detecting diseases in a short time is undeniable. In this paper, we take up this challenge by parallelizing three machine-learning methods among those that are the most intensively used: Support Vector Machine (SVM), Random Forest (RF), and eXtreme Gradient Boosting (XGB) algorithms using the Compute Unified Device Architecture (CUDA) to accelerate the classification of hyperspectral skin cancer images. They all showed a good performance in HS image classification, in particular when the size of the dataset is limited, as demonstrated in the literature. We illustrate the parallelization techniques adopted for each approach, highlighting the suitability of Graphical Processing Units (GPUs) to this aim. Experimental results show that parallel SVM and XGB algorithms significantly improve the classification times in comparison with their serial counterparts.
Adaptive Gaussian Weighted Laplace Prior Regularization Enables Accurate Morphological Reconstruction in Fluorescence Molecular Tomography

Fluorescence molecular tomography (FMT), as a powerful imaging technique in preclinical research, can offer the three-dimensional distribution of biomarkers by detecting the fluorescently labelled probe noninvasively. However, because of the light scattering effect and the ill-pose of inverse problem, it is challenging to develop an efficient reconstruction method, which can provide accurate location and morphology of the fluorescence distribution. In this research, we proposed a novel adaptive Gaussian weighted Laplace prior (AGWLP) regularization method, which assumed the variance of fluorescence intensity between any two voxels had a non-linear correlation with their Gaussian distance. It utilized an adaptive Gaussian kernel parameter strategy to achieve accurate morphological reconstructions in FMT. To evaluate the performance of the AGWLP method, we conducted numerical simulation and in vivo experiments. The results were compared with fast iterative shrinkage (FIS) thresholding method, split Bregman-resolved TV (SBRTV) regularization method, and Gaussian weighted Laplace prior (GWLP) regularization method. We validated in vivo imaging results against planar fluorescence images of frozen sections. The results demonstrated that the AGWLP method achieved superior performance in both location and shape recovery of fluorescence distribution. This enabled FMT more suitable and practical for in vivo visualization of biomarkers.
Sampled-Data-Based H∞ Synchronization of Switched Coupled Neural Networks

This paper investigates the sampled-data-based ${H_\infty }$ synchronization problem for a class of switched coupled neural networks subject to exogenous perturbations. Different from the existing results on the nonswitched and continuous-time control cases, the unmatched phenomena between the switching of the system models and that of the controllers will occur, when the resulting error system switches within a sampling interval. In the framework of time-dependent switching mechanism, sufficient conditions for the existence of the sampled-data controllers are derived under the variable sampling and asynchronous switching. We prove that the proposed method not only renders the synchronization error system exponentially stable but also constrains the influence of the exogenous perturbations on the synchronization performance at a specified level. Finally, a switched coupled cellular neural network and a switched coupled Hopfield neural network are provided to illustrate the applicability and validity of the developed results.
Complete Genome Sequences of Two Methicillin-Susceptible Staphylococcus aureus Clinical Strains Closely Related to Community-Associated Methicillin-Resistant S. aureus USA300

Predominant community-associated methicillin-resistant Staphylococcus aureus strain USA300 is believed to have originated from an ancestral methicillin-susceptible strain, although the details of that evolution remain unknown. To help understand the emergence of this highly successful strain, we sequenced the genomes of two methicillin-susceptible Staphylococcus aureus clinical strains that are very closely related to USA300. ABSTRACT Predominant community-associated methicillin-resistant Staphylococcus aureus strain USA300 is believed to have originated from an ancestral methicillin-susceptible strain, although the details of that evolution remain unknown. To help understand the emergence of this highly successful strain, we sequenced the genomes of two methicillin-susceptible Staphylococcus aureus clinical strains that are very closely related to USA300.
Peri‐implant marginal bone loss reduction with platform‐switching components: 5‐Year post‐loading results of an equivalence randomized clinical trial

Abstract Aim To compare the clinical performance and marginal bone levels of implants restored with platform‐switching (PS) or platform‐matching (PM) abutments. Materials and Methods Adult patients missing two or more adjacent teeth in the posterior mandible received 2–4 CAMLOG SCREW‐LINE implants and were randomly allocated to the PM or PS group, receiving the corresponding prosthetic components from surgery onwards. Implants were conventionally loaded with single cemented crowns. Patients were followed annually for 5 years. Outcome measures were marginal bone level changes, implant survival, performance of the prosthetic components and clinical parameters plaque index, sulcus bleeding index and pocket probing depth. Results Thirty‐three patients received 72 implants in the PM group, and thirty‐five patients received 74 implants in the PS group. Sixty patients attended the final appointment, 31 had received PS components and 29 had received PM components with 65 and 63 implants, respectively. Global survival rate was 96.6% with no differences between groups (p = 0.647). After 5 years of functional loading, PS restored implants presented 0.23mm (95% CI: [0.03, 0.43], p = 0.025) lower marginal bone level changes. The two groups were declared non‐equivalent. Conclusion Patients requiring implant supported restorations in healed bounded or free end edentulous gaps of the mandible benefit from the use of PS components in terms of peri‐implant marginal bone level maintenance, though it may not be clinically noticeable.
Ef(cid:2)cient, physically plausible (cid:2)nite elements

