Miracle-dz/UniFAR-FTUs huggingface dataset:
Use of 68Ga-PSMA-11 and 18F-FDG PET-CT Dual-Tracer to Differentiate Between Lymph Node Metastases and Ganglia

Purpose Differentiating lymph node metastases (LNM) from peripheral ganglia by physiological prostate-specific membrane antigen (PSMA) uptake is challenging. Two tracers (68Ga-PSMA-11 and 18F-fluorodeoxyglucose [FDG]) metabolic uptake patterns were evaluated by positron emission tomography-computed tomography (PET-CT), searching for differences that could tell ganglia from LNM. Methods Dual 68Ga-PSMA-11 and 18F-FDG PET-CT data of 138 prostate cancer patients acquired from June 2018 to December 2019 were retrospectively evaluated. Ganglia and LNM with PSMA-11 uptake above local background were analyzed by the location and PSMA-11-PET and FDG-PET maximum standardized uptake value (SUVmax). Results PSMA-11-positive ganglia (n = 381) and LNM (n = 83) were identified in 138 and 58 patients, respectively. The LNM SUVmax of PSMA-11-PET (16.4 ± 14.8 vs 2.3 ± 0.7, P < 0.001) and FDG-PET (3.3 ± 3.2 vs 1.5 ± 0.5, P < 0.001) were higher than in ganglia. The probabilities of being an LNM in the low-potential (PSMA-11-PET SUVmax of <4.1 and FDG-PET SUVmax of <2.05), moderate-potential (PSMA-11-PET SUVmax of >4.1 and FDG-PET SUVmax of <2.05, or PSMA-11-PET SUVmax of <4.1 and FDG-PET SUVmax of >2.05), and high-potential (PSMA-11-PET SUVmax of >4.1 and FDG-PET SUVmax of >2.05) groups were 0.9% (3/334), 44.6% (37/83), and 91.5% (43/47), respectively (P < 0.001). The cervical and coeliac ganglia had higher PSMA-11 and FDG uptake than the sacral ganglia (P < 0.001 for all). LNM PSMA-11 and FDG uptake was similar in these three locations. Conclusion The FDG-PET and PSMA-11-PET SUVmax, especially when combined, could well differentiate LNM from ganglia. The tracers uptake differed between cervical/coeliac and sacral ganglia, so the lesion location should be considered during image assessment.
Extreme ultraviolet spectroscopy of helium–hydrogen plasma

Extreme ultraviolet spectroscopy was recorded on microwave discharges of helium with 2% hydrogen. Novel emission lines were observed with energies of q . 13.6 eV, q = 1, 2, 3, 7, 9, 11, or q . 13.6 eV, q = 4, 6, 8 less 21.2 eV corresponding to inelastic scattering of these photons by helium atoms due to excitation of He (1s2) to He (1s12p1). The average hydrogen atom temperature was measured to be 180–210 eV versus ≈3 eV for pure hydrogen. The electron temperature Te for helium–hydrogen was 30 500 ± 5% K compared to 7400±5% K for pure helium. Known explanations for the novel series of spectral lines and extraordinary broadening were ruled out.
Environmental Inequalities in Flood Exposure: A Matter of Scale

Studies on inequalities in exposure to flood risk have explored whether population of a lower socio-economic status are more exposed to flood hazard. While evidence exist for coastal flooding, little is known on inequalities for riverine floods. This paper addresses two issues: (1) is the weakest population, in socio-economic terms, more exposed to flood hazard, considering different levels of exposure to hazard? (2) Is the exposure to flood risk homogeneous across the territory, considering different scales of analysis? An analysis of the exposure of inhabitants of Liège province to flood risk was conducted at different scales (province, districts, and municipalities), considering three levels of exposure to flood hazard (level 1- low hazard, level 3- high hazard), and five socio-economic classes (class 1-poorest, class 5-wealthiest households). Our analysis confirms that weaker populations (classes 2 and 3) are usually more exposed to flood hazards than the wealthiest (classes 4 and 5). Still it should be stressed that the most precarious households (class 1) are less exposed than low to medium-range ones (classes 2 and 3). Further on the relation between socio-economic status and exposure to flood hazard varies along the spatial scale considered. At the district level, it appears that classes 4 and 5 are most exposed to flood risk in some peripheral areas. In municipalities located around the center of the city, differences of exposure to risk are not significant.
The Effects of Corticosteroids on the Respiratory Microbiome: A Systematic Review

