Miracle-dz/UniFAR-FTUs huggingface dataset:
Model-Assisted Reduced-Order ESO Based Command Filtered Tracking Control of Flexible-Joint Manipulators with Matched and Mismatched Disturbances

Flexible-joint manipulators (FJMs) have been widely used in the fields of industry, agriculture, medical service, aerospace, etc. However, the FJMs in practical applications inevitably encounter various uncertainties including matched and mismatched disturbances. In this paper, we consider the high precision tracking control problem of FJMs in the presence of unknown lumped matched and mismatched disturbances. An efficient model-assisted composite control approach is proposed by integrating two reduced-order extended state observers (RESOs), a second-order command filtered backstepping (SCFB) technique and an error compensation dynamic system. Unlike some existing methods, the RESOs constructed with partial known model information are capable of estimating and compensating the matched and mismatched disturbances simultaneously. In addition, by employing the SCFB with an error compensation system, the proposed approach can not only overcome the problem of “explosion of complexity” inherent in backstepping, but also reduce the filtering errors arising from the command filters. The stability of the resulting control system and the convergence of error signals are guaranteed by Lyapunov stability theory. Comparative simulations are conducted for a single-link FJM with both matched and mismatched disturbances, and the results show that the proposed approach achieves a better tracking performance, i.e., compared with conventional backstepping method and adaptive fuzzy command filtered control method, the tracking accuracy is improved by 99.5% and 99.2%, respectively.
On Turbo Base-Station Cooperation for Improving the Performance of Cellular Systems

Interference can be mitigated by appropriate signal processing techniques. Sophisticated schemes have been proposed and investigated in order to cancel the intracell interference, e.g., multiuser detection [1], beamforming, or sectorization. However, intercell interference contributes significantly to the system degeneration and the search for a powerful intercell interference cancellation technique is still a demanding topic. Motivated by the significant benefits of joint detection and cooperation for intracell interference cancellation, a joint detection, in specific an iterative cooperation between base-stations, was proposed in [2], in order to mitigate intercell interference, and denoted as Turbo Base-Station Cooperation (Turbo BASCO). In general, all base-stations are connected through some network. The key point of Turbo BASCO is that base-stations, or more specifically signal detectors located at different basestations, exchange valuable information in order to help each other. The cooperation can be applied in several ways. For comparison, the conservative strategy (i.e., a reference case when considering Turbo BASCO) detects the received signals yi without the knowledge of interference, just considering them as additional noise. Then, the detected messages ui are transmitted through the network and forwarded through the Internet to its destination. A first technique of Turbo BASCO, denoted as Common Signal Detector, centralizes the signal processing to a common processor node and is sketched in Fig. 1. The local base-stations forward their received signal values yi to a joint detector through the network. As the transmission of supporting information is through the network, the values have to be quantized for all applied Turbo BASCO schemes.
An Application of Machine Learning Algorithms on the Finger Image Prediction

In recent years, using machine learning (ML) algorithm to analyze a picture, obtain its features, and finally identify what the picture is about is getting more and more important. This is because with the popularity of the electronic equipment and high-performance computing equipment, people began to pursue a more convenient and automatic life. The science of the image recognition frees people’s hands to a certain extent through the training of algorithms, thus making people’s life more convenient. This paper presents a comparison of two ML algorithms: Multi-layer Perceptron (MLP), and Convolutional Neural Network (CNN) with three different optimization methods on the data-set by measuring their test accuracy and their running time. The said data-set consists of a training-set of 1080 pictures (64 by 64 pixels) of signs representing numbers from 0 to 5 (180 pictures per number) and a test set of 120 pictures (64 by 64 pixels) of signs representing numbers from 0 to 5 (20 pictures per number). For the implementation of the ML algorithms, the data-set was partitioned in the following fashion: 90% for training phase, and 10% for testing phase. The hyper-parameters used for all the classifiers were manually assigned. Results show that most of the presented ML algorithms performed not bad with a test accuracy over 80%, and the CNN algorithm performed best among all the implemented algorithms with a test accuracy about 91.04%.
The Impact of Pharmacist-Led Medication Management Services on the Quality of Life and Adverse Drug Reaction Occurrence

