Preconception lifestyle modification and reducing several known risk factors may have an influence on the future pregnancy outcome. The aim of the study was to analyse health behaviour and personal values, as well as to assess the relationship of these factors in women without children, in pregnant ones and in women who had already delivered babies. The questionnaire survey included Health Behaviour Inventory (HBI), Personal Value List (PVL) and the sociodemographic data and was conducted in 538 women. These women were divided into 3 groups: women who recently delivered (n = 235), pregnant women (n = 121) and childless women (n = 182). Pregnant women demonstrated a significantly higher level of declared health behaviours and also they rated higher subscales values "positive mental attitude" and "health practices" in comparison to women who recently delivered and to childless women. In all tested groups the highest rated personal value was "a successful family life", while the most appreciated symbol of happiness was "love and friendship". Our results suggest that the system of values and the perception of happiness symbols may influence women's health behaviours. Positioning “health” in the hierarchy of personal values as the most important one may facilitate introduction of healthy behaviours. This in turn could reduce several adverse pregnancy outcomes that are potentially modifiable with changing preconception health attitudes. Our results also identify several unanswered questions and highlights areas where new research is needed.

Bacterial infections occur when wound healing fails to reach the final stage of healing, usually hindered by the presence of different pathogens. Different topical antimicrobial agents are used to inhibit bacterial growth due to antibiotic failure in reaching the infected site accompanied very often by an increased drug resistance and other side effects. In this review, we focus on antimicrobial peptides (AMPs), especially those with a high potential of efficacy against multidrug-resistant and biofilm-forming bacteria and fungi present in wound infections. Currently, different AMPs undergo preclinical and clinical phase to combat infection-related diseases. AMP dendrimers (AMPDs) have been mentioned as potent microbial agents. Various AMP delivery strategies, such as polymers, scaffolds, films and wound dressings, organic and inorganic nanoparticles, to combat infection and modulate the healing rate have been discussed as well. New technologies such as CRISPR-Cas are taken into consideration as potential future tools for AMP delivery in skin therapy.

Since coffee has been shown to influence positively the metabolism of subjects with metabolic syndrome (MetS), we aimed to evaluate the short- and long-term effects of a coffee-based supplement on different features of diet-induced MetS. 24 Sprague Dawley rats were divided into control or nutraceuticals groups to receive a high-fat/high fructose diet with or without a mixture of caffeic acid (30 mg/day), trigonelline (20 mg/day), and cafestol (1 mg/day) for 12 weeks. An additional 11 rats were assigned to an acute crossover study. In the chronic experiment, nutraceuticals did not alter body weight or glycemic control but improved fed hyperinsulinemia and HOMA-IR, and plasma adiponectin levels. The impact of nutraceuticals on post-prandial glycemia tended to be more pronounced after acute administration than at the end of the chronic study. Circulating and intrahepatocellular alanine transaminase activity, assessed by hyperpolarized-¹³C NMR spectroscopy, were reduced by coffee nutraceuticals at endpoint. There was also a tendency towards lower liver triglyceride content and histological steatosis score in the intervention group. In conclusion, a mixture of coffee nutraceuticals improved insulin sensitivity and exhibited hepatoprotective effects in a rat model of MetS. Higher dosages with or without caffeine deserve to be studied in the future.

This article puts forward the bi-matrix games with crisp parametric payoffs based on interval value function approach. We conclude that the equilibrium solution of the game model can converted into optimal solutions of the pair of the non-linear optimization problem. Finally, experiment results show the efficiency of the model.

Water soluble polymers have gained an increasing interest in enhanced oil recovery (EOR) processes, especially as polymer flooding. Despite the fact that the flow of polymer in porous medium has been a research subject for many decades with numerous publications, there are still some research areas that need progress. The prediction of polymer injectivity remains elusive. Polymers with similar shear viscosity might have different in-situ rheological behaviors and may be exposed to different extent of mechanical degradation. Hence, determining polymer in-situ rheological behavior is of great significance for defining its utility. In this study, an investigation of rheological properties and mechanical degradation of different HPAM (partially hydrolyzed polyacrylamide) polymers was performed using Bentheimer sandstone outcrop cores. Results show that, HPAM in-situ rheology is different from bulk rheology measured in rheometer. Specifically, shear thickening behavior occurs at high rates, and near-Newtonian behavior is measured at low rates in porous media. This deviates strongly from measurements in the rheometer. Polymer molecular weight and concentration influence its viscoelasticity and subsequently its flow characteristics in porous media. Exposure to mechanical degradation by flow at high rate through porous media leads to significant reduction in shear thickening and thereby improved injectivity. More importantly, the degraded polymer maintained in-situ viscosity at low flow rates indicating that improved injectivity can be achieved without compromising viscosity at reservoir flow rates. This is explained by reduction in viscoelasticity. Mechanical degradation also leads to reduced residual resistance factor (RRF), especially for high polymer concentrations. For some of the polymer injections, successive degradation (increased degradation with transport length in porous media) was observed. The results presented here may be used to optimize polymer injectivity.

The Urban Heat Island (UHI) is one of the more serious consequences of urbanization resulting in impacts on thermal comfort levels, heat stress, and even mortality. For Municipal Beirut, implementation of “cool” surface materials and green spaces have been recommended to counterbalance the UHI. This paper builds on previous findings on the topic of non-constructible parcels within the district of Bachoura in Municipal Beirut and examines the possibility of implementing “cool” surface or paving materials and urban vegetation which can improve thermal conditions especially during the summer period and with the viewto project the positive findings of this case study to the entire Municipal Beirut area. A numerical analysis using ENVI-met 4.0 investigates the thermal performance of these non-constructibles further to implementation of high reflective surfaces and urban vegetation within a broad neighborhood scale in Bachoura. Results show reductions in ambient temperatures up to 1K on a summer day.. Within the framework of an integrated approach to planning, this form of urban acupuncture aims for substantial UHI reduction. Energy performance of buildings further to implementation of these mitigation measures is also recommended for future studies and to validate the findings in this paper.

Small non-coding RNAs (sRNAs) are ubiquitously found in the three domains of life playing large-scale roles in gene regulation, transposable element silencing, and defense against foreign elements. While a substantial body of experimental work has been done to uncover function of sRNAs in Bacteria and Eukarya, the functional roles of sRNAs in Archaea are still poorly understood. Recently, high throughput studies using RNA-sequencing revealed that sRNAs are broadly expressed in the Archaea, comprising thousands of transcripts within the transcriptome during non-challenged and stressed conditions. Antisense sRNAs, which overlap a portion of a gene on the opposite strand (cis-acting), are the most abundantly expressed non-coding RNAs and they can be classified based on their binding patterns to mRNAs (3’ UTR, 5’ UTR, CDS-binding). These antisense sRNAs target many genes and pathways, suggesting extensive roles in gene regulation. Intergenic sRNAs are less abundantly expressed and their targets are difficult to find because of a lack of complete overlap between sRNAs and target mRNAs (trans-acting). While many sRNAs have been validated experimentally, a regulatory role has only been reported for very few of them. Further work is needed to elucidate sRNA-RNA binding mechanisms, the molecular determinants of sRNA-mediated regulation, whether protein components are involved, and how sRNAs integrate with complex regulatory networks.

The mitigation of NLOS (non-line-of-sight) propagation conditions is one of main challenges in wireless signals based indoor localization. When RFID localization technology is applied in applications, RSS fluctuates frequently due to the shade and multipath effect of RF signal, which could result in localization inaccuracy. In particularly, when tags carriers are walking in LOS (line-of-sight) and NLOS hybrid environment, great attenuation of RSS will happen, which would result in great location deviation. The paper proposes an IMU-assisted (Inertial Measurement Unit) RFID based indoor localization in LOS/NLOS hybrid environment. The proposed method includes three improvements over previous RSS based positioning methods: IMU aided RSS filtering, IMU aided LOS/NLOS distinguishing and IMU aided LOS/NLOS environment switching. Also, CRLB (Cramér-Rao Low Bound) is calculated to prove theoretically that indoor positioning accuracy for proposed method in LOS/NLOS mixed environment is higher than position precision of only use RSS information. Simulation and experiments are conducted to show that proposed method can reduce the mean positioning error to around 3 meters without site survey.

Vibration measurement serves as the basis for various engineering practices such as natural frequency or resonant frequency estimation. As image acquisition devices become cheaper and faster, vibration measurement and frequency estimation through image sequence analysis continue to receive increasing attention. In the conventional photogrammetry and optical methods of frequency measurement, vibration signals are first extracted before implementing the vibration frequency analysis algorithm. In this work, we demonstrated that frequency prediction can be achieved using a single feed-forward convolutional neural network. The proposed method is verified using a vibration signal generator and excitation system, and the result obtained was compared with that of an industrial contact vibrometer in a real application. Our experimental results demonstrate that the proposed method can achieve acceptable prediction accuracy even in unfavorable field conditions.

Acquisition of real-time hydraulic data is an essential component for flood forecasting. However, we frequently face difficulties in obtaining discharge data using classical contact methods during high magnitude floods and for systems experiencing rapid hydro-geomorphological adjustment. Therefore, we developed low-cost, non-contact sensors and platforms that are designed to overcome these difficulties. These advances enable flood flow properties to be monitored at multiple locations across a river catchment, at low-cost, and communicated in near real-time by using an image velocimetry method. This is an optics-based approach for stream flow measurement using commercially available near-infrared digital cameras to acquire video footage in full HD (30fps). Video footage is then subjected to optical flow tracking techniques based on cross-correlation, and feature-based tracking, enabling the displacement rates of detected features (for example natural foam, seeds, woody debris, and turbulent structures) to be computed. This manual provides step by step guidance to install an image-based gauging station. It contains the list of necessary components, the calibration process of a new camera and the assembly procedure of the system.

Human factors are the most relevant issues contributing to adverse events in obstetrics. Specific training of Crisis Resource Management (CRM) skills (i.e., problem solving and team management, resource allocation, awareness of environment, and dynamic decision-making) are now widespread and are often based on High Fidelity Simulation. In order to be used as a guideline in simulated scenarios, they need to be translated into specific and observable behavioral markers. To this purpose, we developed a set of observable behaviors related to the main elements of CRM in the delivery room. The observational tool was then adopted in a two-days seminar on obstetric hemorrhage where teams working in obstetric wards of six Italian hospitals took part to simulations. The tool was used as guide for the Io and as a peer-to-peer feedback. It was then rated for its usefulness in facilitating the reflection upon one’s own behavior, its ease of use, and its usefulness for the peer-to-peer feedback. The ratings were highly positive, around 4 in a 5-point scale. The CRM observational tool is therefore a useful, quick and easy solution to facilitate the debriefing, the peer-to-peer feedback and, most of all, the transfer of safe behavior from simulation to everyday practice.

The importance and near ubiquity of the Golden Ratio in disciplines like chemistry and biology is well known, but only recently has it come to light in areas pertaining to the Quantum domain. By using a modified tool-kit of hyper-complex numbers (known as Dimensional Gate Operators) and numerical analysis, we uncover a connection between hyper-dimensional objects, the Fibonacci sequence and that of quasiparticles and excitations. The results show that dimensionality increases in step with the Fibonacci sequence.

This publication delves into the intricate world of human communication, extending beyond the realm of spoken and written language to explore the profound influence of non-verbal communication. Focusing on body language—comprising gestures, facial expressions, postures, and movements—it reveals the pivotal role it plays in conveying emotions, intentions, and psychological states. The rapidly evolving fields of neuroscience and cognitive science are investigating the neural mechanisms and cognitive processes that underpin the interpretation and utilization of these non-verbal cues. Notably, the amygdala's involvement in processing emotional facial expressions has provided a neurological foundation for our emotional understanding in non-verbal communication. Concurrently, cognitive psychology sheds light on how perception, attention, and memory influence our interpretation of non-verbal cues and communication strategies.In our modern, technologically advancing society characterized by global interconnectivity and cultural diversity, the significance of non-verbal communication, especially in digital and virtual contexts, is paramount. The transformation of non-verbal expression into digital symbols like emoticons and emojis raises questions regarding its ability to maintain authenticity and emotional understanding. This publication endeavors to comprehensively explore the fundamental role of body language and non-verbal communication in contemporary society. By integrating insights from psychology, neuroscience, social sciences, and digital technologies, it aims to elucidate the underlying mechanisms guiding non-verbal communication. Additionally, it delves into the implications of non-verbal communication across diverse domains, including interpersonal communication, the workplace, politics, advertising, and the virtual world.The research presented herein strives to offer a thorough understanding of interpersonal dynamics, relationships, and social behavior, with the goal of promoting the development of more effective, conscious, and ethically guided communication strategies. Ultimately, this analysis aspires to inspire further interdisciplinary research and reflection, addressing emerging challenges and fully leveraging the potential of non-verbal communication in modern society. This, in turn, guides our path towards a communication landscape that is more inclusive, authentic, and empathetic.