This paper discusses FEM-based simulations of soft bodies in terms of speed and robustness. To be physically plausible, three fundamental laws must be respected: rotational invariance, Newton’s law and Euler’s law. We show that precomputed strain-displacement matrices generate nonphysical torques which can lead to visual artifacts. We then derive the fastest FEM-based method meeting our criteria of plausibility and robustness and discuss their limitations
Illumination Invariant Face Recognition

This paper introduces a system in which the face recognition is carried out with the help of the local feature descriptors. As today face recognition is a very active area of research, a system which carries out the robust face recognition is needed to be developed. Face recognition is used in various fields of security and access control, surveillance military etc. here the system is developed in which face recognition is done under varying illumination (lighting) conditions. Local directional number pattern (LDN) is the descriptor which is used here to extract the features from the face image. The LDN produces the compact code which extracts the useful features of the face. The face image is divided into several regions and then for each region LDN is computed and then the histogram of each region is taken for the sake of comparison. Then all the histograms are concatenated to form a feature vector. The LDN thus perform the best under the varying illumination conditions for the correct face recognition. KeywordsFace recognition, Gabor filter, LBP (Local Binary Pattern), feature extraction, FRM (Face recognition method).
Attraction radii in binary Hop(cid:12)eld nets are hard to compute

We prove that it is an NP-hard problem to determine the attraction radius of a stable vector in a binary Hop(cid:12)eld memory network, and even that the attraction radius is hard to approximate. Under synchronous updating, the problems are already NP-hard for two-step attraction radii; direct (one-step) attraction radii can be computed in polynomial time. A Hop(cid:12)eld memory network [6] consists of n binary valued nodes, or \neurons. " We index the nodes by f1;:::;ng, and choose f(cid:0)1;+1g as their possible states (the values f0;1g could be chosen equally well). Associated to each pair of nodes i;j is an interconnection weight wij. The interconnections are symmetric, so that wij = wji for each i;j; moreover, wii = 0 for each i. In addition, each node i has an internal threshold value ti. We denote the matrix of interconnection weights by W = (wij), and the vector of threshold values by t = (t1;t2;:::;tn). At any given moment, each node i in the network has a state xi, which is either (cid:0)1 or +1. The state at the next moment is determined as a function of the states of the other nodes as (cid:3) Work supported by the Academy of Finland.
Overview of CAFCR and Threads of Reasoning-explore

The described architecting method uses the CAFCR model as starting point. Qualities are used as orthogonal dimension to integrate the CAFCR views. Story telling is used to add specifics. Threads of reasoning combine all the information into a coherent overview. Distribution This article or presentation is written as part of the Gaudí project. The Gaudí project philosophy is to improve by obtaining frequent feedback. Frequent feedback is pursued by an open creation process. This document is published as intermediate or nearly mature version to get feedback. Further distribution is allowed as long as the document remains complete and unchanged. All Gaudí documents are available at: http://www.gaudisite. nl/ version: 1.5 status: finished February 10, 2011
Automate This: How Algorithms Took Over Our Markets, Our Jobs, and the World

How the rise of computerized decision-making affects every aspect of business and daily life These days, high-level taskssuch as diagnosing an illness or interpreting legal documentsare increasingly being handled by algorithms that can do precise work with speed and nuance. In this fascinating book, Steiner tells the story of how algorithms took over and shows why the bot revolution is about to spill into every aspect of our lives. We meet bots that are driving cars, penning haikus, and writing music mistaken for Bachs. They listen in on customer service calls and figure out what Iran would do in the event of a nuclear standoff. But what will the world look like when algorithms control our hospitals, our roads, and our national security? And what role will be left for doctors, lawyers, writers, truck drivers, and many others?
Path Loss and Fading Characterization at 2. 4 GHz for Indoor Scenario

A measurement exercise is undertaken to determine path loss and fading behavior of the propagation channel through RF level measurements. Path loss exponent is computed for LOS and NLOS antenna positions in a building that predicts effect of wall partitions, number of floors at 2.4 GHz. Further, the channel fading is derived to understand the exact fading behavior by virtue of obtaining CDF of the fading distribution of the received data. The fading distribution of the received signal is compared to standard distributions mainly Rayleigh, Rician and Lognormal.
Enacting New Ways of Organizing: Exploring the Activities and Consequences of Post-Industrial Work

Our empirical study of an interactive marketing company explores how post-industrial work is constituted through the ongoing daily activities of organizational actors drawing on diverse backgrounds to accomplish project-based work. These actors engage in four types of work practices: negotiating agreements, concurrent designing and building, coordinating across boundaries within the organization, and collaborating with clients. As individuals interact across their occupational differences, new ways of working are both enabled and constrained, resulting in intended and unintended consequences for both individuals and organizations.
Sequential specification of time-aware stream processing applications (Extended abstract)

