Miracle-dz/UniFAR-FTUs huggingface dataset:
Joint Task Offloading and Resource Allocation for Energy-Constrained Mobile Edge Computing

We consider the problem of task offloading and resource allocation in mobile edge computing (MEC). To maintain satisfactory quality of experience (QoE) of end-users, mobile devices (MDs) may offload their tasks to edge servers based on the allocated computation (e.g., CPU/GPU cycles and storage) and wireless resources (e.g., bandwidth). However, these resources could not be effectively utilized unless an encouraging resource allocation scheme can be proposed. What’s worse, task offloading incurs additional MEC energy consumption, which inevitably violate the long-term MEC energy budget. Considering these two challenges, we propose an online joint offloading and resource allocation (JORA) framework under the long-term MEC energy constraint, aiming at guaranteeing the end-users’ QoE. To achieve this, we leverage Lyapunov optimization to exploit the optimality of the long-term QoE maximization problem. By constructing an energy deficit queue to guide energy consumption, the problem can be solved in a real-time manner. On this basis, we propose online JORA methods in both centralized and distributed manners. Furthermore, we prove that our proposed methods enable the achievement of the close-to-optimal performance while satisfying the long-term MEC energy constraint. In addition, we conduct extensive simulations and the results show superiority in performance over other methods.
An evaluation of three different biofilm detection methods in orthopedic implant associated infections and its implication in healthcare system

: Biofilms are defined as microbially derived sessile communities characterized by the cells that are irreversibly attached to a substratum. These organisms have been associated with implant associated infectionsThe present study is therefore undertaken 1. To compare the three screening methods used for detection of biofilm formation (Tissue culture plate method, Tube method and Congo red agar method) and 2. To correlate the antibiotic resistance pattern of biofilm producers and non biofilm producers. : A prospective study was carried out in the department of microbiology, on all orthopedic implant associated infections from September 2015 to July 2016 on aspirated pus samples. A total of 120 non repetitive clinical isolates were taken and subjected to biofilm detection. All the bacterial isolates were identified by standard biochemical tests. Antibiotic susceptibility test of bacterial isolates was performed by Kirby Bauer disk diffusion method according to Clinical Laboratory Standard Institute (CLSI) guidelines on Muller Hinton Agar (MHA). A reference strain of Staphylococcus epidermidis ATCC 35984(positive biofilm producer) and Staphylococcus epidermidis ATCC 12228(non biofilm producer) were used as controls. Tissue culture plate method was considered as gold standard as it detected 25% biofilm producers which included 12% weak biofilm producers which was missed by congo red agar (CRA) and tube method (TM). Also, this correlated to methicillin resistant staphylococcus aureus (MRSA), ESBL, amp-c and MDR pattern of antibiogram. : TCP is considered as most reliable screening method for biofilm detection and should be routinely employed to prevent treatment failures as these organisms are intrinsically resistant to many antimicrobials leading to implant associated infections.
Innovation by Total Synergy:A Five-stage Model——A Case Study on Haier Group

This paper brings forward a five-stage process model for total synergy of all the innovation elements(namely strategy,technology,market,culture,institution and organization element) under the theoretical framework of Total Innovation Management(TIM),named C~3IS Model.The authors argue that,generally speaking,to achieve the ideal status of total synergy of all the innovation elements,which is the precondition of better innovation performance,it should go through five stages in sequence during the innovation process,namely Contact/Communication;Competition/Conflict;Collaboration;Integration;Synergy.Two RD projects cases from Haier Group are discussed to verify the model.
Comparison of Oral Health Status and Treatment Needs in Autistic and Non-Autistic Children