Magnetic nanoparticles are met across many biological species ranging from magnetosensitive bacteria, fishes, bees, bats, rats, birds, to humans. They can be both of biogenetic origin and due to environmental contamination, being either in paramagnetic or ferromagnetic state. The energy of such naturally occurring single-domain magnetic nanoparticles can reach up to 10-20 room k_BT in the magnetic field of the Earth, which naturally led to supposition that they can serve as sensory elements in various animals. This work explores within a stochastic modeling framework a fascinating hypothesis of magnetosensitive ion channels with magnetic nanoparticles serving as sensory elements, especially, how realistic it is given a highly dissipative viscoelastic interior of living cells and typical sizes of nanoparticles possibly involved.

Biomimicry in additive manufacturing often refers to topology optimization and the use of lattice structures, due to the organic shape of the topology-optimized designs, and the lattices often looking similar to many light-weight structures found in nature such as trabecular bone, wood, sponges, coral, to name a few. Real biomimetic design however involves the use of design principles taken in some way from natural systems. In this work we use a methodology whereby high resolution 3D analysis of a natural material with desirable properties is “reverse-engineered” and the design tested for the purpose. This allows more accurate replication of the desired properties, and adaption of the design parameters to the material used for production (which usually differs from the biological material). One such example is the impact-protective natural design of the glyptodont body armour. In this paper we report on the production of body armour models in metal (Ti4Al4V) and analyze the resulting mechanical properties, assessing their potential for impact protective applications. This is the first biomimetic study using metal additive manufacturing to date.

Pain is a major problem in sick newborn infants, especially for those needing intensive care. Pharmacological pain relief is the most commonly used but may be ineffective, have side effects, including long-term neurodevelopmental sequelae. The effectiveness and safety of alternative analgesic methods are ambiguous. The objective is to review the effectiveness and safety of non-pharmacological methods of pain relief in newborn infants and to identify those that are the most effective. PubMed and Google Scholar were searched using the terms: ‘infant’, ‘premature’, ‘pain’, ‘acupuncture’, ‘skin to skin contact’, ‘sucrose’ ‘massage’, ‘musical therapy’ and ‘breastfeeding’. We included 24 studies assessing different methods of non-pharmacological analgesic techniques. Most resulted in some degree of analgesia but many were ineffective and some were even detrimental. Sucrose, for example, was often ineffective but more effective than music therapy, massage, breast milk (for extremely premature infants) or non-invasive electrical stimulation acupuncture. There were also conflicting results for acupuncture, skin to skin care and musical therapy. Most non-pharmacological methods of analgesia provide some modicum of relief for preterm infants but none are completely effective and there is no clearly superior method. Study is also required to assess potential long-term consequences of any of these methods.

Breast cancer is the most common malignancies in women and the second leading cause of cancer death in women. Triple negative breast cancer (TNBC) subtype is a breast cancer subset without ER, PR and HER2 expression, limiting treatment options and presenting a poorer survival rate. Thus, we investigated whether HDACi would be used as potential anti-cancer therapy on breast cancer cells. In this study, we found TNBC and HER2-enrich breast cancers are extremely sensitive to Panobinostat, Belinostat of HDACi via experiments of cell viability assay, apoptotic marker identification and flow cytometry measurement. On the other hand, we developed a bioluminescence based live cell non-invasive apoptosis detection sensor (IADS) detection system to evaluate the quantitative and kinetic analyses of apoptotic cell death by HDAC treatment on breast cancer cells. In addition, the use of HDACi may also be accompanied with chemotherapeutic agent such as doxorubicin to synergic drug sensitivity on TNBC cell (MDA-MB-231), but not in breast normal epithelia cells (MCF-10A), providing therapeutic benefits against breast tumor in clinic.

Extracellular vesicles (EVs) represent a heterogeneous population of small vesicles, consisting of a phospholipidic bilayer surrounding a soluble interior cargo. Almost all cell types release EVs, thus they are naturally present in all body fluids. Among the several potential applications, EVs could be used as drug delivery vehicles in disease treatment, in immune therapy because of their immunomodulatory properties and in regenerative medicine. In addition to general markers, EVs are characterized by the presence of specific biomarkers (proteins, miRNAs) that allow the identification of their cell- or tissue-origin. For these features, they represent a potential powerful diagnostic tool to monitor state and progression of specific diseases. As regards, a large body of studies supports the idea that endothelial derived (EMPs) together with platelet-derived microparticles (PMPs) are deeply involved in the pathogenesis of diseases characterized by micro- and macrovascular damages, including diabetes. Existing literature suggests that the detection of circulating EMPs and PMPs and their specific miRNA profile may represent a very useful non-invasive signature to achieve informations about the onset of peculiar disease manifestations. In this Review, we discuss the possible utility of EVs in the early diagnosis of diabetes-associated microvascular complications, specifically related to kidney.

Abstract Due to the relatively low efficiency of thermoelectric (TE) generators, they have mostly been used in niche applications where the unique properties of TE generators outweigh their lack of efficiency, or conditions where it is more reasonable to base the optimal design on maximum generated power rather than maximum efficiency. The aim of this work is to investigate how the different fundamental transport properties (Seebeck coefficient, thermal conductivity and electrical resistivity) in materials with equal figure of merit (ZT) impact TE module design and maximum power output. Further, we discuss and review the strategies to enhance material properties and the latest studies on the TE module performance. It is shown, that by increasing the power factor by a factor of 15 and decreasing the thermal conductivity by 13.33 in order to maintain ZT=1, power output is increased by 45%. This effect is stronger in lower module fill factor and thermal resistance of the heat source and heat sink.

Below T_CO=157 K the quasi-one-dimensional charge-transfer salt (TMTTF)_2SbF_6 undergoes a pronounced phase transition to a charge-ordered ground state. We have explored the non-linear and photoconductive behavior as a function of applied voltage, laser pulse energy and temperature. Besides a decay of the photoconductive signal in a double exponential fashion in the millisecond range, we discover current oscillations in the kHz range induced by the application of short laser pulses. While the resonance frequencies do not depend on voltage or laser intensity and vary only slightly with temperature, the amplitude changes linearly with the laser intensity and voltage. The findings are discussed and compared to comparable phenomena in other low-dimensional electron systems.

Medical institutions, where several patients are treated and medical workers engaged, are always exposed to secondary viral and bacterial infections. It is critical to prevent infection transmission by indirect as well as direct contact through air or splash. The infections of most diseases can be transmitted through the air. HEPA filters installed in air conditioning equipment are used to prevent infection transmission through air in medical institutions, but air circulation takes a long time in a large space. Virus and bacteria smaller than 0.3 μm cannot be removed by the HEPA filter; hence, those microbes remain alive throughout the air ventilation. A plasma sterilizer has the capability to provide environmental friendly sterilization by employing reactive oxide species and reactive nitrogen species at a low cost. We developed an excellent plasma sterilizer by using a non-thermal atmospheric-pressure biocompatible plasma (NBP). Ozone concentration in plasma sources has been derived by Kuhn et al. [1]. The diffusion coefficients inside (D₀) and outside (D₁) the plasma sterilizer have been calculated to be 0.0641 m² s^-1 and 0.717 m² s^-1, respectively. To sustain high O₃ concentrations over 121 ppm inside the plasma source and low O₃ concentrations below 0.05 ppm outside the sterilizer, it is necessary to keep O₃ concentrations at the exit of plasma sterilizer below 0.28 ppm. so that diffusion coefficient D₁ has been designed to be as large as 11 times of D₀.

With the development of data science, more and more machine learning technologies have been designed to solve complicated and challenging real-world tasks containing a large volume of data. And many significant real-world datasets contain data in the form of networks or graphs. Graph Neural Networks is one of the powerful machine learning tools, which could provide a perfect solution to processing a large amount of non-Euclidean data. And because most bio information data in bioinformatics is in the non-Euclidean domain, Graph Neural Networks could then directly be applied to solve problems in bioinformatics. Much research has been done in the field of GNN, and there are also some surveys related to GNN and its applications. However, there has been little research focusing on GNN in bioinformatics, and we think in the future we could better utilize GNN in the field of biology, so we would like to write a literature review to help take a comprehensive look at GNN and their applications in the field of bioinformatics. In this paper, we would first introduce SOTA models in Graph Neural Networks, and second, introduce their applications in bio information. And then we would provide future directions of Graph Neural Networks in bioinformatics.

In this paper, an incremental eqivalent contact model is developed for elastic-perfectly plastic solids with rough surfaces. The contact of rough surface is modeled by the accumulation of circular contacts with varying radius, which is estimated from the geometrical contact area and the number of contact patches. For three typical rough surfaces with various mechanical properties, the present model gives accurate predictions of the load-area relation, which are verified by direct finite element simulations. An approximately linear load-area relation is observed for elastic-plastic contact up to a large contact fraction of 15%, and the influence of yield stress is addressed.

Past public health crises (e.g. tobacco, alcohol, opioids, cholera, HIV, lead, pollution, venereal disease, even COVID-19) have been met with interventions targeted both at the individual and all of society. While the healthcare community is very aware that the global pandemic of non-communicable diseases (NCD’s) has its origins in our Western ultraprocessed food diet, society has been slow to initiate any interventions other than public education, which has been ineffective, in part due to food industry interference. This article provides the rationale for such public health interventions, by compiling the evidence that added sugar, and by proxy the ultraprocessed food category, meets the four criteria set by the public health community as necessary and sufficient for regulation — addiction, toxicity, ubiquity, and externalities (how does your consumption affect me?). To its credit, some countries have recently heeded this science and have instituted sugar taxation policies to help ameliorate NCD’s within their borders. This article also supplies scientific counters to food industry talking points, in order to guide both scientists and policy makers in instituting further appropriate public health measures to quell this pandemic.

Efficiently targeted cancer therapy without causing detrimental side effects is necessary for alleviating patient care and improving survival rates. This paper presents observations of morphological changes in H1299 human lung cancer cells following W-band MMW irradiation (75 – 105 GHz) at a non-thermal power density of 0.2 mW/cm², investigated over 14 days of subsequent physiological incubation following exposure. Microscopic analyses of physical parameters measured indicate MMW irradiation induces significant morphological changes characteristic of apoptosis and senescence. The Immediate short-term responses translate into long-term effects, retained over the duration of the experiment(s); reminiscent of the phenomenon of Accelerated Cellular Senescence (ACS) achieving terminal tumorigenic cell growth. Further, results were observed to be treatment-specific in energy (dose) dependent manner and were achieved without the use of chemotherapeutic agents, ionizing radiation or thermal ablation employed in conventional methods; thereby overcoming associated side effects. Adaptation of the experimental parameters of this study for clinical oncology concomitant with current developmental trends of non-invasive medical endoscopy alleviates MMW therapy as an effective treatment procedure for human non-small cell lung cancer (NSCLC).