The aim of this research was to assess the impact of comprehensive medication management (CMM) services on patients’ health-related quality of life (HRQoL) and frequency of adverse drug reactions (ADRs) in older patients with cardiovascular diseases (CVDs). A prospective, pre- and post-intervention study with a one-year follow-up was conducted at the Health Care Centre Zagreb—Centre (HCZC). The Euro-Quality of Life Questionnaire 5 Dimensions 5 Levels (EQ-5D-5L) was used to measure the HRQoL at baseline (initial visit at the HCZC) and 12 months following CMM services. The ADRs collected at the initial assessment of the CMM services and throughout follow-up consultations were analyzed according to the occurrence mechanism, seriousness, expectedness and distribution of the Preferred Term according to the System Organ Class. Following the CMM intervention, 65 patients reported significant improvement in dimensions “self-care” (p = 0.011) and “usual activities” (p = 0.003), whereas no significant change was found in the “mobility” (p = 0.203), “pain/discomfort” (p = 0.173) and “anxiety/depression” (p = 0.083) dimensions and the self-rated VAS scale (p = 0.781). A total of 596 suspected ADR reports were found, the majority at patients’ initial assessment (67.3%), with a mean ± SD of 9.2 ± 16.9 per patient. The CMM services significantly reduced the rate of suspected ADRs, namely 2.7 ± 1.7 ADRs per patient at the initial assessment vs. 1.0 ± 1.5 ADRs per patient at the last consultation (p < 0.001). The obtained results indicate that CMM services may improve patients’ HRQoL. Additionally, as CMM services diminished the proportion of ADRs following 1-year patient follow-up, they may serve as a viable solution for safety management.
PREGNANT AND LACTATING Macaca nigra: BEHAVIOR AND FOOD SELECTION

Pregnancy and lactation are reproductive phases that require large amounts of energy. Females in the reproductive period need good quality and quantity of food to provide nutrition for the fetus, milk production and child care. The mother will adapt to changes in behavior patterns and food type to meet these needs. The influence of parity and environmental conditions can affect the behavior patterns of females. During pregnancy, the Macaca nigra is known to have different proportion of activities in each period, while the behavior during the lactation phase in each mester is unknown. Therefore, this study aimed to analyze the behavior patterns in each mester and the food selection of Macaca nigra during the pregnancy and lactation phases, as well as the influence of female parity and environmental toward the behavior patterns. There were 39 females Macaca nigra observed from two groups from August 2018 to July 2019. An instantaneous focal sampling method was performed to observe females’ daily activities, continuous focal sampling to monitor food types and a selectivity index to analyze food type preferences. The results showed that the female Macaca nigra pattern was influenced by the reproductive phase, female parity and environmental conditions. Females at the end of the pregnancy and lactation phases had a high proportion of feeding and eat more arthropods. Primiparous females mostly performed resting activities. Food preference was influenced by reproductive factors and food availability. The choice of fruit could be affected by fruit availability, and their favorite food was D. mangiferum and Euginia sp.
Habitat value of subsea wells and pipelines for fishery target species in Australia

Subsea pipelines and wells installed to support the oil and gas industry represent some of the most extensive and numerous anthropogenic structures throughout global marine ecosystems. There remains a paucity of information on the habitat value of these structures for fishery target species and, as a result, little understanding of how decommissioning should be conducted to minimise impacts to populations of these economically and socially important species. We assess the diversity and abundance of species that are targets of recreational and commercial fisheries on 33 subsea wells and 17 pipelines across the tropical northwest and temperate southeast marine regions of Australia. We examine relationships between fish identity and abundance and a range of environmental (e.g., depth, location), infrastructure-specific (e.g., pipeline position, diameter, age, length of pipeline, height of well, position on well), and biological (% cover of epibiota) variables using video filmed by remotely operated vehicles during their routine offshore inspection and maintenance campaigns. A total of 100 fishery target species were observed across subsea well and pipeline infrastructure, 56 species uniquely observed on pipelines and nine unique to wells. The families Lutjanidae (snapper), Serranidae (rock cods, groupers, perch), and Carangidae (trevallies) were most common and abundant on both wells and pipelines. In the northwest, lutjanids were most abundant around the base of wells, in shallow depths, on shorter wells, and where pipelines spanned the seafloor. A greater number of fishery target species and abundance of ocean perch (Helicolenus spp.) were also associated with pipelines that spanned the seafloor in temperate southeast Australia. The combined biomass of three species of snapper on wells in the northwest was 1,270 kg, with production levels for these species on each well estimated to be 105.2 g m2 year-1. The present study serves as an important reference point for informing decommissioning decisions for pipeline and well infrastructure and demonstrates the utility of industry-held data for science. We suggest that key predictor variables identified here be incorporated into comprehensive before-after-control-impact scientific studies for specific fields/assets to enable the prediction of potential impacts of decommissioning scenarios on marine communities present and quantification of such impacts after the decommissioning activity has occurred.
MYCN and Metabolic Reprogramming in Neuroblastoma

