Miracle-dz/UniFAR-FTUs huggingface dataset:
Precordial Vibrations: A Review of Wearable Systems, Signal Processing Techniques, and Main Applications

Recently, the ever-growing interest in the continuous monitoring of heart function in out-of-laboratory settings for an early diagnosis of cardiovascular diseases has led to the investigation of innovative methods for cardiac monitoring. Among others, wearables recording seismic waves induced on the chest surface by the mechanical activity of the heart are becoming popular. For what concerns wearable-based methods, cardiac vibrations can be recorded from the thorax in the form of acceleration, angular velocity, and/or displacement by means of accelerometers, gyroscopes, and fiber optic sensors, respectively. The present paper reviews the currently available wearables for measuring precordial vibrations. The focus is on sensor technology and signal processing techniques for the extraction of the parameters of interest. Lastly, the explored application scenarios and experimental protocols with the relative influencing factors are discussed for each technique. The goal is to delve into these three fundamental aspects (i.e., wearable system, signal processing, and application scenario), which are mutually interrelated, to give a holistic view of the whole process, beyond the sensor aspect alone. The reader can gain a more complete picture of this context without disregarding any of these 3 aspects.
Measuring the perception of quality management primary healthcare services through SERVQUAL model

The quality of healthcare is more difficult to identify than other services because it is the clients themselves and their quality of life that gets evaluated (Eiriz & Figueiredu, 2005). The main aim of this study is to investigate people’s perceptions and expectations regarding the quality of services in primary health care (PHC) in Kosovo. A national level survey provides baseline findings intuitively understandable to policymakers on the expectations — perceptions of the quality of services at the PHC level and identifying the quality gap between the expectations and perceptions in all dimensions of different facilities. This comparative test will show the differences between the level of quality services provided by each PHC provider in Kosovo. This research seeks to improve the access and the quality of the priority services at PHC, including maternal and child health (MCH) and non-communicable disease (NCD). This research showed that at the national level the patients have higher expectations toward PHC services. Whereas, in specific, this study showed that there is a significant gap in expected and perceived services of the PHC system between different ethnic patients and different levels of citizen education. Therefore, the result of this study will contribute to enhancing the sustainability of the mandatory health insurance reform and raise the alarm of relevant institutions to reshape the policy-making in order to improve the population health outcome.
Carotenoids in Palliative Care—Is There Any Benefit from Carotenoid Supplementation in the Adjuvant Treatment of Cancer-Related Symptoms?

Carotenoids are organic, liposoluble pigments found in nature, which are responsible for the characteristic colors of ripe tomatoes, carrots, peppers, and crustaceans, among others. Palliative care provided to patients with an incurable disease is aimed at improving the patient’s quality of life through appropriate treatment of symptoms accompanying the disease. Palliative care patients with burdensome symptoms related to advanced-stage cancers are especially interested in the use of natural dietary supplements and herbal remedies to reduce symptoms’ intensity and ameliorate the quality of life. Carotenoids seem to be a group of natural compounds with particularly promising properties in relieving symptoms, mainly due to their strong antioxidant, anti-inflammatory, and neuroprotective properties. Moreover, carotenoids have been used in folk medicine to treat various diseases and alleviate the accompanying symptoms. In this narrative review, the authors decided to determine whether there is any scientific evidence supporting the rationale for carotenoid supplementation in advanced-stage cancer patients, with particular emphasis on the adjuvant treatment of cancer-related symptoms, such as neuropathic pain and cancer-related cachexia.
Orbital polarization in LiVO2 and NaTiO2

We present a band structure study of orbital polarization and ordering in the two-dimensional triangular-lattice transition metal compounds LiVO2 and NaTiO2. It is found that while in NaTiO2 the degeneracy of t2g orbitals is lifted due to the trigonal symmetry of the crystal and the strong on-site Coulomb interaction, in LiVO2 orbital degeneracy remains and orbital ordering corresponding to the trimerization of the two-dimensional lattice develops.
Comparative Transcriptome Analysis on the Regulatory Mechanism of Thoracic Ganglia in Eriocheir sinensis at Post-Molt and Inter-Molt Stages

Eriocheir sinensis is an aquatic species found distributed worldwide. It is found in the Yangtze River of China, where the commercial fishing of this valuable catadromous aquatic species has been banned. As an important member of the phylum Arthropoda, E. sinensis grows by molting over its whole lifespan. The central nervous system of Eriocheir sinensis plays an important regulatory role in molting growth. Nevertheless, there are no reports on the regulatory mechanisms of the nervous system in E. sinensis during the molting cycle. In this study, a comparative transcriptome analysis of E. sinensis thoracic ganglia at post-molt and inter-molt stages was carried out for the first time to reveal the key regulatory pathways and functional genes operating at the post-molt stage. The results indicate that pathways and regulatory genes related to carapace development, tissue regeneration, glycolysis and lipolysis and immune and anti-stress responses were significantly differentially expressed at the post-molt stage. The results of this study lay a theoretical foundation for research on the regulatory network of the E. sinensis nervous system during the post-molt developmental period. Detailed knowledge of the regulatory network involved in E. sinensis molting can be used as a basis for breeding improved E. sinensis species, recovery of the wild E. sinensis population and prosperous development of the E. sinensis artificial breeding industry.
P-33 The effects of distraction task and initial joint angle time in a joint position matching task