Power disaggregation aims at determining the appliance-by-appliance electricity consumption leveraging upon a single meter only, which measures the entire power demand. Data-driven procedures based on Factorial Hidden Markov Models have been proven remarkable results on energy disaggregation. Nevertheless, those procedures have various weaknesses: there is a scalability problem as the number of devices to observe raises and the algorithmic complexity of the inference step is severe. DNN architectures, such as Convolutional Neural Networks, have demonstrated to be a viable solution to deal with FHMMs shortcomings. Nonetheless, there are two significant limitations: a complicated and time-consuming training system based on back-propagation has to be employed to estimates the neural architecture parameters, and large amounts of training data covering as many operation conditions as possible need to be collected to attain top performances. In this work, we aim to overcome those limitations by leveraging upon the unique and useful characteristics of the extreme learning machine technique, which is based on a collection of randomly chosen hidden units and analytically defined output weights. Experiment evaluation has been conducted using the UK-DALE corpus. We find that the suggested approach achieves similar performances to recently proposed ANN-based methods and outperforms FHMMs. Besides, our solution generalises well to unseen houses.

Depending on human body conditions and environmental conditions, it is sometimes difficult to conduct subject experiments. In such cases, it is effective to use a thermal manikin. There are few studies that investigate the effect of the non-uniform and asymmetric outdoor thermal environment on the mean skin temperature. The purpose of this study is to clarify the influence of the non-uniform and asymmetric thermal radiation of short-wavelength solar radiation in an outdoor environment on the calculation of the mean skin temperature. The skin temperature of the front of the coronal surface, which was facing the sun and where the body received direct short-wavelength solar radiation, and the skin temperature of the rear of the coronal surface, which was in the shadow and did not receive direct short-wavelength solar radiation were respectively measured. The feet, upper arm, forearm, hand and lower leg, which are susceptible to short-wavelength solar radiation in a standing posture, had a noticeable difference in skin temperature between sites in the sun and in shade. The mean skin temperature of sites facing the sun was significantly higher than the mean skin temperature of those in the shade.

The Gilles de la Tourette syndrome (GTS) and Non-Coeliac Gluten Sensitivity (NCGS) may be associated. We analyse the efficacy of a gluten-free diet (GFD) in 29 patients with GTS (23 children; 6 adults) in a prospective pilot study. All of them followed a GFD for one year. The YGTSS, Y-BOCS/CY-BOCS and GTS-QOL questionnaires were compared before and after the GFD. 74% of children and 50% of adults were males, not significant (NS). At the beginning of the study, 69% of children and 100% of adults had associated OCD (NS). At baseline, the YGTSS scores were 55.0 ± 17.5 (children) and 55.8 ± 19.8 (adults) (NS), the Y-BOCS/CY-BOCS scores were 15.3 (SD = 12.3) (children) and 26.8 (9.2) (adults) (p = 0.043), and the GTS-QOL scores were 42.8 ± 18.5 (children) and 64 ± 7.9 (adults) (p = 0.000). NCGS was frequent in both groups, with headaches reported by 47.0% of children and 83.6% of adults (p = 0.001). After one year on a GFD there was a marked reduction in measures of tics (YGTSS) (p = 0.001), and the intensity and frequency of OCD (Y-BOCS/CY-BOCS) (p = 0.001), along with improved QOL (p = 0.001) in children and adults. In conclusion, a GFD maintained for one year in GTS patients led to a marked reduction in tics and OCD both in children and adults.

The growth of regularly generated data from many financial activities has significant implications for every corner of financial modeling. This study has investigated the utilization of these continuous growing data by a means of an automated process. The automated process can be developed by using Machine learning based techniques that analyze the data and gain experience from the underlying data. Different important domains of financial fields such as Credit card fraud detection, bankruptcy detection, loan default prediction, investment prediction, marketing and many other financial models can be modeled by implementing machine learning models. Among several machine learning based techniques, the use of parametric and non-parametric based methods are approached by this research. Two parametric models namely Logistic Regression, Gaussian Naive Bayes models and two non-parametric methods such as Random Forest, Decision Tree are implemented in this paper. All the mentioned models are developed and implemented in the field of Credit card fraud detection, bankruptcy detection, loan default prediction. In each of the aforementioned cases, the comparative study among the classification techniques is drawn and the best model is identified. The performance of each classifier on each considered domain is evaluated by various performance metrics such as accuracy, recall, precision, F1-score and mean squared error. In the credit card fraud detection model the decision tree classifier performs the best with an accuracy of 99.1% and, in the loan default prediction and bankruptcy detection model, the random forest classifier gives the best accuracy of 97% and 96.84% respectively.

Predicting the growth response of seedlings from the environmental responses of photosynthesis and metabolism may be improved by considering the dynamics of non-structural carbohydrate, NSC, over a diurnal cycle. Attenuation of growth metabolism when NSC content is low could explain why some NSC is conserved through the night. A dynamic model, incorporating diurnal variation in NSC, was developed to simulate growth of seedlings hour-by-hour. I compared predictions of this model to published growth and NSC data for seedlings that varied according to temperature, light, day length, or CO₂. Prolonged-darkness experiments showed a temperature dependent upper limit on the respiration capacity. Respiration was attenuated as NSC was depleted. Furthermore, when NSC was high at dawn, inhibition of photosynthesis could attenuate the accumulation of NSC under low temperature, or high light, or high CO₂. These concepts were used to simulate plant metabolism and growth rates and diurnal variation of NSC in tomato seedlings under two light levels and various temperatures. Comparison of other results using the same model parameters showed the dynamic model could predict results for starch and starch-less plants, and when growth was affected by CO₂ enrichment and day length.

We introduce poly-symplectic extension of Souriau Lie groups Thermodynamics based on higher-order model of statistical physics introduced by R.S. Ingarden. This extended model could be used for small data analytics and Machine Learning on Lie groups. Souriau Geometric Theory of Heat is well adapted to describe density of probability (Maximum Entropy Gibbs density) of data living on groups or on homogeneous manifolds. For Small Data Analytics (Rarified Gases , sparse statistical survey,…), density of maximum entropy should consider Higher Order Moments constraints (Gibbs density is not only defined by first moment but fluctuations request 2nd order and higher moments) as introduced by R.S. Ingarden. We use Poly-sympletic model introduced by Christian Günther, replacing the symplectic form by a vector-valued form. The poly-symplectic approach generalizes the Noether theorem, the existence of momentum mappings, the Lie algebra structure of the space of currents, the (non-)equivariant cohomology and the classification of G-homogeneous systems. The formalism is covariant, i.e. no special coordinates or coordinate systems on the parameter space are used to construct the Hamiltonian equations. We underline the contextures of these models, and the process to build these generic structures.

This paper considers a non-mixture cure model for right censored data. It utilizes the maximum likelihood method to estimate model parameters in the non-mixture cure model. The simulation study is based on Fréchet susceptible distribution to evaluate the performance of the method. Comparing with Weibull and exponentiated exponential distributions, the non-mixture Fréchet distribution is shown to be the best in modeling a real data on allogeneic marrow HLA-matched donors and ECOG phase III clinical trial e1684 data.

Telemedicine is the use of Information and Communication Technology (ICT) for clinical health care from a distance. The exchange of radiographic images and electronic patient health information/records (ePHI/R) for diagnostic purposes has the risk of confidentiality, ownership identity, and authenticity. In this paper, a data hiding technique for ePHI/R is proposed. The color information in the cover image is used for key generation, and stego-images are produced with ideal case. As a result, the whole stego-system is perfectly secure. This method includes the features of watermarking and steganography techniques. The method is applied to radiographic images. For the radiographic images, this method resembles watermarking, which is an ePHI/R data system. Experiments show promising results for the application of this method to radiographic images in ePHI/R for both transmission and storage purpose.

We analyzed the characteristics of the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) infected children during lock-down period in Catalonia (Spain), and their transmission role within the households. Among 295 traced household contacts of 89 pediatric patients, children were classified as final index cases in only 3.4% of the traced homes.

Electromagnetic eddy current sensors are commonly used to identify and quantify the surface notches of metals. However, the unintentional tilt of eddy current sensors affects results of size profiling, particularly for the depth profiling. In this paper, based on the eddy current thin-skin regime, a revised algorithm has been proposed for the analytical voltage or impedance of a tilted driver–pickup eddy current sensor scanning across a long ideal notch. Considering the resolution of the measurement, the bespoke driver–pickup, also termed as transmitter-receiver (T-R) sensor is designed with a small mean radius of 1 mm. Besides, the T-R sensor is connected to the electromagnetic instrument and controlled by a scanning stage with high spatial travel resolution , with a limit of 0.2 μm and selected as 0.25 mm. Experiments have been out on the voltage imaging of an aluminium sheet with 7 machined long notches of different depths using T-R sensor under different tilt angles. By fitting the measured voltage (both real and imaginary part) with proposed analytical algorithms, the depth profiling of notches is less affected by the tilt angle of sensors. From the results, the depth of notches can be retrieved within a deviation of 10 % for tilt angles up to 60 degrees.

Abstract Introduction:The Robert Koch Institute (RKI) managed the exchange of cross-border contact tracing data between public health authorities (PHA) in Germany and abroad during the COVID-19 pandemic. Aim: We aimed to describe the extent of RKI cross-border contact tracing and the challenges experienced. Methods:We analysed cross-border COVID-19 contact tracing events from 03 February to 05 April 2020 using information exchanged through the European “Early Warning Response System” (EWRS) as well as communication with International Health Regulation (IHR) national focal points. We described events by PHA involved, number of contact persons and exposure context. Results:The RKI processed 467 events, initiating contact to PHA 1,099 times (median 1, IQR [1;2]) and sharing data on 5,099 contact persons. Of 327 (70%) events with known exposure context, most common reported were exposures on aircraft 64 (14%), on cruise ships 24 (5%) and exposures related to non-transport contexts 210 (45%). Cruise ship and aircraft exposures yielded higher median numbers of authorities contacted (10[2;16], 4[2;11]) and contact persons (60 [9;269], 2[1;3]) than non-transport related exposures (1[1;6] and 1[1;2]), respectively. The median time spend on contact tracing activities was the highest for cruise ships: 5 days [IQR 3;9]. Conclusion:In the current COVID-19 pandemic cross-border contact tracing is considered a critical component of the outbreak response. While the majority of international contact tracing activities did not relate to exposure events in transport, they contributed substantially to the workload. The numerous communications highlight the need for fast and efficient global outbreak communication channels between PHA.

Human non-conscious reasoning is one of the most successful procedures developed to solve everyday problems in an efficient way. This is why the field of artificial intelligence should analyze, formalize and emulate the multiple ways of non-conscious reasoning with the purpose of applying them in knowledge based systems, neurocomputers and similar devices for aiding people in the problem-solving process. In this paper, a framework for those non-conscious ways of reasoning is presented based on object-oriented representations, fuzzy sets and multivalued logic.

This paper introduces a novel respiratory detection system based on diaphragm wall motion tracking using an embedded ultrasound sensory system. We assess the utility and accuracy of this method in evaluating diaphragmatic function and its contribution to respiratory workload. The developed system is able to monitor the diaphragm wall activities when the sensor is placed in the zone of apposition (ZOA). This system allows the direct measurements with only one ultrasound PZT5 piezo transducer. The system both generates pulsed ultrasound waves at 2.2 MHz and amplifies reflected echoes. According to the diaphragmatic motions, the respiratory signals of the proposed system is insensitive to human motion artifacts. Promising results were obtained from six subjects on six different tests with an average sensitivity and specificity of 84% and 93% of respiration detection, respectively. Measurements are referenced to a SPR-BTA commercial spirometer. In this study, we also evaluated inertial and photoplethysmography (PPG) sensors as other conventional methods in this area.

Ultraviolet light incident on organic material can initiate its spontaneous dissipative structuring into chromophores which can catalyze their own replication. This may have been the case for one of the most ancient of all chromophores dissipating the Archean UVC photon flux, the nucleic acids. Oligos of nucleic acids with affinity to particular amino acids which foment UVC photon dissipation would have been selected through non-equilibrium thermodynamic imperatives which favor entropy production. Indeed, we show here that those amino acids with characteristics most relevant to fomenting UVC photon dissipation are precisely those with greatest chemical affinity to their codons or anticodons. Entropy production could thus provide an explanation for the accumulation of information in nucleic acids relevant to the dissipation of the externally imposed thermodynamic potentials. The accumulation of information in this manner provides a link between evolution and entropy production.

