Miracle-dz/UniFAR-FTUs huggingface dataset:
Laser Synthesized Core-Satellite Fe-Au Nanoparticles for Multimodal In Vivo Imaging and In Vitro Photothermal Therapy

Hybrid multimodal nanoparticles, applicable simultaneously to the noninvasive imaging and therapeutic treatment, are highly demanded for clinical use. Here, Fe-Au core-satellite nanoparticles prepared by the method of pulsed laser ablation in liquids were evaluated as dual magnetic resonance imaging (MRI) and computed tomography (CT) contrast agents and as sensitizers for laser-induced hyperthermia of cancer cells. The biocompatibility of Fe-Au nanoparticles was improved by coating with polyacrylic acid, which provided excellent colloidal stability of nanoparticles with highly negative ζ-potential in water (−38 ± 7 mV) and retained hydrodynamic size (88 ± 20 nm) in a physiological environment. The ferromagnetic iron cores offered great contrast in MRI images with r2 = 11.8 ± 0.8 mM−1 s−1 (at 1 T), while Au satellites showed X-ray attenuation in CT. The intravenous injection of nanoparticles enabled clear tumor border visualization in mice. Plasmonic peak in the Fe-Au hybrids had a tail in the near-infrared region (NIR), allowing them to cause hyperthermia under 808 nm laser exposure. Under NIR irradiation Fe-Au particles provided 24.1 °C/W heating and an IC50 value below 32 µg/mL for three different cancer cell lines. Taken together, these results show that laser synthesized Fe-Au core-satellite nanoparticles are excellent theranostic agents with multimodal imaging and photothermal capabilities.
Surface Deformation of Expansive Soil at Ankang Airport, China, Revealed by InSAR Observations

Ankang Airport is constructed on an expansive soil-fill platform in Shaanxi Province, Central China. Since its completion in 2020, it has suffered surface deformation caused by the consolidation and settlement of the fill layer and instability of the expansive soil slope. Exploring the special deformation law of expansive soil regions by remote sensing and analyzing the deformation characteristics of airports in mountainous areas have always been key issues in related disaster research. Based on the intensity and phase observation data of 37 Sentinel-1 synthetic aperture radar images, this study obtained the spatio-temporal distribution of the deformation of Ankang Airport from May 2020 to October 2021. First, phase optimization was performed on the original interferograms. Second, the persistent scatterer synthetic aperture radar interferometry (PS-InSAR) method was applied to extract the surface deformation information of Ankang Airport, and the accuracy was evaluated. Finally, the singular spectrum analysis method was introduced to jointly analyze the deformation information obtained by the InSAR technology in combination with geological and climatic data. The results show that the excavation area of Ankang Airport was basically stable, the filling area had obvious surface and uneven deformation, and the expansive soil fill slope exhibits deformation characteristics strongly related to slope, rainfall, and fill depth. The deformation was mainly caused by consolidation and settlement, supplemented by the expansion and shrinkage deformation of the expansive soil.
Energy utilisation strategy in an offshore floating wind system with variable production of fresh water and hybrid energy storage

ABSTRACT Renewable energy sources increase their share in the energy mix and, therefore it is important to accommodate variability in energy production. In this study, a hybrid approach is evaluated where a combination of batteries and compressed air are used together with seawater reverse osmosis in order to match renewable energy against electricity and water needs. Especially in remote islands renewable energy-powered desalination is an attractive option. These technologies are tested on a semi-submersible floating platform, accommodating an offshore wind turbine, a photovoltaic system and a reverse osmosis seawater desalination. The floating offshore system can deliver both fresh water and electricity in a dynamic configuration. Simulations of different operating strategies have been examined and show that sustainable solutions can be achieved.
Multiscale and Hierarchical Feature-Aggregation Network for Segmenting Medical Images

We propose an encoder–decoder architecture using wide and deep convolutional layers combined with different aggregation modules for the segmentation of medical images. Initially, we obtain a rich representation of features that span from low to high levels and from small to large scales by stacking multiple k × k kernels, where each k × k kernel operation is split into k × 1 and 1 × k convolutions. In addition, we introduce two feature-aggregation modules—multiscale feature aggregation (MFA) and hierarchical feature aggregation (HFA)—to better fuse information across end-to-end network layers. The MFA module progressively aggregates features and enriches feature representation, whereas the HFA module merges the features iteratively and hierarchically to learn richer combinations of the feature hierarchy. Furthermore, because residual connections are advantageous for assembling very deep networks, we employ an MFA-based long residual connections to avoid vanishing gradients along the aggregation paths. In addition, a guided block with multilevel convolution provides effective attention to the features that were copied from the encoder to the decoder to recover spatial information. Thus, the proposed method using feature-aggregation modules combined with a guided skip connection improves the segmentation accuracy, achieving a high similarity index for ground-truth segmentation maps. Experimental results indicate that the proposed model achieves a superior segmentation performance to that obtained by conventional methods for skin-lesion segmentation, with an average accuracy score of 0.97 on the ISIC-2018, PH2, and UFBA-UESC datasets.
Computational Analysis of Expression Based Regulation in Psoriasis: An Approach of Systems Biology to Understand Disease Pathology and Predict Potential Regulators

