Miracle-dz/UniFAR-FTUs huggingface dataset:
Liquid-Based Reconfigurable Antenna Technology: Recent Developments, Challenges and Future

Advances in reconfigurable liquid-based reconfigurable antennas are enabling new possibilities to fulfil the requirements of more advanced wireless communication systems. In this review, a comparative analysis of various state-of-the-art concepts and techniques for designing reconfigurable antennas using liquid is presented. First, the electrical properties of different liquids at room temperature commonly used in reconfigurable antennas are identified. This is followed by a discussion of various liquid actuation techniques in enabling high frequency reconfigurability. Next, the liquid-based reconfigurable antennas in literature used to achieve the different types of reconfiguration will be critically reviewed. These include frequency-, polarization-, radiation pattern-, and compound reconfigurability. The current concepts of liquid-based reconfigurable antennas can be classified broadly into three basic approaches: altering the physical (and electrical) dimensions of antennas using liquid; applying liquid-based sections as reactive loads; implementation of liquids as dielectric resonators. Each concept and their design approaches will be examined, outlining their benefits, limitations, and possible future improvements.
Development and Calibration of Seasonal Probabilistic Forecasts of Ice-Free Dates and Freeze-Up Dates

Dynamical forecasting systems are being used to skillfully predict deterministic ice-free and freeze-up date events in the Arctic. This paper extends such forecasts to a probabilistic framework and tests two calibration models to correct systematic biases and improve the statistical reliability of the event dates: trend-adjusted quantile mapping (TAQM) and nonhomogeneous censored Gaussian regression (NCGR). TAQM is a probability distribution mapping method that corrects the forecast for climatological biases, whereas NCGR relates the calibrated parametric forecast distribution to the raw ensemble forecast through a regression model framework. For NCGR, the observed event trend and ensemble-mean event date are used to predict the central tendency of the predictive distribution. For modeling forecast uncertainty, we find that the ensemble-mean event date, which is related to forecast lead time, performs better than the ensemble variance itself. Using a multidecadal hindcast record from the Canadian Seasonal to Interannual Prediction System (CanSIPS), TAQM and NCGR are applied to produce categorical forecasts quantifying the probabilities for early, normal, and late ice retreat and advance. While TAQM performs better than adjusting the raw forecast for mean and linear trend bias, NCGR is shown to outperform TAQM in terms of reliability, skill, and an improved tendency for forecast probabilities to be no worse than climatology. Testing various cross-validation setups, we find that NCGR remains useful when shorter hindcast records (~20 years) are available. By applying NCGR to operational forecasts, stakeholders can be more confident in using seasonal forecasts of sea ice event timing for planning purposes.
Integrating Backdating and Transfer Learning in an Object-Based Framework for High Resolution Image Classification and Change Analysis

Classification and change analysis based on high spatial resolution imagery are highly desirable for urban landscapes. However, methods with both high accuracy and efficiency are lacking. Here, we present a novel approach that integrates backdating and transfer learning under an object-based framework. Backdating is used to optimize the target area to be classified, and transfer learning is used to select training samples for classification. We further compare the new approach with that of using backdating or transfer learning alone. We found: (1) The integrated new approach had higher overall accuracy for both classifications (85.33%) and change analysis (88.67%), which were 2.0% and 4.0% higher than that of backdating, and 9.3% and 9.0% higher than that of transfer learning, respectively. (2) Compared to approaches using backdating alone, the use of transfer learning in the new approach allows automatic sample selection for supervised classification, and thereby greatly improves the efficiency of classification, and also reduces the subjectiveness of sample selection. (3) Compared to approaches using transfer learning alone, the use of backdating in the new approach allows the classification focusing on the changed areas, only 16.4% of the entire study area, and therefore greatly improves the efficiency and largely avoid the false change. In addition, the use of a reference map for classification can improve accuracy. This new approach would be particularly useful for large area classification and change analysis.
What really controls the atmospheric corrosion of zinc? Effect of marine aerosols on atmospheric corrosion of zinc

This paper reviews the processes that control the production, transportation and deposition of aerosols and examines how these parameters affect the atmospheric corrosion of zinc on which the aerosols have deposited. The factors that influence the size and chemistry of aerosols are summarised. It is shown that marine aerosols may be acidified through the absorption of gases and strong acids, and that they may attain very low pH values. Aerosol transportation and deposition are size dependent, with aerosol deposition increasing with aerosol size and decreasing with transportation distance. Acidified marine aerosols may be transported to considerable distances from the sources of the acid precursor gases. The review examines the differences in the electrochemical phenomena on zinc surfaces under fine acidified marine or industrial aerosols and under large near neutral aqueous droplets, and shows that the low pH, fine size and high dissolved ionic salt content of the acidified marine aerosols leads to significant oxide dissolution and higher corrosion rates. Acidified marine aerosols disrupt protective oxide films and establish electrochemical cells in which anodic corrosion separation and resistance through the solution are small and oxygen depletion is unlikely. The authors’ analysis shows that the susceptibility of zinc to chloride containing environments may in part be associated with the effect of acidified marine aerosols.
Electronegativity: Quantum observable