Matiyasevich's theorem states that there is no algorithm to decide whether or not a given Diophantine equation has a solution in non-negative integers. Smorynski's theorem states that the set of all Diophantine equations which have at most finitely many solutions in non-negative integers is not recursively enumerable. We prove: (1) Smorynski's theorem easily follows from Matiyasevich's theorem, (2 ) Hilbert's Tenth Problem for Q has a negative solution if and only if the set of all Diophantine equations with a finite number of rational solutions is not recursively enumerable.

Computers and artificial intelligence affect every field of life nowadays. In medical image interpretation automatic decision making using algorithms are used increasingly in every sub-field and computer aided diagnosis (CAD) is one of the main tools available to medical science today. CAD systems are used as an augmented option for both the medical practitioner and the patients, with image analysis and interpretation being of primary importance. In particular, spatial relations are used in knowledge representation, and these relations can be used for effective medical image interpretation. In this paper, we put forth an algorithm for defining non-small cells lungs cancer (NSCLC) stages in lungs images interpretation using topological spatial relations. We show an application case study in event motion predictions for lung cancer staging scoring - tumor, nodes and metastasis (TNM) - with combined topological and directional relations.

In this paper, we established the existence of PC-mild solutions for non local fractional impulsive functional integro-differential equations with finite delay. The proofs are obtained by using the techniques of fixed point theorems, semi-group theory and generalized Bellman inequality. In this paper, we have used the distributed characteristic operators to define the mild solution of the system. Results obtained here improve and extend some known results.

Low back pain (LBP) is a leading cause of disability. It significantly impacts the patient’s quality of life, limits their daily living activities, and reduces work productivity. To reduce the burden of LBP, several pharmacological and non-pharmacological treatment options are available. This review summarizes the role of heat therapy in the management of LBP. First, we outline the common causes of LBP, then discuss the general mechanisms of heat therapy on (LB)P, and finally review the published evidence regarding the impact of heat therapy in patients with acute or chronic non-specific LBP. This review demonstrates that continuous, low-level heat therapy provides pain relief, improves muscular strength, and increases flexibility. Therefore, this effective, safe, easy-to-use, and cost-effective non-pharmacological pain relief option is still relevant in modern clinical practice.

Mitochondria are classically termed as powerhouse of a mammalian cell. Most of the cellular chemical energy in the form of adenosine tri phosphate (ATP) is generated by mitochondria and dysregulation of mitochondrial functions thus can be potentially fatal of cellular homeostasis and health. Acute respiratory distress has been earlier linked to mitochondrial dysfunction. SARS-CoV-2 infection severity leads to acute respiratory distress syndrome (ARDS) and can be fatal. We tried to investigate possible connection between SARS-CoV-2, ARDS and mitochondria. Here, we report identification of SARS-CoV-2 non-structural proteins (particularly Nsp12 and 13) that have recognition sequence with respect to mitochondrial entry. We also report that these proteins can potentially shuttle between cytoplasm and mitochondria based on the localization signals and help in downstream maintenance of the virus. Their properties to use ATP for enzymatic activities may cause ATP scavenging allowing viral RNA functions in lieu of host cell health.

Developing efficient Artificial Intelligence (AI)-enabled system to substitute human role in non-destructive testing is an emerging topic of considerable interest. In this study, we propose a novel impact-echo analysis system using online machine learning, which aims at achieving near-human performance for assessment of concrete structures. Current computerized impact-echo systems commonly employ lab-scale data to validate the models. In practice, however, the echo patterns can be far more complicated due to varying geometric shapes and materials of structures. To deal with a large variety of unseen data, we propose a sequential treatment for echo characterization. More specifically, the proposed system can adaptively update itself to approaching human performance in impact-echo data interpretation. To this end, a two-stage framework has been introduced, including echo feature extraction and the model updating scheme. Various state-of-the-art online learning algorithms have been reviewed and evaluated for the task. To conduct experimental validation, we collected 10,940 echo instances from multiple inspection sites with each sample had been annotated by human experts with healthy/defective condition labels. The results demonstrated that the proposed scheme achieved favorable echo pattern classification accuracy with high efficiency and low computation load.

Long non-coding RNAs (lncRNAs) have been found to be involved in many biological processes, including the regulation of cell differentiation, but a complete characterization of lncRNA is still lacking. Additionally, there is evidence that lncRNAs interact with ribosomes, raising questions about their functions in cells. Here, we used a developmentally staged protocol to induce cardiogenic commitment of hESCs and then investigated the differential association of lncRNAs with polysomes. Our results identified lncRNAs in both the ribosome-free and polysome-bound fractions during cardiogenesis and showed a very well-defined temporal lncRNA association with polysomes. Clustering of lncRNAs was performed according to the gene expression patterns during the five timepoints analyzed. In addition, differential lncRNA recruitment to polysomes was observed when comparing the differentially expressed lncRNAs in the ribosome-free and polysome-bound fractions or when calculating the polysome-bound vs ribosome-free ratio. The association of lncRNAs with polysomes could represent an additional cytoplasmic role of lncRNAs, e.g., in translational regulation of mRNA expression.

Covid-19 pandemic lockdown has slow down the world economic system. The pandemic has cleared the roads, close factories and grounded planes causing severe economic challenges. The damaging impact of the pandemic amid lockdown has been a blessing in guise for the environment because of significant drop in pollution level as transport and industrial sectors shutdown. Transport and industrial sectors are major contributors to environmental degradation through various emissions as a result of fossil fuel consumption. Energy consumed by transport and industrial sectors will have to shift to viable, readily available, economically and environmentally friendly with no carbon build up post Covid-19 pandemic. Hydrogen energy remains the best alternative option technologies containing green house gas emission and pollutions of several forms. Hydrogen holds the potential to provide a clean, reliable, renewable and economical source of energy for meeting the growing and unending global energy needs post pandemic. The present paper explores the economic feasibility and potential of hydrogen to serve as a competitive fuel option post pandemic. In this paper, the role of hydrogen as an energy carrier hydrogen economy structure, potential of hydrogen economy, hydrogen production methods, hydrogen application and the economic and environmental importance of hydrogen as a viable fuel option post covid-19 pandemic were discussed. There will be a surge in demand and investment for hydrogen economy post Covid-19.

Artificial Intelligence is increasingly being used by social media platforms to tackle online hate speech. The sheer quantity of content, the speed at which is it developed and the enhanced pressure companies are facing by States to remove hate speech quickly from their platforms have led to a tricky situation. This commentary argues that automated mechanisms, which may have biased datasets and be unable to pick up on the nuances of language, should not be left unattended with hate speech as this can lead to issues of violating freedom of expression and the right to non-discrimination.

Atherosclerosis (ATH) and Coronary Artery Disease (CAD) are chronic inflammatory diseases with an important genetic background which derive from the cumulative effect of multiple common risk alleles, most of them located in genomic non-coding regions. These complex diseases behave as non-linear dynamical systems that show a high dependence on their initial conditions, so that long-term predictions of disease progression are unreliable. One likely possibility is that the non-linear nature of ATH could be dependent on non-linear correlations in the structure of the human genome. In this review we show how Chaos theory analysis highlighted genomic regions that shared specific structural constraints that could have a role in ATH progression. These regions were shown to be enriched in repetitive sequences of the Alu family, genomic parasites which colonized the human genome, which show a particular secondary structure and have been involved in the regulation of gene expression. We also review the impact of Alu elements on the mechanisms that regulate gene expression, especially highlighting the molecular mechanisms by which the Alu elements could alter the inflammatory homeostasis. We devise especial attention to their relationship with the lncRNA ANRIL, the strongest risk factor for ATH, their role as miRNA sponges, and their ability to interfere with the regulatory circuitry of the NF-kB response. We aim to characterize ATH as a non-linear dynamic system in which small initial alterations in the expression of a number of repetitive elements are somehow amplified to reach phenotypic significance.

This paper seeks to explain the rapid growth of the Islamic State of Iraq & Syria (ISIS) and approach the question of “what is” the Islamic State? The paper offers several contributions. First is the proposal of a dynamic hypothesis that ISIS is an emerging-state actor and differs notably from traditional non-state actors and insurgencies. The theory consists of both a causal loop diagram and key propositions. A detailed system dynamics simulation (E-SAM) was constructed to test the theory. The propositions of emerging-state actor theory are constructed as synthetic experiments within the simulation and confirm evidence of emerging-state actor behavior. E-SAM’s novelty is its combination of combat simulation with endogenous geospatial feedback, ethnographic behavior in choosing sides in conflict, and details internal simulation of key actor mechanisms such as financing, recruiting and governance. E-SAM can be loaded with scenarios to simulate non-state actors in different geospatial domains: ISIS in Libya, Boko Haram in Nigeria, Taliban in Afghanistan and even expatriated ISIS fighters returning to pursue new conflicts such as in Indonesia.

Many systems in nature and laboratories are far from equilibrium and exhibit significant fluc- tuations, invalidating the key assumptions of small fluctuations and short memory time in or near equilibrium. A full knowledge of Probability Distribution Functions (PDFs), especially time- dependent PDFs, becomes essential in understanding far-from-equilibrium processes. We consider a stochastic logistic model with multiplicative noise, which has gamma distributions as stationary PDFs. We numerically solve the transient relaxation problem, and show that as the strength of the stochastic noise increases the time-dependent PDFs increasingly deviate from gamma distributions. For sufficiently strong noise a transition occurs whereby the PDF never reaches a stationary state, but instead forms a peak that becomes ever more narrowly concentrated at the origin. The addition of an arbitrarily small amount of additive noise regularizes these solutions, and re-establishes the existence of stationary solutions. In addition to diagnostic quantities such as mean value, standard deviation, skewness and kurtosis, the transitions between different solutions are analyzed in terms of entropy and information length, the total number of statistically distinguishable states that a system passes through in time.

Sumudu transform of the Dixon elliptic function with non zero modulus a ≠ 0 for arbitrary powers sm^N(x,a) ; N ≥ 1 ; sm^N(x,a)cm(x,a) ; N ≥ 0 and sm^N(x,a)cm²(x,a) ; N ≥ 0 is given by product of Quasi C fractions. Next by assuming denominators of Quasi C fraction to 1 and hence applying Heliermann correspondance relating formal power series (Maclaurin series of Dixon elliptic functions) and regular C fraction, Hankel determinants are calculated and showed by taking a = 0 gives the Hankel determinants of regular C fraction. The derived results were back tracked to the Laplace transform of sm(x,a) ; cm(x,a) and sm(x,a)cm(x,a).

Intradermal injection of botulinum neurotoxin is a frequently performed procedure in aesthetic dermatology to improve facial skin tone, texture, fine wrinkles, and enlarged pores. In practice, botulinum neurotoxin type A is also used to reduce skin oiliness of the face. There is increasing evidence that acetylcholine plays specific roles in sebum production, suggesting that botulinum neurotoxin type A may reduce sebum production by interfering with cholinergic transmission between sebaceous glands and autonomic nerve terminals. Botulinum neurotoxins can also inhibit several pathogenetic components of acne development, suggesting that botulinum neurotoxins can be used as a safe and effective treatment modality for acne and other skin disorders related to the overactivity of sebaceous glands. This review aims to explore the current evidence behind the treatment of oily skin and acne with botulinum neurotoxin type A.

In this paper, a non-destructive test to diagnose wear of blade´s compressor of a gas turbine is reported. Gas turbine was operating in Campeche City, Mexico, in a very aggressive environment, where the entry of solid particles is unavoidable. The objective was to reduce cost of maintenance in this equipment. Analysis on a blade of gas turbine was performed, which was in operation on an offshore platform. Compressor blade was exposed to a severe damage by the impact of particles and environmental pollutants such as salts, sands and sulphurs. In first stage of this analysis, a visual inspection with a borescope was performed, which has the ability to illuminate dark internal areas, with a bright light for visual examination and/or make a photographic reproduction in semi-annual maintenance cycles. Images analysis was used to determine the typical failure modes. In a second stage, a tribological characterization was carried out. Chemical composition of the material of blades was obtained. Scanning electron microscopy (SEM) was used to measure roughness and evaluate degradation of surfaces of blades after 30,000 service hours. The points, where peak stresses were calculated, correspond to those places in witch corrosion and some irregular scratches similar to plowing action, was observed. These are the points in which failures take place. Results showed wear modes were originated by a severe stinging action. Also, large craters, similar to those observed in solid particle erosion, were developed by at normal impact. In the same way it could be found some localized areas with a witch corrosion and irregular scratches similar to plowing action, was observed. These are the points in which failures take place.