Stream processing applications, and in particular Software Defined Radio applications, are typically executed on multi-core systems. Such applications often have real-time throughput constraints. Automatic parallelization of Nested Loop Programs (NLPs) is an attractive method to create embedded real-time stream processing applications for multi-core systems [1]. However, the description and parallelization of applications with a time dependent functional behavior has not been considered for NLPs. In such a description, semantic information about time dependent behavior must be made available for the compiler, such that an optimized time independent implementation can be generated automatically.
A benchmark study of ab initio gene prediction 1 methods in diverse eukaryotic organisms 2

10 Background: The draft genome assemblies produced by new sequencing technologies 11 present important challenges for automatic gene prediction pipelines, leading to less accurate 12 gene models. New benchmark methods are needed to evaluate the accuracy of gene prediction 13 methods in the face of incomplete genome assemblies, low genome coverage and quality, 14 complex gene structures, or a lack of suitable sequences for evidence-based annotations. 15 Results: We describe the construction of a new benchmark, called G3PO (benchmark for 16 Gene and Protein Prediction PrOgrams), designed to represent many of the typical challenges 17 faced by current genome annotation projects. The benchmark is based on a carefully validated 18 and curated set of real eukaryotic genes from 147 phylogenetically disperse organisms, and a 19 number of test sets are defined to evaluate the effects of different features, including genome 20 sequence quality, gene structure complexity, protein length, etc. We used the benchmark to 21 perform an independent comparative analysis of the most widely used ab initio gene 22 prediction programs and identified the main strengths and weaknesses of the programs. More importantly, we highlight a number of features that could be exploited in order to improve the 24 accuracy of current prediction tools. 25 Conclusions: The experiments showed that ab initio gene structure prediction is a very 26 challenging task, which should be further investigated. We believe that the baseline results 27 associated with the complex gene test sets in G3PO provide useful guidelines for future 28 studies. 29
Scaling Power and Performance viaProcessor Composability

Power dissipation trends are leading high-performance processors to a regime in which all chip elements cannot be operated simultaneously at maximum frequency. Consequently, energy-efficiency will increase even more in importance, and performance must be achieved within strict power budgets. Current designs employ techniques such as dynamic voltage and frequency scaling (DVFS) to provide power-performance tradeoffs for both single and multi-threaded workloads. In power-dominated regimes, processors will be run at or near the minimum voltage. Frequency can be reduced to save power, but there is no scaling strategy for increasing performance with high energy-efficiency if the processor is operating at its maximum frequency (and minimum voltage). In this paper, we evaluate the energy-efficiency of processor composability-dynamically aggregating small energy-efficient physical cores into larger logical processors-as a method of scaling single-threaded performance up and down, comparing composability to the energy-efficiency of voltage and frequency scaling. We measure the power breakdowns of the baseline composable microarchitecture (the TFlex microarchitecture, based on an EDGE ISA) and compare the energy-efficiency and performance to one processor designed for power-efficiency (XScale) and another designed for high-performance (a variant of the Power-4) using normalized power models for as fair a comparison as possible. The study shows that composing multiple dual-issue cores (up to eight) provides performance scaling that is as energy-efficient as frequency scaling in a balanced microarchitecture, and is considerably more efficient than scaling the voltage to achieve additional performance once the maximum frequency at the minimum voltage is attained.
Effect of the pre-taper level of fatigue on the taper-induced changes in performance in elite swimmers

Introduction In swimming, performance gains after tapering could be influenced by the pre-taper level of fatigue. Moreover, this level of fatigue could be associated with sleep. This study aimed to assess (1) the effect of tapering on performance according to the pre-taper level of fatigue in swimmers and (2) the association between sleep and pre-taper level of fatigue. Methods Physiological, psychological and biomechanical profiles were evaluated in 26 elite swimmers on 2 occasions to estimate the pre-taper level of fatigue: at T0 and T1, scheduled respectively 10 and 3 weeks before the main competition. Sleep quantity and quality were also evaluated at T0 and T1. Race time was officially assessed at T0, T1 and during the main competition. The level of significance was set at p ≤ . 05. Results Fourteen swimmers (17 ± 2 years) were allocated to acute fatigue group (AF) and 12 swimmers (18 ± 2 years) to functional overreaching group (F-OR). From T1 to the main competition, performance was improved in AF (+1.80 ± 1.36%), while it was impaired in F-OR (−0.49 ± 1.58%, p < 0.05 vs. AF). Before taper period, total sleep time was lower in F-OR, as compared to AF. Conversely, the fragmentation index was higher in F-OR (p = .06). From wakefulness to sleep, body core temperature decreased in AF but not in F-OR. Discussion Performance gain after tapering was higher in AF swimmers than in overreached. Moreover, pre-taper sleep was poorer in overreached swimmers, which could contribute to their different response to the same training load. This poorer sleep could be linked to a lower regulation of internal temperature.