The question whether electronegativity may be considered as quantum observable is responded in positive by a special ionization-affinity wave function construction within the fermionic Fock space for the valence state of a chemical system. The present approach consecrates electronegativity as the minus eigen-energy of the unperturbed occupied valence state involved in addition and release of electrons by atoms-in-molecules interactions. This way, the earlier crisis raised by Bergmann and Hinze concerning the assignment of chemical potential to electronegativity quantification is here solved in the favor of Parr density functional picture. © 2008 Wiley Periodicals, Inc. Int J Quantum Chem, 2009
Effect of adipose tissue thickness and tissue optical properties on the differential pathlength factor estimation for NIRS studies on human skeletal muscle.

We propose a quantitative and systematic investigation of the differential pathlength factor (DPF) behavior for skeletal muscles and its dependence on different factors, such as the subcutaneous adipose tissue thickness (ATT), the variations of the tissue absorption (µa ) and reduced scattering (µ's ) coefficients, and the source-detector distance. A time domain (TD) NIRS simulation study is performed in a two-layer geometry mimicking a human skeletal muscle with an overlying adipose tissue layer. The DPF decreases when µa increases, while it increases when µ's increases. Moreover, a positive correlation between DPF and ATT is found. These results are supported by an in-vivo TD NIRS study on vastus lateralis and biceps brachii muscles of eleven subjects at rest, showing a high inter-subject and inter-muscle variability.
Residential Racial and Socioeconomic Segregation as Predictors of Housing Discrimination in Detroit Metropolitan Area

This study examined neighborhood racial and socioeconomic characteristics associated with housing discrimination (HD) in the Detroit Metropolitan Area, Michigan. Using novel neighborhood level data from the Fair Housing Center of Metropolitan Detroit in combination with the American Community Survey, incidence rate ratios (IRRs) were derived to examine associations between HD cases and percentage of homeowners, non-Hispanic White (NHW) residents, and median income. Models were stratified to examine these associations for race-, disability- and rent-related HD outcomes. Between 2008–2017, 988 HD incidents were reported. Independently, neighborhood proportion NHW, income, and homeownership were inversely associated with all-types of HD. Jointly, the neighborhood predictors remained significant indicators. Similar patterns were observed in race-, disability- and rent-related HD when neighborhood predictors were examined independently. In the joint models, household income no longer predicted race-related HD, while proportion NHW no longer predicted disability- and rent-related HD. Results suggest HD may be more frequent in neighborhoods with greater proportions of NHB or Hispanic residents, those with lower incomes, and greater proportion of rental households. These findings have great social and health implications and warrant further exploration of how HD contributes to social and health inequities in lower income, predominantly NHB and Hispanic neighborhoods and those with more renters.
Sustainable Disaster Response Management Related to Large Technical Systems

Numerous investigations assess the technical, technological, and managerial aspects of disaster response related to large technical systems. This paper deals with the possibility of synthesizing these aspects in a disaster response methodology, thus combining the technical, technological methods, tools, and software with the art of management. Its objective is to develop a preliminary methodology that supports the response management decision making processes related to earthquake-damaged large technical systems. The introduced methodology is demonstrated with the example of railway systems. It utilizes a combination of (i) a probabilistic model of railway system damage caused by earthquakes, (ii) a Markov model related to the damage and recovery phases, (iii) a probabilistic model of aftershocks, (iv) a statistical model of secondary effects, (v) impact models of management support actions, and (vi) response process management supported by a Markov Decision Process. The simulation results validate the concept. Based on these research results, the authors recommend that the described preliminary response management approach be further specified and implemented in disaster management procedures.
Six Novel Biomarkers for Diagnosis and Prognosis of Esophageal squamous cell carcinoma: validated by scRNA-seq and qPCR