Proprioception is a sense that can detect the position and movement of one’s own body parts. It is not only essential in the effective interaction with the outside world, but also critical in the situation that bodily movements need to be made in the absence of vision. A joint position matching is a method to evaluate the proprioceptive acuity. In a joint position matching task, subjects should replicate a reference joint angle without the aid of vision, only relying on the proprioceptive information. Then, spatial error between the reference and the matching movement is measured. This study investigates the effect of a distraction task and initial joint angle time on the accuracy of an elbow joint position matching task. An experiment was designed and conducted and twelve participants voluntarily participated in the experiment. In the conditions with distraction tasks, the participants were requested to solve simple calculation problems when they were holding the initial joint angle waiting for the onset of the replication signal. The time for holding the initial joint angle was manipulated as 0s, 5s, 10s, and 15s. The results showed that the accuracy of the joint position matching decreased as the initial joint angle time increased. In addition, the effect of distraction task and the interaction between the two factors were significant, showing degraded performance with the presence of the distraction task in most initial joint angle time conditions. A further study is suggested to investigate the effects of different types of distracting tasks in an experiment with a larger scale.
Full‐state prescribed performance pose tracking of space proximity operations with input saturation

This paper investigates the relative position tracking and attitude synchronization control for spacecraft close‐range proximity missions with input saturation and model uncertainties. A robust saturated relative motion controller is proposed for this purpose. Prescribed performance functions are designed to guarantee the transient and steady‐state response of the system and the full‐state constraints. Then, a nonlinear disturbance observer is developed to estimate the lumped disturbance that comprises the effects of parametric uncertainties and kinematic couplings. At the same time, a linear compensator system is incorporated into the controller design to deal with the control input saturation. Finally, it can be proved via the Lyapunov theory that the closed‐loop system is uniformly ultimately bounded stable. Simulation results on the spacecraft close‐range rendezvous and docking mission validate the effectiveness of the proposed control approach.
Model Selection Criterion Based on the Multivariate Quasi‐Likelihood for Generalized Estimating Equations

The generalized estimating equations (GEE) approach has attracted considerable interest for the analysis of correlated response data. This paper considers the model selection criterion based on the multivariate quasi‐likelihood (MQL) in the GEE framework. The GEE approach is closely related to the MQL. We derive a necessary and sufficient condition for the uniqueness of the risk function based on the MQL by using properties of differential geometry. Furthermore, we establish a formal derivation of model selection criterion as an asymptotically unbiased estimator of the prediction risk under this condition, and we explicitly take into account the effect of estimating the correlation matrix used in the GEE procedure.
International Conference on Flexible Automation and Intelligent Manufacturing , FAIM 2017 , 27-30 June 2017 , Modena , Italy Towards shared autonomy for robotic tasks in manufacturing

Recently a new class of industrial robots hit the market that can be potentially used in the same environment as human coworkers (fenceless) if relevant norms are fulfilled. The concept of robots cooperating with humans has gained a lot of interest in the academia, but lacks nowadays applications in both domestic and industrial areas. In this paper, we present a platform for human robot collaboration, which allows building applications of human robot interactions in an intuitive way. Using this platform, the worker is enabled to pursue different levels of shared autonomy between human and robot. Three applications in industrial environment are demonstrated with increasing level of autonomy from coexistence to collaboration. These examples exemplify the usability of such a flexible system in the automation chain and the presented results provide strong evidence of the technological potential in the field. © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 27th International Conference on Flexible Automation and Intelligent Manufacturing.
Deep Reinforcement Learning-Based Power Allocation for Rate-Splitting Multiple Access in 6G LEO Satellite Communication System

Rate-splitting multiple access (RSMA) softly reconciles and decodes the extreme interference by non-orthogonal transmission, which can remarkably solve the spectrum scarcity for future six-generation (6G) low earth orbits (LEO) satellite communication system. In this letter, we investigate the power allocation problem in LEO satellite networks with RSMA mechanism based on the deep reinforcement learning (DRL) technique. Specifically, in order to achieve better RSMA performance, the LEO satellite base station (SBS) has to effectively allocate transmit power to common and private streams, which is very challenging due to the uncertain and limited information of the channel distribution. To solve this problem, a highly-effective proximal policy optimization (PPO) based scheme is further proposed, which enables the LEO SBS to learn an optimal power allocation strategy to maximize the sum rate of the system without knowing any prior information. Simulation results prove that the proposed scheme significantly outperforms the other three baseline schemes in terms of the sum rate metric with low computation complexity.
Net Economic Values of Eight Soil Management Practices Used in Stake Tomato Production