Background: Since its discovery, the respiratory microbiome has been implicated in the pathogenesis of multiple pulmonary diseases. Even though corticosteroid treatments are widely prescribed for pulmonary diseases, their effects on the respiratory microbiome are still poorly understood. This systematic review summarizes the current understanding of the effects of corticosteroids on the microbiome of the airways. Research Question: How does treatment with corticosteroids impact the respiratory microbiome? Study Design and Methods: According to the PRISMA guidelines, Embase, Medline, and the Cochrane Central Register of Controlled Trials (CENTRAL) databases were systematically searched for all observational or randomized-controlled studies comparing the microbiome parameters of patients receiving corticosteroids to those of controls. The primary outcomes of interest were changes in the diversity, composition and total burden of the respiratory microbiome as assessed by culture-independent molecular methods. Results: Out of 1,943 identified reports, five studies could be included: two on patients with asthma, two on patients with chronic obstructive pulmonary disease and one on patients with chronic rhinosinusitis. The studies were highly heterogeneous with regards to the methods used and the populations investigated. Microbiome diversity increased with corticosteroids at least transiently in three studies and decreased in one study. The effects of corticosteroids on the composition of the respiratory microbiome were significant but without a clear shared direction. A significant increase in microbial burden after corticosteroids was seen in one study. Interpretation: Data on the effect of corticosteroids on the respiratory microbiome are still limited, with considerable heterogeneity between studies. However, available data suggest that corticosteroid treatment may have significant effects on the composition and possibly the diversity of the respiratory microbiome. Further research is needed to better understand the influence of corticosteroids on the respiratory microbiome and thus better target its widespread therapeutic use.
Internet of Things: A General Overview between Architectures, Protocols and Applications

In recent years, the growing number of devices connected to the internet has increased significantly. These devices can interact with the external environment and with human beings through a wide range of sensors that, perceiving reality through the digitization of some parameters of interest, can provide an enormous amount of data. All this data is then shared on the network with other devices and with different applications and infrastructures. This dynamic and ever-changing world underlies the Internet of Things (IoT) paradigm. To date, countless applications based on IoT have been developed; think of Smart Cities, smart roads, and smart industries. This article analyzes the current architectures, technologies, protocols, and applications that characterize the paradigm.
Distributed Denial of Service (DDoS) Mitigation Using Blockchain - A Comprehensive Insight

Distributed Denial of Service (DDoS) attack is a major threat impeding service to legitimate requests on any network. Although the first DDoS attack was reported in 1996, the complexity and sophistication of these attacks has been ever increasing. A 2 TBps attack was reported in mid-August 2020 directed towards critical infrastructure, such as finance, amidst the COVID-19 pandemic. It is estimated that these attacks will double, reaching over 15 million, in the next 2 years. A number of mitigation schemes have been designed and developed since its inception but the increasing complexity demands advanced solutions based on emerging technologies. Blockchain has emerged as a promising and viable technology for DDoS mitigation. The inherent and fundamental characteristics of blockchain such as decentralization, internal and external trustless attitude, immutability, integrity, anonymity and verifiability have proven to be strong candidates, in tackling this deadly cyber threat. This survey discusses different approaches for DDoS mitigation using blockchain in varied domains to date. The paper aims at providing a comprehensive review, highlighting all necessary details, strengths, challenges and limitations of different approaches. It is intended to serve as a single platform to understand the mechanics of current approaches to enhance research and development in the DDoS mitigation domain.
Short-Term Electricity Load Forecasting with Machine Learning