Objective: To recommend how physicians can best respond to families whose hopes for a miracle via divine intervention influence their medical decisions, like, for example, making them not want to withdraw ventilatory support in cases of poor neurologic prognosis because they are still hoping for God to intervene. Methods: Auto-ethnographic analysis of chaplaincy experience in this clinical context yields a nuanced 90-second, point-of-care spiritual intervention physicians can use to address the religious aspect of families who base medical decisions on their hopes for a miracle via divine intervention. Explanation of how spiritual intervention dovetails with existing physician communication protocol for responding to families hoping for a miracle. Results: Spiritual intervention for religious aspect of miracle-hoping families is integrated into existing physician communication protocol for responding to families hoping for a miracle with recommendations for utilization of existing communication technology when necessary. Conclusion: Properly addressing the religious dimension of families hoping for a miracle may be helpful for physicians interested in decreasing their own stress levels, improving outcomes for this clinical context, and ensuring that unintentional discrimination does not perpetuate racial disparities in end-of-life care.

This paper reviews non-intrusive load monitoring (NILM) approaches that employ deep neural networks to disaggregate appliances from low frequency data, i.e. data with sampling rates lower than the AC base frequency. We first review the many degrees of freedom of these approaches, what has already been done in literature, and compile the main characteristics of the reviewed publications in an extensive overview table. The second part of the paper discusses selected aspects of the literature and corresponding research gaps. In particular, we do a performance comparison with respect to reported MAE and F$_1$-scores and observe different recurring elements in the best performing approaches, namely data sampling intervals below 10\,s, a large field of view, the usage of GAN losses, multi-task learning, and post-processing. Subsequently, multiple input features, multi-task learning and related research gaps are discussed, the need for comparative studies is highlighted, and finally, missing elements for a successful deployment of NILM approaches based on deep neural networks are pointed out. We conclude the review with an outlook on possible future scenarios.

Liquid biopsies are an integral part of the diagnosis of cancer. Here, we have extended previous validation studies of a new targeted NGS panel to include the detection of copy number amplifications (CNAs), fusions, and exon skipping variants. Detection of these gene classes included specimens from clinical and healthy donors and cell lines (fusions: ROS1, EML4-ALK, NTRK1), (exon skipping: MET exon 14), and (CNAs: HER2, CDK6, EGFR, MYC and MET). The limit of detection (LOD) for fusion/skipping was 42 copies (QC threshold = 3 copies) and was verified using 3 additional fusion/skipping variants. LOD for CNAs was 1.40-fold-change (QC threshold = 1.15-fold change) and was verified with 3 additional CNAs. In precision studies, all fusion/skipping variants were detected in all runs and all days of testing (n=18/18; 100%); average CV for repeatability was 20.5% (range 8.7% - 34.8%), and for reproducibility was 20.8% (range 15.7% - 30.5%). For CNAs, 28/29 (96.6%) copy gains were detected. For CNAs, average CV of 1.85% (range 0% to 5.49%) for repeatability and 6.59% (range 1.65% to 9.22%) for reproducibility. The test panel meets the criteria for being highly sensitive and specific and extends its utility for the detection of clinically relevant variants in cancer.

This article makes a general analysis of the supply chain of photovoltaic systems in Colombia, taking as a starting point a conceptual base and the current situation of the country in this sector. This article especially will contemplate the non-interconnected areas (ZNI) to the electricity grid in the national, due to its complexity in the logistics issues. Likewise, the work performs a graphical representation of the stages and processes of the supply chain using a powerful-modeled tool such as the Petri Nets (PNs). Finally, it identifies some of the flaws in the operation and the joint of all the links of the logistic part and from there it is based the importance of the strategy of orientation to the supply chain (SCO) as a possible alternative to improve and to enhance the logistic processes of this type of systems.

COVID-19 is causing major turmoil around the globe, and the clinical trial industry is likely to face unprecedented challenges to health and business sectors. In an effort to find a suitable treatment and prevention options for COVID-19, several COVID-19 clinical trials are being planned and initiated, while a large number of clinical trials for non- COVID-19 indications are suffering delays. With over more than 1000 trials being disrupted and more trials being added to this category daily, there is a direct impact on trial site activation and patient enrolment. This analysis deals with the specific impacts of the COVID-19 pandemic on the clinical trial and pharmaceutical industry. The objective of this study is to provide an updated information of the disrupted clinical trials and its impact on various therapeutic areas and different drugs. Among the severely affected clinical trials, oncology and CNS trials are the hardest hit therapy areas.This article will certainly emphasize the need for advanced and innovative approaches to maintain the health of the clinical trial ecosystem by continuing the existing trials and the start of the new studies. We have to take and follow necessary actions to guarantee that the initiatives will not be locked during the COVID-19 pandemic, both for the treatment of patients and for the researchers to conduct decision-relevant clinical trials.

This paper builds upon a theory of emerging-state actors using ISIS as a case study. This paper seeks to apply the theory in analyzing intervention & containment policies to use against emerging-state actors, using ISIS as the case study. Two baseline scenarios are used for evaluation – one replicating the historical foreign intervention against ISIS and a counter-factual where no foreign intervention occurred. Eleven contemporary military policies were tested against these baseline in isolation, combination, at different timing windows and under hypothetical “best case” conditions as well as operationally constrained. Insights of these tests include the influence of ethnographic envelopes, timing windows. Finally, a policy based on emerging-state actor theory is tested performing substantially better across primary measures than other policies or the historical baseline. This is compared against a falsified-policy designed to disprove that emerging-state actor theory contributed to the benefits. This paper’s contributions are a practical application of system dynamics simulations and systems-thinking to current problems, generate insights into the dynamics of emerging-state actors and intervention strategies, and demonstrate utility for future application of the underlying simulation in other scenarios involving non-state actor irregular conflict including terrorism, insurgents, or emerging-state actors.

A temperate deep lake, Lake Kuttara, Hokkaido, Japan (148 m deep at maximum) was completely frozen every winter in the 20th century. However, unfrozen conditions of the lake over winter occurred four times in the 21st century, which is probably due to global warming. In order to understand how thermal regime of the lake responds to climate change, its heat storage change was calculated by estimating heat budget of the lake and monitoring water temperature at the deepest point for September 2012–June 2016. As a result, temporal change of the heat storage from the heat budget was very consistent with that from the direct temperature measurement (determination coefficient R² = 0.827). The 1978–2017 data at a meteorological station near Kuttara indicated that there are significant (less than 5% level) long-term trends for air temperature (0.024 °C/yr) and wind speed (−0.010 m/s/yr). A sensitivity analysis for the heat storage from the heat budget estimate and an estimate of return periods for mean air temperature in mid-winter allow us to conclude that the lake could be unfrozen once per about two year in a decade.

The scope of a lucrative career promoted by Google through its video distribution platform YouTube 1 has attracted a large number of users to become content creators. An important aspect of this line of work is the feedback received in the form of comments which show how well the content is being received by the audience. However, volume of comments coupled with spam and limited tools for comment classification makes it virtually impossible for a creator to go through each and every comment and gather constructive feedback. Automatic classification of comments is a challenge even for established classification models, since comments are often of variable lengths riddled with slang, symbols and abbreviations. This is a greater challenge where comments are multilingual as the messages are often rife with the respective vernacular. In this work, we have evaluated top-performing classification models and four different vectorizers, for classifying comments which are a mix of different combinations of English and Malayalam (only English, only Malayalam and Mix of English and Malayalam). The statistical analysis of results indicates that Multinomial Naïve Bayes, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Random Forest and Decision Trees offer similar level of accuracy in comment classification. Further, we have also evaluated 3 multilingual sub-types of the novel NLP language model, BERT and compared its’ performance to the conventional machine learning classification techniques. XLM was the top-performing BERT model with an accuracy of 67.31%. Random Forest with Term Frequency Vectorizer was the best the top-performing model out of all the traditional classification models with an accuracy of 63.59%.

This work promotes new methods in Mathematical Modeling, consisting in the use of the methods of Non-standard Analysis in Topoi, having as its main purpose, the mathematical definitions of the pseudoparticles from the title, with arguments from Biology/Physiology (Mathematical Neuroscience), Physics (String Theory and Emergent Quantum Mechanics), and Cybernetics (Global Brain, including Natural and Artificial Intelligence). The connections between brain and mind will be scketched via the genetic/epigenetic interplay. The topoi model the intuitionistic logic (multi-valued) and have been used in Quantum Physics while Non-Standard Analysis in SET (= the Category of sets) has been applied in Mathematical Economics; topics from Theory of Categories were also used in the study of Consciousness; however, the combination topoi - non-standard analysis was never used until now in Applied Mathematics. Another important objective is to produce progress in this aria of Pure Mathematics also - the build of non-standard analysis in classes of topoi, already used in Physics. We propose the logic of non-standard extensions in topoi as a model of the human thinking (based on infons/receptons), these theories representing new top and very difficult results in Abstract Mathematics either.

In this study, we used the natural and anthropogenic characteristics of a coastal region to generate risk maps showing vulnerability and potential hazards, and proposed design criteria for coastal defense and land use for the various kinds of risks faced. The Yunlin coast: a first-level protection area in mid-west Taiwan, was then used as an example to illustrate the proposed design criteria. The safety of the present coastal defenses and land use of the Yunlin coastal area was assessed, and coastal protection measures for hazard prevention were proposed based on the generated risk map. The results can be informative for future coastal management and the promotion of sustainable development of coastal zones.

In December 2019, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in the province of Wuhan, China. Since then, it has spread worldwide with new mutations being reported. We performed genomic analysis to identify the changes in genetic diversity of SARS-CoV-2 between December 2019 and November 2020, and through molecular surveillance, we monitored the mutations that could be involved in viral fitness. We analyzed 2,213 complete genomes from 6 geographical regions worldwide, which were downloaded from GenBank and GISAID databases. Although SARS-CoV-2 presented low genetic diversity, there has been an increase over time, with the presence of several hotspot mutations throughout its genome. We identified 7 frequent mutations that resulted in non-synonymous substitutions (dN). Two of them, C14408T>P323L and A23403G>D614G, located in the nsp12 and Spike protein, respectively, emerged early in the pandemic and showed a considerable increase in frequency over time. Two other mutations, A1163T>I120F in nsp2 and G22992A>S477N in the Spike protein emerged recently and have spread in Oceania and Europe. Continuous molecular surveillance of SARS-CoV-2 will be necessary to detect and describe the transmission dynamics of new variants of the virus with clinical relevance. This information is important to improve programs to control the virus.

Suitable measures of grazing impacts on ground cover, that enable separation of the effects of climatic variations, are needed to inform land managers and policy makers across the arid rangelands of the Northern Territory of Australia. This work developed and tested a time-series, change-point detection method for application to time series of vegetation fractional cover derived from Landsat data to identify irregular and episodic ground-cover growth cycles. These cycles were classified to distinguish grazing impacts from that of climate variability. A measure of grazing impact was developed using a multivariate technique to quantify the rate and degree of ground cover change. The method was successful in detecting both long term (> 3 years) and short term (< 3 years) growth cycles. Growth cycle detection was assessed against rainfall surplus measures indicating a relationship with high rainfall periods. Ground cover change associated with grazing impacts was also assessed against field measurements of ground cover indicating a relationship between both field and remotely sensed ground cover. Cause and effects between grazing practices and ground cover resilience can now be explored in isolation to climatic drivers. This is important to the long term balance between ground cover utilisation and overall landscape function and resilience.