Esophageal squamous cell carcinoma (ESCC) is one of the most common cancers worldwide. ESCC has a generally poor prognosis and there is a lack of available biomarkers for diagnosis and prognosis. The aim of the study was to identify novel biomarkers for ESCC. We screened the overlapping differentially expressed genes (DEGs) acquired from six Gene Expression Omnibus (GEO) ESCC datasets and The Cancer Genome Atlas (TCGA) ESCC datasets. Subsequently, protein-protein interaction network analysis was performed to identify the key hub genes. Then, Kaplan Meier survival and receiver operating curve (ROC) analysis were utilized to clarify the diagnostic and prognostic role of these hub genes. The UALCAN database, single cell RNA sequencing (scRNA-seq) and real-time quantitative PCR (qPCR) were performed to confirm the expression levels of identified hub genes. Finally, immune infiltration analysis was conducted to investigate the role of these genes in the pathogenesis of ESCC. The results showed that PBK, KIF2C, NUF2, KIF20A, RAD51AP1, and DEPDC1 effectively distinguish ESCC tissues from normal samples, and all of them were significantly correlated with overall survival. The results of scRNA-seq and qPCR indicated that the expression levels of hub genes in ESCC were significantly higher than in normal cells or tissues. Further immune infiltration analysis showed that infiltration of dendritic cells was significantly negatively correlated with PBK, KIF2C, NUF2, RAD51AP1, and DEPDC1 expression levels. In conclusion, our results suggest that PBK, KIF2C, NUF2, KIF20A, RAD51AP1 and DEPDC1 are all potential biomarkers for ESCC diagnosis and prognosis may also be potential therapeutic targets for ESCC.
A Functional DNase I Coating to Prevent Adhesion of Bacteria and the Formation of Biofilm

Biofilms are detrimental in many industrial and biomedical applications and prevention of biofilm formation has been a prime challenge for decades. Biofilms consist of communities of adhering bacteria, supported and protected by extracellular‐polymeric‐substances (EPS), the so‐called “house of biofilm organisms”. EPS consists of water, proteins, polysaccharides and extracellular‐DNA (eDNA). eDNA, being the longest molecule in EPS, connects the different EPS components and therewith holds an adhering biofilm together. eDNA is associated with bacterial cell surfaces by specific and non‐specific mechanisms, mediating binding of other biopolymers in EPS. eDNA therewith assists in facilitating adhesion, aggregation and maintenance of biofilm structure. Here, a new method is described to prevent biofilm formation on surfaces by applying a DNase I enzyme coating to polymethylmethacrylate, using dopamine as an intermediate. The intermediate coupling layer and final DNase I coating are characterized by water‐contact‐angle measurements and X‐ray photoelectron‐spectroscopy. The DNase I coating strongly reduces adhesion of Staphylococcus aureus (95%) and Pseudomonas aeruginosa (99%) and prevents biofilm formation up to 14 h, without affecting mammalian cell adhesion and proliferation. Also agarose‐gel‐electrophoresis indicates loss of enzyme activity between 8 and 24 h. This duration however, is similar to many local antibiotic‐delivery devices, which makes it an ideal coating for biomaterial implants and devices, known to fail due to biofilm formation with disastrous consequences for patients and high costs to the healthcare system. With threatening increases in antibiotic resistance, the DNase I coating may provide a timely, potent new approach to biofilm prevention on biomaterial implants and devices.
Reliability analysis of cyber‐physical microgrids: Study of grid‐connected microgrids with communication‐based control systems

Due to the greater penetration of renewable energy resources and the increasing complex-ity of the distribution system, moving towards a smart distribution system is essential and achievable via advanced information and communication technologies. These technologies come with side effects: not only do they change the structure and functionality of the system, their availability and efﬁciency alter the operation of the system as a whole. The aim of this paper is to examine the reliability of a cyber-physical microgrid as a part of a smart distribution grid to evaluate the impact of the integration of information and communication technologies into the system and the impact of non-dispatchable renewable energy resources, that is, photovoltaic and wind farms. This paper proposes a framework for developing reliability assessment tools for a grid-connected microgrid with a hierarchical three-level and communication-based control system. Emphasis is laid on incorporating the interdependencies between the cyber system and the microgrid and on detailed models of renewable energy resources.
Self-Assembly of Rod−Coil Diblock Oligomers Based on α-Helical Peptides

A detailed study of the supramolecular organization of two series of peptide-based diblock oligomers is reported. The diblock oligomers are comprised of an α-helical oligopeptide rod, which is either based on γ-benzyl-l-glutamate or e-benzyloxycarbonyl-l-lysine, and a short oligo(styrene) coil. The unique feature of these rod−coil molecules is that the conformation of the α-helical peptide rod is sensitive to temperature. As a result, the supramolecular organization of these rod−coil oligomers can be manipulated not only via changes in the block length ratio or chemical composition but also via temperature-induced conformational changes in the rod segments. This makes these molecules attractive building blocks for the development of stimuli-sensitive self-assembled materials.
Professional Development for EMI: The Choice of a Blended Learning Format for Training EMI Lecturers at the University of Verona