Background: Dental treatment need is identified as the greatest neglected health need of children with developmental disabilities. The most commonly known developmental disorder is autism, and there is a recent increase in the diagnosis of autism cases. The aim of this study is to bring to light that providing quality dental care and inculcating dental education programmes can significantly improve the oral conditions of institutionalized autistic children, thereby improving their lifestyle. Materials and Methods: The study conducted an institutionally based case-control study on 50 children with autism, selected from two special schools in Chennai, India. The total number of decayed, missing, and filled teeth was assessed for the institutionalized autistic group undergoing dental education programme and the non-autistic group selected from our general hospital. Oral Hygiene Index-Simplified (OHI-S) and the DMF score were also calculated for both groups. Results: There was a statistically significant difference in OHI scores between institution trained autistic children and non-autistic controls, but we found no significant difference in decayed, missing, and filled teeth. Conclusion: Autistic children exhibit good cooperation and good response to Dental education programmes, significantly improving their oral health conditions.
Factors associated with depressive symptoms in Japanese women with rheumatoid arthritis

Abstract Objectives It has been suggested that patients with RA are more likely to suffer from depression. Therefore, this study identified the factors associated with depressive states in female RA patients to inform future patient care. Methods A self-assessment questionnaire was administered to 150 female RA patients aged ≥20 years regarding their satisfaction with disease activity, pain (measured using a visual analogue scale), self-rated depression scale (SDS), stress content (illness, work, family, difficulty in daily life, appearance, treatment and other), confidence in stress management and satisfaction (treatment effect, health status and relationships with health-care professionals). The factors related to depression and the presence of depressive tendencies were investigated. Results Data from 145 patients were analysed. Eighteen patients (12.4%) showed depressive tendencies according to their SDS scores. Among these patients, SDS scores were positively correlated with disease activity and with scores on the modified HAQ, visual analogue scale for pain, and stress content. The SDS score was also negatively correlated with patients’ confidence in stress management and health status satisfaction. Conclusion Female RA patients had family problems and various stressors in their daily lives. Nurses need to conduct regular mental health assessments to monitor their self-management status and support them to improve their confidence and satisfaction in coping. To achieve this, it is important for health-care teams involving various health-care professionals to collaborate and cooperate.
Intelligent Method for Real-Time Portable EEG Artifact Annotation in Semiconstrained Environment Based on Computer Vision

As a convenient device for observing neural activity in the natural environment, portable EEG technology (PEEGT) has an extensive prospect in expanding neuroscience research into natural applications. However, unlike in the laboratory environment, PEEGT is usually applied in a semiconstrained environment, including management and engineering, generating much more artifacts caused by the subjects' activities. Due to the limitations of existing artifacts annotation, the problem limits PEEGT to take advantage of portability and low-test cost, which is a crucial obstacle for the potential application of PEEGT in the natural environment. This paper proposes an intelligent method to identify two leading antecedent causes of EEG artifacts, participant's blinks and head movements, and annotate the time segments of artifacts in real time based on computer vision (CV). Furthermore, it changes the original postprocessing mode based on artifact signal recognition to the preprocessing mode based on artifact behavior recognition by the CV method. Through a comparative experiment with three artifacts mark operators and the CV method, we verify the effectiveness of the method, which lays a foundation for accurate artifact removal in real time in the next step. It enlightens us on how to adopt computer technology to conduct large-scale neurotesting in a natural semiconstrained environment outside the laboratory without expensive laboratory equipment or high manual costs.
Impact of Surfactants on the Electrical and Rheological Aspects of Silica Based Synthetic Ester Nanofluids

This study reports experimental investigations of the effects of different surfactants (CTAB, Oleic acid and Span 80) on silica based synthetic ester nanofluids. The positive and negative potential observed for the ionic (CTAB) and non-ionic surfactant (Span 80) from zeta potential analysis indicates an improved stability. The optimization of nanofillers and surfactants is performed considering the corona inception voltage measured using ultra high frequency (UHF) technique and fluorescent fiber. Rheological analysis shows no significant variation of properties with shear rate, implying Newtonian behavior even with the addition of surfactant. In addition, the permittivity of the nanofluid is not much affected by adding surfactant but a marginal variation is noticed in the loss tangent with the effect of temperature. The fluorescence spectroscopy shows no change in the emission wavelength with the addition of silica nanofiller and surfactants. Flow electrification studies indicate an increase in the streaming current with the rotation speed and temperature, with a higher current magnitude observed in the case of nanofluids.
Heavy metals phytofiltration potential of Hydrocotyle umbellata from Nullah Lai wastewater and its environmental risk