Insufficient mixing in large-scale bioreactors, provokes gradient zones of substrate, dissolved oxygen, pH and other parameters. E. coli responds to a high glucose, low oxygen feeding zone with the accumulation of mixed acid fermentation products, especially formate, but also with the synthesis of non-canonical amino acids, such as norvaline, norleucine and -methyl-norleucine. These amino acids can be mis-incorporated into recombinant products, which causes a problem for pharmaceutical production whose solution is not trivial. While these effects can also be observed in scale down bioreactor systems, these are challenging to operate. Especially the high-throughput screening of clone libraries is not easy, as fed-batch cultivations would need to be controlled via repeated glucose pulses with simultaneous oxygen limitation, as has been demonstrated in well controlled robotic systems. Here we show that not only glucose pulses in combination with oxygen limitation can provoke the synthesis of these non-canonical branched-chain amino acids, but also that pyruvate pulses produce the same effect. Therefore we combined the enzyme based glucose delivery method Enbase® in a PALL24 mini-bioreactor system and combined repeated pyruvate pulses with simultaneous reduction of the aeration rate. These cultivation conditions, produced an increase in the non-canonical branched chain amino acids norvaline and norleucine in both the intracellular soluble protein and inclusion body fractions with mini-proinsulin as an example product, and this effect was verified in a 15 L stirred tank bioreactor. To our opinion this cultivation strategy is easy to apply for the screening of strain libraries under standard laboratory conditions if no complex robotic and well controlled parallel cultivation devices are available.

The expanding use of devices emitting Pulsed Telecommunication Signals (PTS) has launched a serious debate over the possible effects of electromagnetic radiation (EMR) on living organisms. Our previous work has indicated that PTS exposure alters Amyloid Precursor Protein (APP) and alpha-synuclein (α-syn) metabolism in human cells of neural origin, providing a possible connection between exposure and neurodegeneration. This investigation aimed to reveal, in vitro in human non-neural cells (HEK293), the aftermath of the same exposure on the processing of APP and α-syn. Data presented here, indicate changes in APP metabolism, acquisition of different cellular topologies of the newly generated APP fragments, changes in monomeric α-syn accumulation and multimerization, indicating that APP and α-syn processing is possibly altered in the periphery by EMR. These effects are accompanied by a substantial increase in the levels of Reactive Oxygen Species (ROS). Further investigation is required in order to provide insights into the interaction of PTS with non-neural cells affecting the peripheral systemic functional stability. This is necessary because nowadays whole body human exposure from various EMR sources is a fact in normal life with the valid estimation that they may be increased in view of the forthcoming 5G telecommunications network implementation.

The Cannabis plant (Cannabis sativa L.) produces an estimated 545 chemical compounds of different biogenetic classes. In addition to economic value, many of these phytochemicals have medicinal and physiological activity. The plant is most popularly known for its two most prominent and most studied secondary metabolites— Δ9-Tetrahydrocannabinol (Δ9-THC) and Cannabidiol (CBD). Both Δ9-THC and CBD have a wide therapeutic window across many ailments and form part of a class of secondary metabolites called cannabinoids—of which approximately over 104 exist. This review will focus on non-cannabinoid metabolites of Cannabis sativa that also have therapeutic potential, some of which share medicinal properties similar to those of cannabinoids. The most notable of these non-cannabinoid phytochemicals are flavonoids and terpenes. We will also discuss future directions in cannabis research and development of cannabis-based pharmaceuticals. Caflanone, a flavonoid molecule with selective activity against the human viruses including the coronavirus SARS-COV2, and certain cancers, is one of the most promising non-cannabinoid molecules that is being advanced into clinical trials. As validated by thousands of years of the use of cannabis for medicinal purposes, vast anecdotal evidence abounds on the medicinal benefits of the plant. These benefits are attributed to the many phytochemicals in this plant, including non-cannabinoids. The most promising non-cannabinoids with potential to alleviate global disease burdens are discussed.

The widely spread CoronaVirus Disease (COVID)- 19 is one of the worst infectious disease outbreaks in history and has become an emergency of primary international concern. As the pandemic evolves, academic communities have been actively involved in various capacities, including accurate epidemic estimation, fast clinical diagnosis, policy effectiveness evaluation and development of contract tracing technologies. There are more than 23,000 academic papers on the COVID-19 outbreak, and this number is doubling every 20 days while the pandemic is still on-going [1]. The literature, however, at its early stage, lacks a comprehensive survey from a data analytics perspective. In this paper, we review the latest models for analyzing COVID19 related data, conduct post-publication model evaluations and cross-model comparisons, and collect data sources from different projects.

We prove: (1) the set of all Diophantine equations which have at most finitely many solutions in non-negative integers is not recursively enumerable, (2) the set of all Diophantine equations which have at most finitely many solutions in positive integers is not recursively enumerable, (3) the set of all Diophantine equations which have at most finitely many integer solutions is not recursively enumerable, (4) analogous theorems hold for Diophantine equations D(x₁, …, x_p) = 0, where p ∈ N\{0} and for every i ∈ {1, …, p} the polynomial D(x₁, …, x_p) involves a monomial M with a non-zero coefficient such that x_i divides M, (5) the set of all Diophantine equations which have at most k variables (where k ≥ 9) and at most finitely many solutions in non-negative integers is not recursively enumerable.

Literature is inconsistent as to how coffee affects the features of the metabolic syndrome (MetS), and which bioactive compounds are responsible for its metabolic effects. We aimed to compare the in-vivo effects of unfiltered coffee with a selected mixture of its compounds on diet-induced MetS. 24 male Sprague-Dawley rats were fed a high-fat (35% W/W) food plus 20% W/W fructose in drinking water for 14 weeks, and were randomized into three groups: control, coffee, or nutraceuticals (5-O-caffeoylquinic acid, caffeic acid, and trigonelline). Coffee or nutraceuticals were provided in drinking water in a dosage equal to 4 cups/day in a human. Compared to the controls, only coffee supplementation decreased total food intake, weight gain, and estimated average plasma glucose. Surrogate measures of insulin resistance (fasting insulin, HOMA-IR, and oral glucose tolerance) were improved at endpoint in the coffee group. Circulating triglyceride levels were also reduced by coffee. Histopathological and quantitative measurements indicated lower grades of liver steatosis after long-term coffee consumption. In conclusion, a combination of phenolic acids and trigonelline was not as effective as coffee per se in improving the components of the MetS. This points to the role of other coffee chemicals and a potential synergism between compounds.

Beer is a fermented beverage with a history as old as human civilization and its productive process has been spread all around the world becoming unique in every country and iconic of entire populations. Ales and lagers are by far the most common beers; however, the combination of raw materials, manufacture techniques and aroma profiles are almost infinite, so it is not surprising to notice that there is a large amount of different beer styles, each of them with unique characteristics. Nowadays, diversification is becoming increasingly important in the brewing market and the brewers are continuously interested in improving and extending the already wide range of products, especially in craft brewery. One of the major components that can have a deep impact on the final product is yeast, since it is able to convert carbohydrates in wort, especially maltose and maltotriose, into ethanol, carbon dioxide and other minor aroma-active compounds. Saccharomyces cerevisiae (top‐fermenting yeasts used to produce ales) and Saccharomyces pastorianus (cryotolerant bottom‐fermenting hybrids between S. cerevisiae and Saccharomyces eubayanus responsible for the fermentation of lagers) are most used in breweries. However, an increasing number of different yeast starter cultures are commercially available, to improve the production efficiency also at relative low temperatures and to obtain desirable and diversified aroma profiles avoiding undesired compounds. Four main genetic engineering-free trends are becoming popular in craft brewing yeast development: 1) the research for novel reservoirs as source of new performant S. cerevisiae yeasts; 2) the creation of synthetic hybrids between S. cerevisiae and Saccharomyces non-cerevisiae in order to mimic lager yeasts by expanding their genetic background; 3) the exploitation of evolutionary engineering approaches; 4) the usage of non-Saccharomyces yeasts either in co-coculture or in sequential fermentation with S. cerevisiae. In the present work we summarized pro and contra of these approaches and provided an overview on the most recent advances on how brewing yeast genome evolved and domestication took place. Finally, we delineated how the correlations maps between genotypes and relevant brewing phenotypes can assist and further improve the search for novel craft beer starter yeasts.

Importance: The COVID-19 pandemic is currently accelerating. Patients with locally advanced non-small cell lung cancer (LA-NSCLC) may require treatment in locations where resources are limited and the prevalence of infection is high. Patients with LA-NSCLC frequently present with comorbidities that increase the risk for severe morbidity and mortality from COVID-19. These risks may be further increased by treatments for LA-NSCLC. Observation: We present expert thoracic oncology multidisciplinary (radiation oncology, medical oncology, surgical oncology) consensus of alternative strategies for the treatment of LA-NSCLC during a pandemic. The overarching goals of these approaches are to reduce the number of visits to a healthcare facility, reduce the risk of SARS-CoV-2 exposure, and attenuate the immunocompromising effects of lung cancer therapies. Patients with resectable disease can be treated with definitive non-operative management if surgical resources are limited or the risks of perioperative care are high. Non-operative options include chemotherapy, chemoimmunotherapy, and radiation therapy with sequential schedules. The order of treatments may be based on patient factors and clinical resources. Whenever radiation therapy is delivered without concurrent chemotherapy, hypofractionated schedules are appropriate. For patients who are confirmed to have COVID-19, usually cancer therapies may be withheld until symptoms have resolved with negative viral test results. Conclusions and Relevance: The risk of severe treatment-related morbidity and mortality is significantly elevated for patients undergoing treatment for LA-NSCLC during the COVID-19 pandemic. Adapting alternative treatment strategies as quickly as possible may save lives and should be implemented through communication with the multidisciplinary cancer team.

The present reality about the Nigerian economy calls for investment and development in the non-oil sector. This becomes necessary as a result of fall in the oil price in the global market. This paper examined the Bayesian Vector Autoregression (BVAR) modeling and forecasting of the dynamic interrelationship between Economic growth and revenue from the oil and non-oil sectors in Nigeria. To achieve this, annual data on Gross Domestic Product (GDP), revenue from oil and non-oil sectors were collected from Central Bank of Nigeria (CBN) bulletin, the sample from 1981 to 2008 was used for analysis, while sample from 2009 to 2014 was used for model validation. Six (6) versions of Sims-Zha BVAR models were compared for out-of-sample forecast, the result revealed the superiority of the BVAR6 model over the other BVAR models. Lastly, evidence from the decomposition forecast errors revealed that revenue of oil sector contributed 7.69% to GDP while revenue from non-oil sector contributed 0.12% to GDP in Nigeria. This paper therefore recommended that the present government should encourage investment that is geared toward development in the non-oil sector, of which it has the capacity to improve the Economic growth of the Nigerian economy.

Skin involvement is an overlooked aspect in the management of paediatric patients with type 1 diabetes. A comprehensive search of published literature using the PubMed database was carried out using the following key terms: “children”, “pediatric/paediatric patients”, “skin”, “skin disorders”, “type 1 diabetes”. Dermatological side effects are frequently observed among diabetic children and adolescents. Insulin-induced lipodystrophies and allergic contact dermatitis caused by insulin pumps or glycaemic sensors are the most common skin reactions in these patients. Furthermore, several diabetes-associated skin diseases such as necrobiosis lipoidica, granuloma annulare, vitiligo, and bullosis diabeticorum may already be present in paediatric age. Paediatric diabetes specialists should pay attention to their patients’ skin so as to recognize these disorders, identify the potential causes, and choose the most suitable treatment. Finally, the evaluation of skin concentrations of advanced glycation end-products using non-invasive diagnostic techniques may be used to assess the risk of chronic complications of diabetes as early as adolescence.

Cooperative non-orthogonal multi access communication is a promising paradigm for the future wireless networks because of its advantages in terms of energy efficiency, wider coverage and interference mitigating. In this paper, we study the secrecy performance of a downlink cooperative non-orthogonal multi access (NOMA) communication system under the presence of an eavesdropper node. Smart node selection based on feed forward neural networks (FFNN) is proposed in order to improve the physical layer security (PLS) of a cooperative NOMA network. The selected cooperative relay node is employed to enhance the channel capacity of the legal users, where the selected cooperative jammer is employed to degrade the capacity of the wiretapped channel. Simulations of the secrecy performance metric namely the secrecy capacity ($C_S$) are presented and compared with the conventional technique based on fuzzy logic node selection technique. Based on our simulations and discussions the proposed technique outperforms the existing technique in term the of secrecy performance.