Simple Summary Metabolic reprogramming has a central role in the initiation and progression of cancer, including high-risk neuroblastoma, a deadly childhood malignant tumor of the sympathetic nervous system. This rewiring of cellular metabolism increases the manufacture of fuel and building blocks for biomass production, which is essential to sustain the growth and proliferation of neuroblastoma cells. However, the rewiring also makes neuroblastoma cells metabolically distinct from normal sympathetic neurons, thereby offering new therapeutic opportunities. In this review, we summarize the recent progress in the study of neuroblastoma metabolic reprogramming and underlying molecular mechanisms. Abstract Neuroblastoma is a pediatric cancer responsible for approximately 15% of all childhood cancer deaths. Aberrant MYCN activation, as a result of genomic MYCN amplification, is a major driver of high-risk neuroblastoma, which has an overall survival rate of less than 50%, despite the best treatments currently available. Metabolic reprogramming is an integral part of the growth-promoting program driven by MYCN, which fuels cell growth and proliferation by increasing the uptake and catabolism of nutrients, biosynthesis of macromolecules, and production of energy. This reprogramming process also generates metabolic vulnerabilities that can be exploited for therapy. In this review, we present our current understanding of metabolic reprogramming in neuroblastoma, focusing on transcriptional regulation as a key mechanism in driving the reprogramming process. We also highlight some important areas that need to be explored for the successful development of metabolism-based therapy against high-risk neuroblastoma.
A Review on Recent Advancements of Ni-NiO Nanocomposite as an Anode for High-Performance Lithium-Ion Battery

Recently, lithium-ion batteries (LIBs) have been widely employed in automobiles, mining operations, space applications, marine vessels and submarines, and defense or military applications. As an anode, commercial carbon or carbon-based materials have some critical issues such as insufficient charge capacity and power density, low working voltage, deadweight formation, short-circuiting tendency initiated from dendrite formation, device warming up, etc., which have led to a search for carbon alternatives. Transition metal oxides (TMOs) such as NiO as an anode can be used as a substitute for carbon material. However, NiO has some limitations such as low coulombic efficiency, low cycle stability, and poor ionic conductivity. These limitations can be overcome through the use of different nanostructures. This present study reviews the integration of the electrochemical performance of binder involved nanocomposite of NiO as an anode of a LIB. This review article aims to epitomize the synthesis and characterization parameters such as specific discharge/charge capacity, cycle stability, rate performance, and cycle ability of a nanocomposite anode. An overview of possible future advances in NiO nanocomposites is also proposed.
On the Workspace of Electromagnetic Navigation Systems

In remote magnetic navigation, a magnetic navigation system is used to generate magnetic fields to apply mechanical wrenches to steer a magnetic object. This technique can be applied to navigate untethered micro- and nanorobots, as well as tethered magnetic surgical tools for minimally invasive medicine. The design and characterization of these systems have been extensively investigated over the past decade. The determination of the region in space in which these systems can operate has yet to be formalized within the research community. This region is commonly referred to as the “workspace” and constitutes a central concept for any class of robotic system. We focus on magnetic navigation systems comprised of electromagnets and propose a first set of definitions for a magnetic workspace, a methodology to determine it, and evaluation metrics to analyze its characteristics. Our methodology and tools are illustrated with several examples of planar and spatial electromagnetic magnetic navigation systems for both didactic and realistic navigation scenarios.
Hydrogen-ion Toxicity on Citrus1

Young ‘Rough’ lemon seedlings were grown in nutrient solutions adjusted to pH 4. 5, and 6 with three mineral acids. The sources of H+ were HNO3, H2SO4, and H3PO4. All plants produced healthy new leaves but growth was markedly reduced at pH 4. New roots were short and thickened at pH 4 and less dry matter was produced. At pH 5, the roots were less elongated than at pH 6 but plant weight was unaffected. All three acids produced similar effects, indicating that the source of H+ was not important. Reduction in growth was associated with excess H+ and abnormal root development.
A Review of the Role of Oral Microbiome in the Development, Detection, and Management of Head and Neck Squamous Cell Cancers

Simple Summary Head and neck squamous cell cancers (HNSCC) are the seventh most common form of cancer in the United States. Though the role of the microbiome in the development of other diseases of the aerodigestive tract is well defined, the role of the microbiome in HNSCC is a developing subject. The notion of harnessing the microbiome for the prevention, detection, and treatment of HNSCC is an exciting new prospect in oncology. This manuscript discusses what is known about the healthy oral microbiome, the microbiome unique to premalignant lesions of the head and neck, the microbiome of HNSCC, and the microbiome as a modulator of immunity and malignancy. The manuscript also discusses clinical applications of the microbiome as they relate to HNSCC, including relationships between the microbiome and outcome data, and treatment toxicities. The aim of this review is to guide future research and clinical trials on the microbiome with the hopes of improving screening techniques, decreasing treatment toxicities, and improving survival for patients with HNSCC. Abstract The role of the microbiome in the development and propagation of head and neck squamous cell cancer (HNSCC) is largely unknown and the surrounding knowledge lags behind what has been discovered related to the microbiome and other malignancies. In this review, the authors performed a structured analysis of the available literature from several databases. The authors discuss the merits and detriments of several studies discussing the microbiome of the structures of the aerodigestive system throughout the development of HNSCC, the role of the microbiome in the development of malignancies (generally and in HNSCC) and clinical applications of the microbiome in HNSCC. Further studies will be needed to adequately describe the relationship between HNSCC and the microbiome, and to push this relationship into a space where it is clinically relevant outside of a research environment.
Synergetic Chemo‐Piezodynamic Therapy of Osteosarcoma Enabled by Defect‐Driven Lead‐Free Piezoelectrics