Abstract This study aims to examine the heavy metal phytofiltration potential of Hydrocotyle umbellata from Nullah Lai wastewater and its environmental risk. Wastewater was initially analyzed for heavy metals and physicochemical parameters and compared with irrigation water standards. The phytofiltration potential of H. umbellata was determined by periodically monitoring heavy metal concentrations at time points T1 (day 05), T2 (day10), T3 (day 15), and T4 (day 20). This study shows that some water parameters reached the permissible limits after treatment with H. umbellata. Results of the risk analysis reveal a significant discharge (kg d−y) of heavy metals to arable land. Phytofiltration efficiency of H. umbellata for water quality parameters was in order of Ni (98.75%), Cr (98.11%), Cd (95.84%), Pb (94.90%), Cu (94.10%), Zn (85.34%), BOD (53.67%), TDS (29.28%), EC (27.31%), Cl (6.65%), and SAR (6.34%). The growth of H. umbellata in wastewater resulted in heavy metal bioaccumulation in both roots and shoots of the plant. Less than 01 translocation factor (TF) values for cadmium, copper, lead, chromium, and zinc showed the metal tolerance ability of the tested plant. These results demonstrated that treated water could be used in water-deficient peri-urban areas as supplementary irrigation. Novelty Statement This study evaluates the phytofiltration potential of Hydrocotyle umbellata for heavy metals (Cu, Cr, Cd, Pb, Ni, and Zn) from Nullah Lai wastewater by greenhouse experiments. The environmental risk associated with using Nullah Lai wastewater for irrigation purposes was estimated.
Oviposition site selection in the crepuscular moth, Grapholita molesta: does light matter?

Some insects that particularly prefer sunny or shaded sites use light intensity to locate suitable oviposition sites during the day. However, it is not known whether crepuscular species can be guided by light for oviposition under dim or variable light conditions. We used the crepuscular moth Grapholita molesta (Busck) (Lepidoptera: Tortricidae), a major pest of stone and pome fruits worldwide, to investigate oviposition response to light at various intensities (1000, 100, 10, and 1 mW m−2). Light intensity in sunny sites in a peach tree canopy is about 10× higher than in shaded sites. In both light vs. dark and brighter light vs. darker light choices, G. molesta females can discriminate differences in light intensity, exhibiting a strong preference for brighter light, independent of light intensity. Moreover, the light‐dependent oviposition responses did not change when exposed to odor stimuli. Our findings show that this crepuscular moth G. molesta can use light intensity to direct oviposition toward relatively sunny sites under dim light conditions. This study highlights the importance of vision for crepuscular species in oviposition site selection.
A Case of Advanced Non-Small-Cell Lung Cancer With Response to Alectinib and Favorable Quality of Life

Lung cancer is the leading cause of cancer death globally and in the United States. Non-small-cell lung cancer (NSCLC) accounts for approximately 85% of lung cancer cases. A progressive increase in morbidity and mortality is seen with advanced disease. Identifying specific driver mutations, such as anaplastic lymphoma kinase (ALK) mutations and directed therapy, has improved the quality of life and survival in ALK-positive NSCLC patients. Here, we present the case of a 37-year-old female who was diagnosed with stage IV NSCLC (adenocarcinoma) with a positive ALK mutation six years ago. Our case report highlights a rare ALK mutation NSCLC treated with targeted ALK inhibitor therapy. Despite having advanced-stage cancer, the treatment significantly impacted her survival with an improved quality of life.
Redox Hyperactive MOF for Li+, Na+ and Mg2+ Storage