Since its inception in the late 2000s, blockchain has emerged as a powerful tool for creating trust without intermediaries to incentivize global communities for working for a common goal, such as the improvement of its very ecosystem, its applications and community adoption. While first blockchains were mainly devised for confirming transactions of their innate cryptocurrencies like Bitcoin, smart-contract blockchains like Ethereum can interface with the real-world through so-called “oracles”, which feed trustful off-chain information. This paper introduces digital twins of physical objects and processes as computational oracles to effectively unleash the tremendous opportunity offered by blockchain to the realm of fundamental science, research and technology development (RTD). The crowdsourcing concept is illustrated with the example of centrifugal flow control in microfluidic “Lab-on-a-Disc” (LoaD) systems.

Polluted rivers are a primary problem in Changhua County, Taiwan, due to rapid and massive developments in agriculture and industry. In this study, samples consisted of water influent from the Yangzi-Cuo River, Ci-Tong Jiao, Changhua County. Ecology technology, a combination of gravel contact oxidation and surface flow constructed wetlands, was employed to enhance the water quality. Ecology technology is a useful and ordinary process that focuses on original treatment of pollution through chemical, physical, and biological procedures based on the mediums of soil, plant, water, and microorganisms from pure environments. Moreover, this study aimed to minimize the river pollution index (RPI) of the Yangzi-Cuo River by using combinations of gravel contact oxidation and surface flow constructed wetlands. The inflow volume of the water samples in situ was found to be 1534–2261 cubic meters per day (CMD). The pollution in the water sample mostly involved suspended solid (SS), ammoniacal nitrogen (NH₃–N), total phosphorus (TP), total nitrogen (TN), and biochemical oxygen demand (BOD), and the values of the above indexes were found to be 10.0–26.7 mg/L, 0.9–14.0 mg/L, 1.2–14.1 mg/L, 11.1–18.2 mg/L, and 0.5–3.6 mg/L, respectively. Efficiencies of pollution elimination in SS, NH₃–N, TP, TN, and BOD were found to be 24.2–93.1%, 58.3–86.2%, 5.2–85.0%, 59.4–77.2%, and 46.3–76.4%, correspondingly, after purification treatment via ecology technology. Thus, ecology technology is a valid means of purification treatment for polluted rivers.

Beta adrenoblockers is a large class of drugs mainly used to manage abnormal heart rhythms. Over the last couples of decades, the anticancer effects of these compounds has been extensively studied. There is much evidence about their activity in non-small cell lung, pancreatic, breast, colorectal, prostate and ovarian cancer. However, the mechanism of beta blockers anticancer activity is still not known, and more detailed studies are needed. The aim of our study was to evaluate the anticancer activity of beta adrenoblockers in non-small cell lung cancer cell lines A549 and H1299. In order to find the relationship with their selectivity to beta adrenoreceptors, in our study we used selective (atenolol, betaxolol, esmolol, metoprolol) and non-selective (pindolol, propranolol and timolol) beta blockers. The effect on cell viability was evaluated by MTT assay and the activity on cell ability to form colonies was tested by clonogenic assay. The type of cell death was evaluated by cell double staining with Hoechst 33342 and Propidium iodide. The most active adrenoblockers against both tested cancer cell lines were propranolol and betaxolol. They completely inhibited lung cancer cell colony formation at 90% of EC50 (half maximal effective concentration) value. Most tested compounds induced cell death through apoptosis and necrosis. In A549 cell lines apoptosis was mainly induced while in H1299 cell line compounds induced both apoptosis and necrosis. There was no correlation established between beta adrenoblocker anticancer activity and their selectivity to beta adrenoreceptors.

The growing awareness of the biological effects of artificial light on humans has stimulated ample research. It is now widely accepted that asynchrony between artificialand natural light-dark cycles can elicit severe detrimental health effects. New research has been devoted to lighting solutions that dynamically change their color to mimic spectral changes of daylight and to account for human needs. However, in some situations, the visual properties of light must be preserved: For example professional TV video editors and shift workers who must work under standardized lighting conditions to do color correction in post-production. We have investigated the possibility to tune circadian effects using white lights that are spectrally different but nonetheless have similar color coordinates thus appear as a similar white tone. Our simulation results indicate that it is possible to modulate circadian light effects by combining LEDs for neutral white (4000 K), a widely used white tone for indoor lighting in europe. The results also show that the solutions combining single-color LEDs do however not meet the quality criteria from the visual point of view because their color rendering ability decays to unacceptable low levels. Combining narrowband LEDs with a broadband white LED improves the color rendering quality and we show how far circadian light effects can be tuned according to common theoretical models. The aim is to reflect daylight situations with artificial lighting, thus having a high melatonin suppression in the morning and low melatonin suppression in the evening. As a consequence our aim is to show what maximum and minimum circadian effect is possible with the same set of LEDs.

A vast majority of the countries is under the economic and health crises due to the current epidemic of coronavirus disease 2019 (COVID-19). The present study analyzes the COVID-19 using time series, which is an essential gizmo for knowing the enlargement of infection and its changing behavior, especially the trending model. We have considered an autoregressive model with a non-linear time trend component that approximately converted into the linear trend using the spline function. The spline function split the COVID-19 series into different piecewise segments between respective knots and fitted the linear time trend. First, we obtain the number of knots with its locations in the COVID-19 series and then the estimation of the best-fitted model parameters are determined under Bayesian setup. The results advocate that the proposed model/methodology is a useful procedure to convert the non-linear time trend into a linear pattern of newly coronavirus case for various countries in the pandemic situation of COVID-19.

Lambertianic acid (LA) is a biologically active compound from the leaves of Pinus koraiensis. In the present study, apoptotic mechanisms of LA plus TNF-related apoptosis-inducing ligand (TRAIL) were elucidated in non-small cell lung cancer cells (NSCLCs). Cytotoxicity assay, flow cytometry, immunoprecipitation and Western blotting were performed. Here, combined treatment of LA and TRAIL increased cytotoxicity, sub-G1 population and cleaved poly (ADP-ribose) polymerase (PARP) and caspase3/8/9 in A549 and H1299 cells compared to LA or TRAIL alone. Furthermore, combined treatment of LA and TRAIL significantly decreased anti-apoptotic proteins such as B-cell lymphoma 2 (Bcl-2), Fas-like inhibitor protein (FLIP) and X-linked inhibitor of apoptosis protein (XIAP) and enhanced the activation of pro-apoptotic proteins Bid compared to LA or TRAIL alone. In addition, combined treatment of LA and TRAIL upregulated the expression of Death receptor 4 (DR4) and downregulated phosphorylation of nuclear factor kappa-light-chain-enhancer of activated B cells (p-NF-B), inhibitory protein of kB family (p-IB) and FLIP in A549 and H1299 cells along with disrupted binding of XIAP with caspase3 or NF-B. Overall, these findings suggest that lambertianic acid enhances TRAIL-induced apoptosis via inhibition of XIAP/NF-B in TRAIL resistant NSCLCs.

True contact between solids with randomly rough surfaces tends to occur at a large number of microscopic contact patches. So far, two scaling regimes have been identified for the number density n(A) of contact-patch sizes A in elastic, non-adhesive, self-affine contacts. At small A, n(A) is approximately constant, while n(A) decreases as a power law at large A. Using Green’s function molecular dynamics, we identify a characteristic (maximum) contact area Ac above which a superexponential decay of n(A) becomes apparent if the contact pressure is below the pressure p_cp at which contact percolates. We also find that A_c increases with load relatively slowly far away from contact percolation. Results for A_c can be estimated from the stress autocorrelation function G_σσ (r) with the following argument: the radius of characteristic contact patches, r_c, cannot be so large that G_σσ (r_c) is much less than p_c². Our findings provide a possible mechanism for the breakdown of the proportionality between friction and wear with load at large contact pressures and/or for surfaces with a large roll-off wavelength.

Observed sea surface Ka-band normalized radar backscatter cross section (NRCS) and Doppler velocity (DV) exhibit energy at low frequencies (LF) below the surface wave range. It is shown that non-linearity in NRCS-wave slope Modulation Transfer Function (MTF) and inherent NRCS averaging within the footprint account for the NRCS and DV LF variance with the exception of VV NRCS for which almost half of the LF variance is attributable to wind fluctuations. Although the distribution of radar DV is quasi-Gaussian suggesting virtually little impact of non-linearity, the LF DV variations arise due to footprint averaging of correlated local DV and non-linear NRCS. Numerical simulations demonstrate that MTF non-linearity weakly affects traditional linear MTF estimate (less than 10% for |MTF|< 20). Thus the linear MTF is a good approximation to evaluate the DV averaged over large footprints typical of satellite observations.

Common genetic variants of the fat mass and obesity associated (FTO) gene are strongly associated with obesity and type 2 diabetes. FTO is ubiquitously expressed, but appears to have tissue-specific roles. Earlier studies have focused on the role of hypothlamic FTO in the regulation of metabolism. However, it appears that FTO plays a role in the regulation of metabolism in a tissue-specific manner. Recent studies suggest that expression of hepatic FTO is regulated by metabolic signals such as nutrients and hormones and altered FTO levels in liver affects glucose and lipid metabolism. This review outlines recent findings on hepatic FTO in the regulation of metabolism, with particular focus on hepatic glucose and lipid metabolism. It is proposed that abnormal activity of hepatic signaling pathways involving FTO links metabolic impairments such as obesity, type 2 diabetes and nonalcoholic fatty liver disease (NAFLD). Therefore, a better understanding of these pathways may lead to therapeutic approaches to treat these metabolic diseases by targeting hepatic FTO. The overall goal of this review is to place FTO within the context of hepatic regulation of metabolism.

Activating mutations in the Epidermal Growth Factor Receptor gene occur as early cancer-driving clonal events in a subset of patients with non-small cell lung cancer (NSCLC) and result in increased sensitivity to EGFR-tyrosine-kinase-inhibitors (EGFR-TKIs). Despite very frequent and often prolonged clinical response to EGFR-TKIs, virtually all advanced EGFR-mutated (EGFRM+) NSCLCs inevitably acquire resistance mechanisms and progress at some point during treatment. Additionally, 20-30% of patients do not respond or respond for a very short time (< 3 months) because of intrinsic resistance. While several mechanisms of acquired EGFR-TKI-resistance have been determined analyzing tumor specimens obtained at disease progression, the factors causing intrinsic TKI-resistance are less understood. However, recent comprehensive molecular-pathological profiling of advanced EGFRM+ NSCLC at baseline has illustrated the co-existence of multiple genetic, phenotypic, and functional mechanisms that may contribute to tumor progression and cause intrinsic TKI-resistance. Several of these mechanisms have been further corroborated by preclinical experiments. Intrinsic resistance can be caused by mechanisms inherent EGFR or by EGFR-independent processes, including genetic, phenotypic or functional tumor changes. This comprehensive review describes the identified mechanisms connected with intrinsic EGFR-TKI-resistance and differences and similarities with acquired resistance and among clinically implemented EGFR-TKIs of different generations. Additionally, the review highlights the need for extensive pre-treatment molecular profiling of advanced NSCLC for identifying inherently TKI-resistant cases and designing potential combinatorial targeted strategies to treat them.

We generalize the idea of quantum clock time to quantum spacetime reference frame via physical realization of a reference system by quantum rulers and clocks. Omitting the internal degrees of freedom (such as spins) of the physical rulers and clocks, only considering their metric properties, the spacetime reference frame is described by a bosonic non-linear sigma model (NLSM). We study the quantum behavior of the system under approximations, and obtain (1) a cosmological constant valued (2/π)ρ_c0 (ρ_c0 the critical density at near current epoch) which is very close to the observations; (2) an effective Einstein-Hilbert term; (3) the ratio of variance to mean-squared of spacetime interval tends to a universal constant 2/π in the infrared region. This effect is testable by observing a linear dependence between the inherent quantum variance and mean-squared of the redshifts from cosmic distant spectral lines. The proportionality is expected to be the observed percentage of the dark energy. The equivalence principle is also generalized to the quantum level.