Staked tomatoes (Lycopersicon esculentum Mill) grown in 8 soil management systems are compared for differences in marketable yields, gross revenues, treatment costs, and net economic values. Maximum marketable yields were obtained using a fumigant and straw mulch combinatory practice, but the highest net economic value (gross revenues less treatment costs) was realized by a fumigant and herbicide ground management practice. These data suggest that the use of mulch materials and/or herbicides increased yields and net returns over standard cultivation practices.
Modeling of CH4/CO2 hydrate phase behavior in organic and electrolyte inhibitors by dickens’ model

Abstract The main purpose of this study is investigating a reliable and convenient model based on Dickens and Quinby-Hunt approach to predict CH4/CO2 gas hydrate equilibrium temperature in presence of organic inhibitors (e.g., methanol, ethanol, ethylene glycol, triethylene glycol, glycerol), and electrolyte inhibitors (e.g., NaCl, KCl, NaBr, KBr, CaCl2, CaBr2, MgCl2, EMIM-Cl, BMIM-Cl, BMIM-Br, BMIM-I, BMIM-DCA, EMIM-HSO4, EMIM-EtSO4, and EMIM-MeSO4). This model named as Dickens’ model is an activity-based model and to calculate water activity of organic solutions the nonrandom two-liquid (NRTL) and Margules was used. Also, Pitzer model was employed to calculate activity of water in electrolyte solutions. A correlation was suggested to determine enthalpy of hydrate dissociation in terms of inhibitor weight percent and equilibrium pressure. Due to no data in open literature, the virial coefficients of Pitzer model in ionic liquid solutions were adjusted. The model results were compared with available experimental data from open literature and observed to be in good agreement with the reported literature.
Non-native terrestrial slugs from Sinaloa, Mexico: Deroceraslaeve (O. F. Müller, 1774) and Sarasinulaplebeia (P. Fischer, 1868) (Mollusca, Gastropoda)

Abstract This is the first record of two non-native terrestrial slug species from Sinaloa, Mexico. Deroceraslaeve and Sarasinulaplebeia were collected between 2019 and 2022 in Concordia and Mazatlan Municipalities (north-western Mexico). The external morphology and anatomic features of the dissected specimens coincide with the descriptions of each species, whose identities were also confirmed by their partial COI sequences. The ample occurrence of S.plebeia suggests that this species has an established population, while D.laeve was found as isolated individuals, likely associated with plant nurseries.
Development of Framework for Highway Lawn Condition Monitoring using UAV Images

– Planning, monitoring, and maintenance of highway assets is an essential, long-term operation for successful civil infrastructure management. These monitoring and maintenance activities are usually carried out manually, suffering from time-consuming, costly, potentially dangerous tasks. The advancements in Unmanned Aerial Vehicles (UAVs) and computer vision technologies have demonstrated the potential to enable automation of the monitoring workflows. Existing UAS-based approaches are used for various management; however, there was no study to examine the feasibility of aerial image-based computer vision algorithms for the purpose of lawn condition monitoring. This study aims to provide periodic and easy-to-use UAV technology for civil infrastructure maintenance. We developed the comprehensive framework from UAS data collection to build a deep learning model suitable to distinguish areas of interest with vague boundaries robustly, process the outputs into geo-database, and visualize them through a Geographic Information Systems (GIS) platform. The outcome of the proposed framework displays the overall mowing quality in the highway environment in an intuitive way to support decision-making in the management.
Information Extraction from Text Documents for the Semantic Enrichment of Building Information Models of Bridges

- The majority of innovative approaches in the realm of the retrospective generation of building information models for existing structures deal with geometry extraction from point clouds or engineering drawings. However, many building-specific o r o bject-specific at tributes fo r th e en richment of building models cannot be inferred from these geometric and visual data sources, and thus their acquisition requires the analysis of textual building documentation. One type of such documents are structural bridge records, which include specifications regarding used m aterial, l ocation, structural health, modifications, and administrative d ata. The documents are semi-structured and hardly allow a robust information extraction based on traditional programming, since the implementation of such an approach would result in a complex nesting of conditional clauses, which is not guaranteed to remain effective for future versions of the document structure. Therefore, a data-driven approach is adopted for the information extraction. This paper demonstrates an end-to-end semantic enrichment method, taking a bridge status report as input and feeding structured object parameters directly to the building information modeling software for the enrichment of the model. The proposed method requires little user interaction and achieves production-ready accuracy. It is tested on an as-built model of an actual bridge and shows promising results.
Semiclassical Singularity Propagation Property for Schr\"odinger Equations