In the era of post genomics, computational analysis of expression based regulation in Psoriasis by the approach of Systems Biology to understand the pathology of disease and predicting a potential regulator is a challenging task to execute. The challenge was approached on the context of bottom-up approach [Expression analysis of Psoriasis associated genes from RNA Seq data with text mining of regulators (microRNAs and Transcription Factors)] to construct and analyze the network by the approach of Systems Biology for understanding the disease pathology and predict potential regulators to enhance the discovery of biomarker for Psoriasis in future.
Texas panhandle beef production tour, a high-impact compressed course in animal science

Abstract Many animal science students have little exposure to working livestock production systems prior to college. As such, they can lack insight into day-to-day challenges and rationale behind decision making in these systems, opening the door for the adoption of misconceptions frequently promoted in the popular press. In addition, students identify a lack of first-hand knowledge and experience in the industry as a challenge to their educational success. Field trips stimulate interest and motivation, provide context for learning, and influence long-term career goals, but are underutilized in higher education. The potential impact of such experiences prompted the creation of the Texas Panhandle Beef Production Tour, a 2-credit hour compressed course. Students on this tour visited beef production sites in the Texas Panhandle ranging from cow-calf operations, to feedlots and packing plants. To cement learning through reflection, students responded to a series of questions before, during, and after visiting these sites to probe preconceptions, observations, and outcomes of the experience. We performed a retroactive qualitative evaluation of these reflections (n = 22) to determine cogent themes. Emergent themes included surprise at the intensive systems of data collection and management and the level of technology used at each site. Cattle were calmer and more comfortable than expected at the feedlots and packing plants. Students expressed new appreciation and understanding of course material and a desire to share their insights with others after completing the tour. Finally, participants gained a broader view of industry opportunities and returned with renewed motivation to pursue additional hands-on opportunities. Participation in this course provided valuable insight into the livestock production industry and motivated students to explore new career options and address their own preconceptions of the industry through independent inquiry. The creation of similar courses may be useful to address misconceptions, create personal connections with course material, and broaden career interests in animal science students.
Social Frailty and Health-Related Quality of Life in Community-Dwelling Older Adults

This study aimed to identify the association between social frailty and health-related quality of life (HRQoL) and to identify the factors influencing HRQoL in community-dwelling older adults in South Korea. This was a secondary analysis of a cross-sectional survey study of 735 older adults. HRQoL was measured using the EuroQoL-5 Dimension, and social frailty was measured using five items. The differences in HRQoL according to sociodemographic characteristics, health-related characteristics, and social frailty of subjects were tested using the Mann–Whitney test, Kruskal–Wallis test, and χ2 test. A Tobit regression model was used to identify the influencing factor of HRQoL. About 31.0% of the older adults were in a social pre-frailty state, and 48.4% were in a social frailty state. Of the five components of social frailty, going out less compared to the previous year and being alone were frequently observed. Older adults who had social frailty had lower HRQoL scores than those who were robust after controlling for sociodemographic and health-related characteristics (BT = −0.04, p < 0.001). Researchers need to consider older adults’ social frailty as well as health status and sociodemographic status in future interventions to improve the HRQoL of older adults.
Characteristics of Economic and Environmental Benefits of Shore Power Use by Container-Ship Size

To combat climate change, efforts to reduce greenhouse gas (GHG) emissions are being made in all industries. The shipping sector is also one of the industries that emits GHG, including carbon. One way to reduce GHG emissions in the shipping sector is to use shore power (SP) rather than auxiliary engines during berthing. Port authorities are actively expanding SP facilities because it is possible to achieve the long-term goals of environmental benefits and green ports. However, the low economic feasibility of SP is a stumbling block for ship operators. Therefore, in this study, an economic analysis of SP use was conducted by container-ship size from the perspective of ship operators in consideration of benefits from differences in fuel oil and electricity prices, benefits through carbon emission reduction, and incentives from the port authorities. The result of the analysis showed that the benefit from the price of oil as well as the converted benefit from carbon emission reduction increased according to the size of the vessels. The economic analysis of a single port confirmed that small ships providing feeder services presented economic feasibility due to low installation costs and increased number of calls, while insufficient economic feasibility was presented for large ships above the old Panamax class due to the increased costs for installation. However, economic feasibility differs widely depending on whether port incentives are provided, and it was estimated that even large ships will be able to secure the economic feasibility of using SP if additional calls are made to ports that provide similar policy advantages.
Assessment and Promotion Strategy of Rural Resilience in Yangtze River Delta Region, China