An accurate short-term load forecasting (STLF) is one of the most critical inputs for power plant units’ planning commitment. STLF reduces the overall planning uncertainty added by the intermittent production of renewable sources; thus, it helps to minimize the hydrothermal electricity production costs in a power grid. Although there is some research in the field and even several research applications, there is a continual need to improve forecasts. This research proposes a set of machine learning (ML) models to improve the accuracy of 168 h forecasts. The developed models employ features from multiple sources, such as historical load, weather, and holidays. Of the five ML models developed and tested in various load profile contexts, the Extreme Gradient Boosting Regressor (XGBoost) algorithm showed the best results, surpassing previous historical weekly predictions based on neural networks. Additionally, because XGBoost models are based on an ensemble of decision trees, it facilitated the model’s interpretation, which provided a relevant additional result, the features’ importance in the forecasting.
Carbon Dioxide Flux in a Soil Treated with Biosolids Under Semiarid Conditions

The restoration of degraded land using biosolids provides a well known means of recycling these organic residues. In semiarid ecosystems they can enhance the chemical and physical properties of the soil and stimulate soil microbe growth and activity, leading to increases in soil fertility and quality. However, the respiratory activity in biosolids-treated soil may contribute to an increase in atmospheric CO2. Few studies examining CO2 emissions from biosolids-amended soils in semiarid climates have been conducted under field conditions. The aims of the present study were to determine the effect of applying different amounts of biosolids on the soil organic matter content and respiratory activity of a semiarid, abandoned agricultural soil. The CO2 fluxed from the soil surface (kg CO2 ha−1 d−1) was measured using a portable analyser. Soil temperature and soil water content were measured in the first 5 cm of soil. The results show that a large proportion of the organic matter incorporated into the soil via the biosolids was easily biodegradable in the first three years following its application. In addition, biosolids application generally increased soil CO2 emissions, although in a manner not proportional to the quantity applied. Differences in soil humidity were associated with differences in soil CO2 flux over the year. The soil water content was the major factor affecting soil respiration; a strong correlation was found between these variables. Soil respiration activity could serve as a useful index of soil biological activity, allowing the decomposition of biosolids under field conditions to be monitored.
Rubbing‐induced molecular alignment and its relaxation in polystyrene thin films

Rubbing-induced molecular alignment and its relaxation in polystyrene (PS) thin films are studied with optical birefringence. A novel relaxation of the alignment is observed that is distinctly different from the known relaxation processes of PS. First, it is not the Kohlrausch–Williams–Watts type but instead is characterized by two single exponentials plus a temperature-dependent constant. At temperatures several degrees or more below the glass-transition temperature (Tg), the relaxation time falls between that of the α and β relaxations. Second, the decay time constants are the same within 40% for PS with weight-average molecular weights (Mw's) of 13,700–550,000 Da at temperatures well below the sample Tg's, indicating that the molecular relaxations involved are mostly local within the entanglement distance. Nonetheless, the temperature at which the rubbing-induced molecular alignment disappears (T0) exhibits a strong Mw dependence and closely approximates the Tg of the sample. Furthermore, T0 depends notably on the thickness of the polymer in much the same way as previously found for the Tg of supported PS films. This suggests that the α process becomes dominant near Tg. Preliminary spectroscopic studies in the mid-infrared range show a significant degree of bending of the phenyl ring toward the sample surface, with the CC bond connecting the phenyl ring and the main chain tends to lie along the rubbing direction, which indicates that the relaxation is connected with the reorientation of this CC bond. We exclude the observed relaxation, as predominantly a near-surface one, because detailed studies on the effects of rubbing conditions on the degree of molecular alignment indicate that the alignment is not local to the polymer–air surface. © 2001 John Wiley & Sons, Inc. J Polym Sci Part B: Polym Phys 39: 2906–2914, 2001
Online Consumers' Brain Activities When Purchasing Second-Hand versus New Products That Are Brand-Name or Brand-Less