We consider Schr\"odinger equations with variable coefficients, and it is supposed to be a long-range type perturbation of the flat Laplacian on $R^n$. We characterize the wave front set of solutions to Schr\"odinger equations in terms of the initial state. Then it is shown that the singularity propagates following the classical flow, and it is formulated in a semiclassical settings. Methods analogous to the long-range scattering theory, in particular a modified free propagator, are employed.
CD44 Contributes to the Regulation of MDR1 Protein and Doxorubicin Chemoresistance in Osteosarcoma

Osteosarcoma is the most common type of pediatric bone tumor. Despite great advances in chemotherapy during the past decades, the survival rates of osteosarcoma patients remain unsatisfactory. Drug resistance is one of the main reasons, leading to treatment failure and poor prognosis. Previous reports correlated expression of cluster of differentiation 44 (CD44) with drug resistance and poor survival of osteosarcoma patients, however the underlying mechanisms are poorly defined. Here, we investigated the role of CD44 in the regulation of drug chemoresistance, using osteosarcoma cells isolated from mice carrying a mutation of the tumor suppressor neurofibromatosis type 2 (Nf2) gene. CD44 expression was knocked-down in the cells using CRISPR/Cas9 approach. Subsequently, CD44 isoforms and mutants were re-introduced to investigate CD44-dependent processes. Sensitivity to doxorubicin was analyzed in the osteosarcoma cells with modified CD44 expression by immunoblot, colony formation- and WST-1 assay. To dissect the molecular alterations induced by deletion of Cd44, RNA sequencing was performed on Cd44-positive and Cd44-negative primary osteosarcoma tissues isolated from Nf2-mutant mice. Subsequently, expression of candidate genes was evaluated by quantitative reverse transcription PCR (qRT-PCR). Our results indicate that CD44 increases the resistance of osteosarcoma cells to doxorubicin by up-regulating the levels of multidrug resistance (MDR) 1 protein expression, and suggest the role of proteolytically released CD44 intracellular domain, and hyaluronan interactions in this process. Moreover, high throughput sequencing analysis identified differential regulation of several apoptosis-related genes in Cd44-positive and -negative primary osteosarcomas, including p53 apoptosis effector related to PMP-22 (Perp). Deletion of Cd44 in osteosarcoma cells led to doxorubicin-dependent p53 activation and a profound increase in Perp mRNA expression. Overall, our results suggest that CD44 might be an important regulator of drug resistance and suggest that targeting CD44 can sensitize osteosarcoma to standard chemotherapy.
How to allocate portfolio weight based on the FF3F model

Selecting the correct stocks and funds is essential for portfolio management and allocation. In order to reduce the risk of the portfolio, it is better to diversify the assets and select the stocks within more than one sector. Another step would be setting the portfolio with the firefighter case or without it. The firefighter case illustrates that we suppose there is a firefighter who has 25 years of service as a firefighter who will be retired in Florida. The Florida government gives the retired firefighter two choices. He takes the lump-sum payout and invests his nest egg and the lump sum in supporting him throughout his retirement. Another one is that he takes the pension benefit and invests his nest egg in supplementing the pension benefit. In this case, we compared those two and finally selected the one in which he maintained the pension and made the pension weight precisely equal to 71%. The Sharpe ratio for this scenario is relatively higher than the another. Moreover, choosing the correct financial model. Comparing the pros and cons between the CAPM model and the Fama French Three-Factor model, we found that the Fama French Three-Factor model is more related to reality and includes the market risk, making the portfolios more accurate and reliable.
β-Cyclodextrin/CMK-8-Based Electrochemical Sensor for Sensitive Detection of Cu2+

In this work, β-cyclodextrin (β-CD)/mesoporous carbon (CMK-8) nanocomposite was synthesized and used as an electrochemical sensing platform for highly sensitive and selective detection of Cu2+. The morphology and structure of β-CD/CMK-8 were characterized by scanning electron microscope (SEM) and X-ray diffraction (XRD). In addition, the dates from electrochemical impedance spectroscopy (EIS) and Cyclic voltammetry (CV) demonstrated that the β-CD/CMK-8 possessed a fast electronic transfer rate and large effective surface area. Besides this, the β-CD/CMK-8 composite displayed high enrichment ability toward Cu2+. As a result of these impressive features, the β-CD/CMK-8 modified electrode provided a wide linear response ranging from 0.1 ng·L−1 to 1.0 mg·L−1 with a low detection limit of 0.3 ng·L−1. Furthermore, the repeatability, reproducibility and selectivity of β-CD/CMK-8 towards Cu2+ were commendable. The sensor could be used to detect Cu2+ in real samples. All in all, this work proposes a simple and sensitive method for Cu2+ detection, which provides a reference for the subsequent detection of HMIs.