The Yangtze River Delta region is the most economically active and open region in China. It is also the region with the most prominent contradictions between urban and rural development. Therefore, it is necessary to strengthen the resilience of the rural areas in this region so that they can develop further with resources and opportunities after sustaining shocks. This study used a weighted TOPSIS method to measure the rural resilience of 153 research units from 2000 to 2019 and then applied the ESDA method to measure the spatial agglomeration or heterogeneity characteristics. The results show that: (1) The rural resilience of this region is higher in the east and lower in the west; (2) rural resilience has obvious spatial agglomeration characteristics, which have undergone a process of shifting from strong to weak before becoming strong again; and (3) the hotspots of rural resilience gradually shifted from Jiangsu to Zhejiang, while the coldspots gradually shifted from Zhejiang to Anhui. Finally, the K-means clustering algorithm was applied to divide all research units into five types: natural capital-dominated areas, productive capital-dominated areas, human capital-dominated areas, social-financial capital-dominated areas and general development areas. Then, the strategies for resilience promotion were proposed accordingly.
Efficient Prediction of Stock Price Using Artificial Neural Network Optimized Using Biogeography-Based Optimization Algorithm

Stock market price prediction has always draws more attention from researchers and analysts. Prediction of stock price is extremely tough task due to the nature of stock data. Therefore, it is needed to develop an efficient model for predicting stock price. This paper explored the use of Feed Forward Neural Network (FFNN) and bio inspired algorithms to develop two efficient models for prediction. The proposed model is based on the ten indicators derived from historical data. Particle Swarm Optimization (PSO) algorithm which inspired from the behavior of bird flocking and Biogeography Based Optimization (BBO) algorithm driven by the geographical distribution of biological organisms is adopted to optimize the parameters of FFNN. Prediction ability of the proposed models is evaluated by using statistical measures. The experimental results demonstrate that the proposed BBO-FFNN is superior to PSO-FFNN and existing methods taken for comparison in terms of prediction accuracy. It is proved that the proposed BBO-FFNN can effectively enhance stock prediction and reduce the prediction error.
Feature selection based on genetic algorithm for transient stability assessment

Aimed at the disadvantages existing in feature selection by traditional combination optimization method in PCA(Principal Component Analysis), a new method based on genetic algorithm to select the input features is put forward. In this approach, the feature set to describe the system status and post-fault network configuration change are selected for transient stability assessment and the initial data is preprocessed by dynamic clustering analysis firstly. With the within-class/between-class distance criterion used as fitness function, a binary genetic algorithm is employed to select an effective subset of features forming the feature set after PCA, and the input dimension is reduced remarkably. As an example, the 3-machine 9-bus WSCC system and the 10-machine 39-bus New England system are used for simulation. The results reveals the validity of the proposed approach.
Age-Related Differences in Psychological Distress during the COVID-19 Pandemic

While the negative impact of COVID-19 total lockdown on mental health in youth has been extensively studied, findings collected during subsequent waves of the pandemic, in which restrictive rules were more eased, are very sparse. Here, we explore perceived psychological distress during the partial lockdown of the third wave in Southern Italy in a large sample of students, focusing on age and gender differences. Also, we assessed whether attending the type of education could have a protective role on students’ psychological well-being. An online survey was completed by 1064 southern Italian students (age range: 8–19 years; males = 368) from March to July 2021. The survey consists of a set of questions regarding general sociodemographic information as well as several aspects of students’ psychological well-being. Psychological distress was higher in high school students compared to both elementary and middle ones. In addition, we found gender differences, but only in high school students, with females reporting higher psychological distress than males. Finally, our mediation analysis showed a mediated role of face-to-face schooling in the relationship between age and psychological distress. In conclusion, this study highlights age-related differences in psychological distress during the pandemic and the protective role of school in presence for mental health in Italian students.
Investigation and analysis of groundwater heat pump application

Ground source heat pump has the characteristic of renewability,high efficiency,energy conservation,environmental protection and economy.Its utilization can reduce power consumption and save energy for terminal users and be good to realize the goal of reducing 20 percents of GDP consumption during the 11th five-year plan period.The article introduces the application status of ground-source heat pump in our country and analyzes the typical cases in Beijing and Liaoning regions.It illustrates that developing ground-source heat pump in the regions with appropriate condition has great superiority.The article at last brings out the related suggestions about strengthening policy supporting,broadening application extension,imporving builiding technology level and power enterprises participating actively.
Concealed Automated Trash Bin with Shredder for Solid Wastes