It is now common to apply functional magnetic resonance imaging to explore which areas of the human brain are activated during the decision-making process. In the study of consumer behaviors, product brand has been identified as a major factor affecting consumer purchase decisions. Prior studies indicate that the brand had a significant impact on brain activation. However, it is unsure if consumers’ brain activation is also significant when purchasing brand-name second-hand products (SHPs). Therefore, the purpose of this study is to verify the areas of brain neuron activation in the context of online auctions among consumers whose purchasing decisions are affected by an SHP’s brand. The results show that a brain region (i.e., the medial prefrontal cortex) activates significantly when comparing the purchasing decision-making process between new items and SHPs. The activation of the insula is also found when an SHP purchasing decision is made. In addition, the dorsolateral prefrontal cortex is activated significantly when purchasing brand-name SHPs. However, due to consumers’ preferences for different brands, there is no significant activation in the ventromedial prefrontal cortex.
EEG and fMRI Correlates of Insight: A Pilot Study

Insight is described as the sudden solution of a problem and is contrasted with an analytical, step-by-step approach. Traditionally, insight is thought to be associated with activity of the right hemisphere, whereas analytical solutions are thought to be associated with activity of the left hemisphere. However, empirical evidence as to the localization of insight-related brain activity is mixed and inconclusive. Some studies seem to confirm the traditional view, whereas others do not. Moreover, results of EEG and fMRI studies frequently contradict each other. In this study, EEG and fMRI data were recorded while subjects performed the remote association test and for each solved problem were asked to report whether the solution was reached analytically or insightfully. The data were analyzed in a 16-second fragment preceding the subject’s response. Source localization techniques were used in the analysis of EEG data. Based on EEG data, insightful as compared to analytical problem solving was accompanied by high-frequency synchronization in semantic cortical areas of the left hemisphere 10–12 s before the subject’s response. Based on fMRI data, however, insightful solutions were accompanied by increased activity in frontal and temporal regions of the right hemisphere. The results are interpreted in terms of different cognitive processes involved in insightful problem solving, which could be differently reflected in EEG and fMRI data.
DroidbotX: Test Case Generation Tool for Android Applications Using Q-Learning

Android applications provide benefits to mobile phone users by offering operative functionalities and interactive user interfaces. However, application crashes give users an unsatisfactory experience, and negatively impact the application’s overall rating. Android application crashes can be avoided through intensive and extensive testing. In the related literature, the graphical user interface (GUI) test generation tools focus on generating tests and exploring application functions using different approaches. Such tools must choose not only which user interface element to interact with, but also which type of action to be performed, in order to increase the percentage of code coverage and to detect faults with a limited time budget. However, a common limitation in the tools is the low code coverage because of their inability to find the right combination of actions that can drive the application into new and important states. A Q-Learning-based test coverage approach developed in DroidbotX was proposed to generate GUI test cases for Android applications to maximize instruction coverage, method coverage, and activity coverage. The overall performance of the proposed solution was compared to five state-of-the-art test generation tools on 30 Android applications. The DroidbotX test coverage approach achieved 51.5% accuracy for instruction coverage, 57% for method coverage, and 86.5% for activity coverage. It triggered 18 crashes within the time limit and shortest event sequence length compared to the other tools. The results demonstrated that the adaptation of Q-Learning with upper confidence bound (UCB) exploration outperforms other existing state-of-the-art solutions.
A Study of Factors Affecting Intention to Adopt a Cloud-Based Digital Signature Service

The electronic signature service has been causing various problems due to the rapid growth of e-commerce services. Therefore, in order to create an authentication service suitable for the era of the 4th Industrial Revolution, new security authentication technologies such as the cloud must be utilized. However, there is a lack of prior management studies on the intention to accept digital signatures. Therefore, this study conducted an empirical study to identify factors affecting the intention to adopt cloud-based digital signature services. This research proposed a model based on the technology–organization–environment framework and empirically analyzed the degree of mutual causality and influence between variables using the partial least squares structural equation model. The results show that technical characteristics, organizational characteristics, and environmental characteristics significantly affected the intention to adopt. However, there are still many concerns about the security of cloud-based services. It has been confirmed that solving this problem is the key to the activation of the electronic signature service.
In Vitro Assessment of Dose Delivery Performance of Dry Powders for Inhalation