The internationalization of higher education (IoIHE) has led to many changes in university teaching, including the introduction of English Medium Instruction (EMI). This refers to the complete or partial delivery of course contents in English in a context where it is not the first language of the institution. The aim behind such courses is twofold: firstly to create courses that are accessible for overseas students wishing to study abroad and secondly to meet the lifelong learning needs of local students, equipping them with the means to export their own expertise and have the specialized language and content skills to participate in a global community. The introduction of such courses in Italian institutions has not been unproblematic, and EMI has been considered to be a top-down imposition, but if EMI is to be effective, it should, in fact, be driven by motivated lecturers themselves who wish to cater for the needs of their students in a globalized world. Professional development for such lecturers is still lacking or implemented non-systematically at local levels. This article briefly examines the phenomenon of EMI against a backdrop of internationalization and then describes the findings of questionnaires on lecturer confidence and their influence on the course design and teaching approach to EMI lecturer training courses at the University of Verona. The curriculum design of these courses, originally introduced to meet the English language needs of lecturers, is based on an ongoing study, which has shown over the years that the original emphasis has shifted to an awareness of the need for a specific EMI methodology. The course participants have consistently expressed an interest in developing a blended learning approach with the integration of the face-to-face and the digital as a suitable teaching and learning framework.
Ultrafine particles: mechanisms of lung injury

Many ultrafine particles comprised classically of low–toxicity, low–solubility materials such as carbon black and titanium dioxide have been found to have greater toxicity than larger, respirable particles made of the same material. The basis of the increased toxicity of the ultrafine form is not well understood and a programme of research has been carried out in Edinburgh on the toxicology of ultrafines aimed at understanding the mechanism. We used fine and ultrafine carbon black, TiO2 and latex and showed that there was an approximately 10–fold increase in inflammation with the same mass of ultrafine compared with fine particles. Using latex particles in three sizes — 64, 202 and 535 nm — revealed that the smallest particles (64 nm) were profoundly inflammogenic but that the 202 and 535 nm particles had much less activity, suggesting that the cut–off for ultrafine toxicity lies somewhere between 64 and 202 nm. Increased oxidative activity of the ultrafine particle surface was shown using the fluorescent molecule dichlorofluorescein confirming that oxidative stress is a likely process by which the ultrafines have their effects. However, studies with transition–metal chelators and soluble extracts showed that the oxidative stress of ultrafine carbon black is not necessarily due to transition metals. Changes in intracellular Ca2+ levels in macrophage–like cells after ultrafine particle exposure suggested one way by which ultrafines might have their pro–inflammogenic effects.
An Organometallic Super‐Gelator with Multiple‐Stimulus Responsive Properties

Stimulus-responsive gels have recently attracted widespread attention as new functional materials for potential applications in sensors, actuators, shape memories, drug delivery devices, and displays. One of the promising properties that organogels based on low molecular mass organic gelators (LMOGs) can offer is their reversible sol–gel phase transition as a result of external stimuli. As far as we know, redoxresponsive organogels from LMOGs, however, are limited. Shinkai and coworkers reported the first example of organogels of this kind, which contains a redox-active Cu/ Cu center. Besides, they also synthesized a series of quater-, quinque-, and sexithiophene derivatives bearing two cholesteryl moieties at the a-position. It was found that a sol–gel phase transition can be implemented by addition of oxidizing and reducing reagents. Zhu and colleagues prepared an electro-active LMOG containing a tetrathiafulvalene (TTF) entity. The gel formation can be tuned by means of oxidation/ reduction of the TTF group chemically or electrochemically. Although these gel systems are redox responsive, their properties, such as mechanical strength, flexibility, and sensitivity to external stimulus, are far from those required for practical uses. Therefore, creating instant, reversible, redox-responsive, and mechanically flexible organogels still remains a challenge. As a remarkable organometallic compound, ferrocene (Fc) contains an oxidizable metal ion, Fe, and is a nonpolar compound in the neutral state, and thereby it dissolves readily in hydrocarbon solvents. This property, however, can be easily reversed by simple oxidation of the central ion. Our interest in stimulus-responsive supramolecular gel systems led us to consider the compound as a neutral–cation redox pair that may be employed to tune the gelling ability of a gelator containing it. Actually, the same idea has been adopted by a number of groups for studies of switchable complexation and molecular aggregation in micelles and vesicles. However, all com-
Anode Modification as an Alternative Approach to Improve Electricity Generation in Microbial Fuel Cells

Sustainable production of electricity from renewable sources by microorganisms is considered an attractive alternative to energy production from fossil fuels. In recent years, research on microbial fuel cells (MFCs) technology for electricity production has increased. However, there are problems with up-scaling MFCs due to the fairly low power output and high operational costs. One of the approaches to improving energy generation in MFCs is by modifying the existing anode materials to provide more electrochemically active sites and improve the adhesion of microorganisms. The aim of this review is to present the effect of anode modification with carbon compounds, metallic nanomaterials, and polymers and the effect that these modifications have on the structure of the microbiological community inhabiting the anode surface. This review summarizes the advantages and disadvantages of individual materials as well as possibilities for using them for environmentally friendly production of electricity in MFCs.