Osteosarcoma (OS) is a lethal malignancy of the bone, jeopardizing the life of an enormous population worldwide. There are grand ongoing challenges to improve overall patient survival. Herein, a synergetic chemo‐piezodynamic therapy by defect‐engineered lead‐free piezoelectric (K,Na)NbO3 (KNN) is reported, which can generate reactive oxygen species (ROS) to effectively circumvent OS. Significant anti‐tumor effects in human OS cells, and xenograft OS models are observed that almost stop the growth of the tumors after treatment with KNN because of oxygen vacancies‐driven free radical catalysis (namely, the chemodynamic therapy), and those effects are enhanced after introducing ultrasonic vibration enabled by the ultrasound‐triggered piezocatalysis (piezodynamic therapy). Moreover, it is found that KNN induces apoptosis and autophagy of OS cells and shows good histocompatibility on evaluation in mouse models, which has no killing effect on normal cells and no toxic effects on organs in vivo. Both in vitro cellular level evaluation and in vivo OS xenograft assessment have demonstrated that injectable KNN nanocrystals induce cytotoxicity and tumor eradication by the synergy of chemo‐piezocatalytic effects. This study opens an avenue for customized design of high‐tech nanocatalysts by integrating synergetic catalytic effects for therapeutic applications in tumor healthcare.
Optimal Operation of Microgrids Comprising Large Building Prosumers and Plug-in Electric Vehicles Integrated into Active Distribution Networks

Active distribution networks and microgrids will be powerful tools for future power systems in their endeavor to integrate more renewable energy sources, increase distributed generation and optimize their operation. In this paper, a method for the coordinated optimal operation scheduling of active distribution networks that are hosting complex microgrids comprising large building prosumers and plug-in electric vehicle aggregators is proposed. The electrical and thermal power systems of the microgrid are modelled in detail while the examined active distribution network is assumed to be able to optimally shift part of its loads in time and comprises renewable energy sources as part of its local generation. Moreover, the microgrid is assumed to be able to shift part of its load in order to assist the active distribution network in order to satisfy all of the network constraints when this is required. The proposed method was developed in such a way that allows both the microgrid and the active distribution network to optimize their operations without exchanging the internal information comprising their technical characteristics and parameters. To this end, the method is organized into five levels wherein only the absolutely necessary information is exchanged, i.e., the power that is exchanged by the microgrid and the active distribution network and the time periods in which the network constraints are violated.
Development of a Thermodynamic Model of the Human Skin Development of a Thermodynamic Model of the Human Skin

Active thermal imaging can be used for medical examination of human skin diseases. During this process, the skin surface is subjected to thermal excitation by either cooling or heating and the radiation emitted by the skin surface is measured and imaged. However, due to the complex structure of the human skin, the interpretation of measured data is very difficult and not yet fully understood. Many heat transport models of human skin have been developed to solve this problem. Most of them are based on the Pennes equation for heat distribution within biological tissue. Sensitivity analyses have shown that blood perfusion exhibits a strong influence on thermal response of the skin temperature during cooling and reheating. Against this backdrop, we want to understand the role perfusion rate plays for simulating the temperature distribution within human skin during thermal stimulation and how the stimulation can be optimized. In the presented study, three different approaches for modelling the perfusion are implemented in a 1D thermodynamic model, the classical Pennes approach for constant blood perfusion within biological tissue, an advanced Pennes approach with linear temperature dependent perfusion, and a new approach where the blood is assumed to flow in a vertical loop through the skin. The surface temperature response to cooling and reheating is evaluated and compared. The new approach exhibited greater agreement with measurement data and allowed the simulation of realistic body temperature regulation behavior. Different durations and strengths of thermal stimulations are simulated and compared. The simulations for optimal thermal stimulation yielded a better understanding of the influence of the stimulation on the temperature distribution within human skin. A process for finding an optimal range of the strength and duration of the thermal stimulation was developed.