To create both greener and high-power metal-ion batteries, it is of prime importance to invent an unprecedented electrode material that will be able to store a colossal amount of charge carriers by a redox mechanism. Employing periodic DFT calculations, we modeled a new metal-organic framework, which displays energy density exceeding that of conventional inorganic and organic electrodes, such as Li- and Na-rich oxides and anthraquinones. The designed MOF has a rhombohedral unit cell in which an Ni(II) node is coordinated by 2,5-dicyano-p-benzoquinone linkers in such a way that all components participate in the redox reaction upon lithiation, sodiation and magnesiation. The spatial and electronic changes occurring in the MOF after the interaction with Li, Na and Mg are discussed on the basis of calculated electrode potentials versus Li0/Li+, Na0/Na+ and Mg0/Mg2+, respectively. In addition, the specific capacities and energy densities are calculated and used as a measure for the electrode applicability of the designed material. Although the highest capacity and energy density are predicted for Li storage, the greater structural robustness toward Na and Mg uptake suggests a higher cycling stability in addition to lower cost. The theoretical results indicate that the MOF is a promising choice for a green electrode material (with <10% heavy metal content) and is well worth experimental testing.
fNIRS-Based Upper Limb Motion Intention Recognition Using an Artificial Neural Network for Transhumeral Amputees

Prosthetic arms are designed to assist amputated individuals in the performance of the activities of daily life. Brain machine interfaces are currently employed to enhance the accuracy as well as number of control commands for upper limb prostheses. However, the motion prediction for prosthetic arms and the rehabilitation of amputees suffering from transhumeral amputations is limited. In this paper, functional near-infrared spectroscopy (fNIRS)-based approach for the recognition of human intention for six upper limb motions is proposed. The data were extracted from the study of fifteen healthy subjects and three transhumeral amputees for elbow extension, elbow flexion, wrist pronation, wrist supination, hand open, and hand close. The fNIRS signals were acquired from the motor cortex region of the brain by the commercial NIRSport device. The acquired data samples were filtered using finite impulse response (FIR) filter. Furthermore, signal mean, signal peak and minimum values were computed as feature set. An artificial neural network (ANN) was applied to these data samples. The results show the likelihood of classifying the six arm actions with an accuracy of 78%. The attained results have not yet been reported in any identical study. These achieved fNIRS results for intention detection are promising and suggest that they can be applied for the real-time control of the transhumeral prosthesis.
Underwater Drone Architecture for Marine Digital Twin: Lessons Learned from SUSHI DROP Project

The ability to observe the world has seen significant developments in the last few decades, alongside the techniques and methodologies to derive accurate digital replicas of observed environments. Underwater ecosystems present greater challenges and remain largely unexplored, but the need for reliable and up-to-date information motivated the birth of the Interreg Italy–Croatia SUSHI DROP Project (SUstainable fiSHeries wIth DROnes data Processing). The aim of the project is to map ecosystems for sustainable fishing and to achieve this goal a prototype of an Unmanned Underwater Vehicle (UUV), named Blucy, has been designed and developed. Blucy was deployed during project missions for surveying the benthic zone in deep waters of the Adriatic Sea with non-invasive techniques compared to the use of trawl nets. This article describes the strategies followed, the instruments applied and the challenges to be overcome to obtain an accurately georeferenced underwater survey with the goal of creating a marine digital twin.
Current State of Hyperspectral Remote Sensing for Early Plant Disease Detection: A Review

The development of hyperspectral remote sensing equipment, in recent years, has provided plant protection professionals with a new mechanism for assessing the phytosanitary state of crops. Semantically rich data coming from hyperspectral sensors are a prerequisite for the timely and rational implementation of plant protection measures. This review presents modern advances in early plant disease detection based on hyperspectral remote sensing. The review identifies current gaps in the methodologies of experiments. A further direction for experimental methodological development is indicated. A comparative study of the existing results is performed and a systematic table of different plants’ disease detection by hyperspectral remote sensing is presented, including important wave bands and sensor model information.
Measurement System for Unsupervised Standardized Assessments of Timed Up and Go Test and 5 Times Chair Rise Test in Community Settings—A Usability Study