The common difficulty in populated developing countries like the Philippines is inappropriate waste management practices. The improper use of waste bins and waste segregation are some of those. One of the major causes is the irresponsibility of the people. As expected, the consequences are environmental and health risks experienced by people. The countermeasure to minimize these risks is the solution proposed by people, particularly the development of an automated segregation system. The waste bins are designed to be concealed to conserve space, slow down the decomposition rate and reduce the foul odor of waste. The design is fully automated to minimize direct contact with the waste. The classifying section is capable of collecting and segregating waste using a gripper, servo motors, ultrasonic, capacitive, and photoelectric sensors. To conserve power, the segregated waste is held in a storage bin prior to shredding. Shredded waste is routed to their respective transport bins for collection after shredding.The ultrasonic sensors provide data about the capacity of the transport bins and allow the GSM module to send an SMS informing the concerned authority regarding the bins’ status. These messages facilitate easier waste collection. Two tests were conducted to determine the performance of the prototype: response-time and garbage level detection tests. The result shows that the prototype performed well and can successfully achieve the desired function. It took 23.745 and 2.711 seconds to collect and segregate the waste, respectively. Likewise, the monitoring system successfully expedited the checking of the waste bins. However, it is recommended to include quality of output and SMS delay tests. These tests can improve the overall performance of the prototype.
Clinical and haematological determinants of outcome among children with cerebral malaria in a tertiary centre in Nigeria

Background: Many cl inicaland haematological changes occur as a result of severe malaria, of which cerebral malaria (CM) is a common entity. These changes affect virtually all organs and systems of the body. We identify various clinical and haematological determinants of outcome in CM so as to institute proactive management of such children. Methods: All children who met World Health Organization (WHO) diagnostic criteria for CM over 8 month-period were prospectively studied. The presenting symptoms and its duration, detailed physical examination and laboratory parameters were obtained. Logistic regression was employed to determine the prognostic significance of various clinical and laboratory parameters. Outcome indicators were full recovery, alive with neurological sequelae or death of the children.Results: Of the 892 children admitted into the Children Emergency Unit (CEU) over the study period, 50 (5.6%) had CM with M: F ratio of 1:1 and age range of 6 months to 12 years. Sixty percent were aged less than 5 years. The defining symptoms were fever (100%), coma (100%) and convulsion (98%). Forty-one (82%) patients survived, while nine (18%) died. Of the 41 survivors, 30 (73.2%) recovered fully, while 11 (26.8%) had neurological deficits at discharge.Identified clinical and laboratory predictors of mortality and neurological sequelae in CM included Blantyre coma score of 0-2(p = 0.018) prolonged coma recovery time > 26 hours (p =0.026), abnormal breathing pattern (p = 0.0124), absent corneal reflex (p = 0.012), absent pupillary reflex (p = 0.012), depressed tendon reflex (p = 0.028), hyperreflexia (p =0.014), retinal haemorrhage (p =0.001), duration of admission (p=0.000), hyper parasitaemia (p=0.001), hypoglycemia (p= 0.014) and leucocytosis (p = 0.008). Independent determinants of immediate post-recovery neurological deficits and death were hyper-parasitaemia (OR = 8.657, p = 0.017.) and leucocytosis (OR = 1.090; p = 0.035Conclusion: CM is a potentially reversible encephalopathy associated with high mortality and sequelae. Affected children with the above listed clinical / haematological parameters especially hyperparasitemia and leucocytosis should be given proactive management to improve the outcome.
A Systematic Literature Review of Game Design Tools

Existing research works show the role of game-based learning to increase lifelong learners’ learning and motivation. Furthermore, many game design tools are increasingly available and easy-to-use even by people without any technical knowledge, making the choice of the tool difficult. The aim of this paper is to identify and compare game design tools in order to help people to choose the most suitable game design tool for their needs. After having identified 9 criteria that characterize a game design tool, we have conducted a systematic literature review following the PRISMA methodology. This methodology allows us to identify references via 2 methods: databases and the interview with a pedagogical engineer. From 302 identified studies via 5 databases (IEEE Xplore, ScienceDirect, Scopus, Springer, and Web of Science), 18 have been used for the discussion. From the 8 game design tools advised by the pedagogical engineer, 3 have been used for the discussion. These 2 methods allow us to identify 12 game design tools. This research work is dedicated to Technology Enhanced Learning community and pedagogical community, and more specifically to game designers, pedagogical engineers, teachers, and researchers who encounter difficulties in choosing the game design tool the more suitable for their needs.