The aerosol performance of engineered porous particles (PulmoSphere™) for inhalation as a function of powder properties (particle size and density) was assessed using an idealized replica of the adult human upper respiratory tract (URT) known as the Alberta mouth-throat model. Engineered placebo powders were prepared using the PulmoSphere™ technology, which is based on spray-drying an emulsion feedstock and produces porous particles with well-controlled size and density. These placebo powders are useful surrogates for a class of potent active formulations, and covered a range of particle sizes and densities, representing a particle design space relevant to dry powder inhalers. The Alberta idealized mouth-throat model was used for in vitro measurement of oropharyngeal (mouth and throat) losses and to estimate the total lung dose for different inhalation drug products. The in vitro lung doses measured with the mouth-throat model were compared to predictions of lung dose from semi-empirical numerical models of oropharyngeal deposition. Data from the mouth-throat model and numerical models were used to rank order oropharyngeal losses and flow-rate dependence in the 1–6 kPa pressure drop range. Aerosol performance of the PulmoSphere™ powders was favored by low-particle density and large geometric size, with the oropharyngeal deposition and flow rate dependence being lower for powders with median particle diameter ≥2.5 microns. In comparison, data from lactose-blend formulations showed significantly higher oropharyngeal deposition and flow rate dependence. The idealized mouth-throat model provides a reasonable in vitro estimate of dose delivered to the lungs, and is a useful tool for studying the effect of factors such as drug/device and inhalation airflow. Copyright 2014 American Association for Aerosol Research
An Experimental Investigation on the Effect of Ferrous Ferric Oxide Nano-Additive and Chicken Fat Methyl Ester on Performance and Emission Characteristics of Compression Ignition Engine

In recent years, industries have been investing to develop a potential alternative fuel to substitute the depleting fossil fuels which emit noxious emissions. Present work investigated the effect of ferrous ferric oxide nano-additive on performance and emission parameters of compression ignition engine fuelled with chicken fat methyl ester blends. The nano-additive was included with various methyl ester blends at different ppm of 50, 100, and 150 through the ultrasonication process. Probe sonicator was utilized for nano-fuel preparation to inhibit the formation of agglomeration of nanoparticles in base fuel. Experimental results revealed that the addition of 100 ppm dosage of ferrous ferric oxide nanoparticles in blends significantly improves the combustion performance and substantially decrease the pernicious emissions of the engine. It is also found from an experimental results analysis that brake thermal efficiency (BTE) improved by 4.84%, a reduction in brake specific fuel consumption (BSFC) by 10.44%, brake specific energy consumption (BSEC) by 9.44%, exhaust gas temperature (EGT) by 19.47%, carbon monoxides (CO) by 53.22%, unburned hydrocarbon (UHC) by 21.73%, nitrogen oxides (NOx) by 15.39%, and smoke by 14.73% for the nano-fuel B20FFO100 blend. By seeing of analysis, it is concluded that the doping of ferrous ferric oxide nano-additive in chicken fat methyl ester blends shows an overall development in engine characteristics.
A Parallel Hybrid Bregman Subgradient Extragradient Method for a System of Pseudomonotone Equilibrium and Fixed Point Problems

We introduce a new parallel hybrid subgradient extragradient method for solving the system of the pseudomonotone equilibrium problem and common fixed point problem in real reflexive Banach spaces. The algorithm is designed such that its convergence does not require prior estimation of the Lipschitz-like constants of the finite bifunctions underlying the equilibrium problems. Moreover, a strong convergence result is proven without imposing strong conditions on the control sequences. We further provide some numerical experiments to illustrate the performance of the proposed algorithm and compare with some existing methods.