Comprehensive measurements are needed in older populations to detect physical changes, initiate prompt interventions, and prevent functional decline. While established instruments such as the Timed Up and Go (TUG) and 5 Times Chair Rise Test (5CRT) require trained clinicians to assess corresponding functional parameters, the unsupervised screening system (USS), developed in a two-stage participatory design process, has since been introduced to community-dwelling older adults. In a previous article, we investigated the USS’s measurement of the TUG and 5CRT in comparison to conventional stop-watch methods and found a high sensitivity with significant correlations and coefficients ranging from 0.73 to 0.89. This article reports insights into the design process and evaluates the usability of the USS interface. Our analysis showed high acceptance with qualitative and quantitative methods. From participant discussions, suggestions for improvement and functions for further development could be derived and discussed. The evaluated prototype offers a high potential for early detection of functional limitations in elderly people and should be tested with other target groups in other locations.
Analysis of Global Gene Expression in Maize (Zea mays) Vegetative and Reproductive Tissues That Differ in Accumulation of Starch and Sucrose

Carbon allocation between vegetative and reproductive tissues impacts cereal grain production. Despite great agricultural importance, sink–source relationships have not been fully characterized at the early reproductive stages in maize. Here, we quantify the accumulation of non-structural carbohydrates and patterns of gene expression in the top internode of the stem and the female inflorescence of maize at the onset of grain filling (reproductive stage R1). Top internode stem and female inflorescence tissues of the Puma maize inbred line were collected at reproductive stage R1 (without pollination) and non-structural carbohydrates were quantified by spectrophotometry. The female inflorescence accumulated starch at higher levels than the top internode of the stem. Global mRNA transcript levels were then evaluated in both tissues by RNA sequencing. Gene expression analysis identified 491 genes differentially expressed between the female inflorescence and the top stem internode. Gene ontology classification of differentially expressed genes showed enrichment for sucrose synthesis, the light-dependent reactions of photosynthesis, and transmembrane transporters. Our results suggest that sugar transporters play a key role in sugar partitioning in the maize stem and reveal previously uncharacterized differences between the female inflorescence and the top internode of the stem at early reproductive stages.
Germacrone alleviates okadaic acid-induced neurotoxicity in PC12 cells via M1 muscarinic receptor-mediated Galphaq (Gq)/phospholipase C beta (PLCβ)/ protein kinase C (PKC) signaling

ABSTRACT Alzheimer’s disease (AD) is a neurodegenerative disorder with prominent individual morbidity and mortality among elderly people. Germacrone (Germ) has been reported to exert dominant protective roles in multiple human diseases, and neurological diseases are also included. The intention of this paper is to determine the impacts of Germ on okadaic acid (OA)-treated PC12 cells and confirm the hidden regulatory mechanism. First, PC12 cells were induced by OA in the absence or presence of Germ. Cell counting kit-8 assay was to monitor cell proliferation. Western blot was to test the protein levels of cholinergic muscarinic M1 receptor (CHRM1), Galphaq (Gq), phospholipase C beta (PLCβ) and protein kinase C (PKC). The levels of reactive oxygen species (ROS) and other oxidative stress markers were evaluated using corresponding kits. ELISA was used to estimate the levels of AD markers. RT-qPCR was used to examine the mRNA levels of beta-site amyloid-precursor-protein-cleaving enzyme 1 (BACE-1) and apolipoprotein E (APOE). The results uncovered that Germ enhanced the proliferation of OA-insulted PC12 cells, elevated the protein level of CHRM1 and activated the Gq/PLCβ/PKC signaling. Moreover, after OA-induced PC12 cells were administered with Germ, insufficiency of CHRM1 impeded cell proliferation, enhanced oxidative stress and neuron injury and inactivated the Gq/PLCβ/PKC signaling. Furthermore, the addition of Gq inhibitor UBO-QIC, PLCβ inhibitor U73122 or PKC inhibitor Go6983 reversed the enhanced proliferation, the reduced oxidative stress and neuron injury in OA-treated PC12 cells caused by Germ. Collectively, Germ modulated M1 muscarinic receptor-mediated Gq/PLCβ/PKC signaling, thereby alleviating OA-induced PC12 cell injury. Graphical Abstract