The commitment of the EU to Corporate Social Responsibility (CSR) is projected in the EU law about annual reporting by businesses. Since EU member states further develop this framework by their own domestic laws, annual reporting with CSR information is not unified and just partially mandatory in the EU. Do all European businesses report CSR information and what public declaration to society do they provide with it? The main dual purpose of this paper is identifying the parameters of this annual reporting duty and studying the CSR information provided by the ten largest Czech companies in their annual statements for 2013-2017. Based on legislative research and the teleological interpretation, the current EU legislative framework with Czech particularities is presented and, via a case study exploring 50 annual reports, the data about the type, extent and depth of the CSR is dynamically and comparatively assessed. It appears that, at a minimum, large Czech businesses satisfy their legal duty and e-report on CSR in a similar extent, but in dramatically different quality. Employee matters and adherence to international standards are used as a public declaration to society more than the data on environmental protection, while social matters and R&D are played down.

Objective: To evaluate the existing meta-analytic evidence of associations between exposure to ultra-processed foods, as defined by the Nova food classification system, and adverse health outcomes. Design: Systematic umbrella review of existing meta-analyses. Data Sources: MEDLINE, PsycINFO, Embase, and the Cochrane Database of Systematic Reviews, as well as manually searching reference lists from 2009 to June 2023. Inclusion Criteria: Systematic reviews and meta-analyses of cohort, case-control, and/or cross-sectional study designs that evaluated the associations between exposure to ultra-processed foods and adverse health outcomes in humans across the lifespan. Results: The search identified 45 unique pooled analyses, including 13 dose-response and 32 non-dose-response associations (n=9,888,373). Overall, direct associations were found between exposure to ultra-processed foods and 32 (71%) health outcome domains spanning cardiometabolic, gastrointestinal, and respiratory conditions, cancer, mental health, and mortality. Based on a pre-specified evidence classification criteria, convincing evidence (Class I) supported direct associations between greater ultra-processed food exposure and higher risks of incident cardiovascular disease-related mortality (RR: 1.50; 95%CIs: 1.37 to 1.63), type two diabetes (dose-response RR: 1.12; 95%CIs: 1.11 to 1.13), and depressive outcomes (HR: 1.21; 95%CIs: 1.16 to 1.28), as well as higher risks of prevalent anxiety outcomes (OR: 1.48; 95%CIs: 1.37 to 1.59) and combined common mental disorder outcomes (OR: 1.53; 95%CIs: 1.43 to 1.63). Highly suggestive (Class II) evidence indicated that greater exposure to ultra-processed foods was directly associated with higher risks of incident all-cause mortality (RR: 1.21; 95%CIs: 1.15 to 1.27), heart disease-related mortality (dose-response HR: 1.66; 95%CIs: 1.51 to 1.84), and type two diabetes (OR: 1.40; 95%CIs: 1.23 to 1.59), together with higher risks of prevalent obesity (OR: 1.55; 95%CIs: 1.36 to 1.77), adverse sleep-related outcomes (OR: 1.41; 95%CIs: 1.24 to 1.60), and wheezing (RR: 1.40; 95%CIs: 1.27 to 1.55). Out of the remaining 34 pooled analyses, 21 were graded as suggestive or weak strength (Class III-IV) and 13 were graded as no evidence (Class V). Using the GRADE framework, 22 pooled analyses were rated as "Low" quality, with 19 rated as "Very Low” and four rated as "Moderate" quality. Conclusions: Higher exposure to ultra-processed food was associated with a greater risk of adverse health outcomes, especially cardiometabolic, common mental disorder, and mortality outcomes. These findings provide a rationale to evaluate the effectiveness of using population-based measures to target and reduce dietary exposure to ultra-processed foods for improved human health. Systematic Review Registration: PROSPERO CRD42023412732.

We construct a family of two-step optimal fourth order iterative methods for finding single root of non-linear equations. We generalize these methods to simultaneous iterative methods for determining all the distinct as well as multiple roots of single variable non-linear equations. Convergence analysis is present for both cases to show that the order of convergence is four in case of single root finding method and is twelve for simultaneous determination of all roots of non-linear equation. The computational cost, Basin of attraction, efficiency, log of residual and numerical test examples shows, the newly constructed methods are more efficient as compared to the existing methods in literature.

The function of the endoplasmic reticulum (ER) can be impaired by the alternation of the extra- and intracellular environment such as disruption of calcium homeostasis, expression of mutated proteins and oxidative stress. In response to disruptions to ER homeostasis, eukaryotic cells activate canonical branches of signal transduction cascades, collectively termed the unfolded protein response (UPR). The UPR attempts to recover the protein folding capacity and avoid irreversible cellular damage. Additionally, the UPR has been shown to play unique physiological roles in the regulation of diverse cellular events, including cell differentiation and development and lipid biosynthesis. Recent studies have indicated that these important cellular events are also regulated by contact and communication among organelles. These reports suggest strong involvement among the UPR, organelle communication and regulation of cellular homeostasis. However, the precise mechanisms for the formation of contact sites and the regulation of its dynamics by UPR remain unresolved. In this review, we summarized the current understanding of how the UPR regulates morphological changes to the ER and the formation of contact sites between the ER and other organelles. We also review how UPR-dependent connections between the ER and other organelles affect cellular and physiological functions.

Abstract: This work is part of the interest of solving the problems of water contamination with last generation pollutants, for which a novel and in an aqueous medium FeBTC material incorporated with magnetite nanoparticles was proposed. That material was synthesized by in situ solvothermal method, the Fe3O4 nanoparticles were added during the Fe-BTC MOF synthesis and used in the drug’s adsorption. The materials were characterized by XRD, FTIR and Raman spectroscopy, and N2-physisorption at 77 K. Fe3O4-FeBTC material showed a maximum adsorption capacity of 357.1 mg g−1 for diclofenac sodium, 70.9 mg g−1 for naproxen sodium, and 122.9 mg g−1 for Ibuprofen. A pseudo-second-order kinetic model can describe the adsorption process, and the thermodynamic study revealed that the adsorption of the three drugs was a feasible, spontaneous, and exothermic process. The incorporation of magnetite nanoparticles in the FeBTC considerably increased the adsorption capacity of pristine FeBTC. Also, hybridization of the FeBTC with magnetite nanoparticles reinforced the most vulnerable part of the MOF, increasing its thermal and aqueous media stability. The electrostatic interaction, H-bonding, and interactions in the open-metal sites played a vital role in drug adsorption. The competition of sites in the multicomponent mixture's adsorption showed selective adsorption at diclofenac sodium and naproxen sodium.

The epidemiological situation generated by COVID-19 has highlighted the importance of applying non-pharmacological measures. Among these, mass screening of the asymptomatic general population has been established as a priority strategy by carrying out diagnostic tests to limit the spread of the virus. In this article, we aim to evaluate the economic impact of mass COVID-19 screenings of an asymptomatic population through a Cost-Benefit Analysis based on the estimated total costs of mass screening versus health gains and associated health costs avoided. Excluding the value of monetized health, the Benefit-Cost ratio was estimated at approximately 0.45. However, if monetized health is included in the calculation, the ratio is close to 1.20. The monetization of health is the critical element that tips the scales in favour of the desirability of screening. Screenings with the highest return are those that maximize the percentage of positives detected.

In recent years, numerous topologies of single phase and three phase Field Excited Flux-Switching Machine (FEFSM) have been developed for several applications. Comparative study of three types of single-phase low-priced Field Excited Flux-Switching Machine (FEFSM) is presented in this paper. Both the conventional 8S/4P sub-part rotor design and 6S/3P salient rotor design have an overlapped winding arrangements between armature coil and field excitation coil that depicts high copper losses as well as results in increased size of motor. Additionally, FEFSM with salient structure of the rotor have high flux strength in the stator-core that has much impact on high iron losses. Copper consumption and iron loss being a crucial proportion in total machine losses. Therefore a novel topology of single phase modular rotor field excited FSM with 8S/6P configuration is proposed, which enable non-overlap arrangement between armature coil and FEC winding that facilitates devaluation in the copper losses. The proposed modular rotor design acquires reduced iron losses as well as reduced active rotor mass comparatively to conventional rotor design. It is very persuasive to analyze the best range of speed for these rotors to avoid cracks and deformation, the maximum tensile strength (can be measured with principal stress in research) of the rotor analysis is conducted using JMAG. A deterministic optimization technique is used to enhance the performance of 8S/6P modular rotor design. The electromagnetic performance of conventional sub-part rotor design, F1-A3-3P design and proposed novel-modular rotor design are analyzed by 3D-Finite Element Analysis (3D-FEA), includes flux linkage, flux distribution, flux strength, back-EMF, cogging torque, torque characteristics, iron losses and efficiency.

Background: To evaluate the effect of systemic erythropoietin, as well as oral steroids, in the management of recent onset non-arteritic anterior ischemic optic neuropathy (NAION). Method: Ninety-nine eyes of 99 patients diagnosed with NAION within 5 days of onset were included in this single masked randomized clinical trial. Thirty-four patients were randomized into group 1 (systemic erythropoietin), group 2 (oral steroids), and group 3 (control). Group A received 10,000 units of erythropoietin twice a day for three days. Group B received oral prednisone 75 mg daily for two weeks followed by a tapering dose (70 mg for 5 days, 60 mg for 5 days, and 5 mg reductions thereafter every 5 days). Functional and structural outcomes were analyzed at 3 and 6 months following treatment. Best corrected visual acuity (BCVA) was the main outcome measure, and mean deviation (MD) of visual field (VF) test and peripapillary retinal nerve fiber layer thickness (PRNFLT) were secondary outcome measures. Results:The mean BCVA (±SD) at the time of presentation was 1 ± 0.56, 1.01 ± 0.6, and 0.94 ± 0.47 logMAR in groups A, B, and C, respectively (P = 0.140); corresponding values were 0.72 ± 0.45, 0.83 ± 0.46, and 0.78 ± 0.4 logMAR (P = 0.417), and at 6-month follow-up, they were 0.70 ± 0.44, 0.73 ± 0.35, and 0.75 ± 0.39 logMAR, respectively (P = 0.597). Fifty-five percent of patients in group A vesus 34.3% in group B, and 31.2% in group C had an improvement of at least 3 lines in the BCVA values at the 6th-month follow-up visit. (P= 0.04) The mean deviation (MD) at the time of presentation was 19.67 ± 6.2, 20.83 ± 4.83, and 18.94 ± 6.92 decibels (db), respectively (P= 0.483).The corresponding values at month 3 were 18.22 ± 7.5, 19.82 ± 7.15, and 17.65 ± 7.22 db, (P = 0.848); and at month 6 they were 16.56 ± 7.08, 18.15 ± 6.57, and 15.9 ± 5.97 db, respectively. (P = 0.699) PRNFLT at presentation was 189 ± 58, 193 ± 64, and 199 ± 62 micrometers, respectively (P = 0.779), which decreased to 110 ± 45, 127 ± 37, and 119 ± 37 at month 3 (P = 0.423). The corresponding values for month 6 were 88 ± 12, 74 ± 25, and 71 ± 18, respectively (P = 0.041). Conclusion: The findings of our study indicate the beneficial effects of systemic erythropoietin in preserving the function and structure of the optic nerve in recent onset NAION.

The calculation of power flow in power systems with the presence of harmonics has been properly studied in the scientific literature. However, power flow calculation considering interharmonic components is still an open question. Traditional methods based on the IEEE1459 standard have proven to be valid and accurate only for linear and sinusoidal systems, but have been criticized for non-linear and non-sinusoidal systems because they are not able to explain correctly the current and voltage interactions beyond the active power. This paper proposes the use of a novel mathematical framework called geometric algebra (GA) to study the power flow considering the interaction of current and voltage harmonics and interharmonics. The use of GA enables the precise determination of the direction and magnitude of the total and single active power flow for each component, as well as other power elements related to the non-active power due to cross interaction. Moreover, this paper makes a novel contribution to the definition of interharmonics in geometric algebra space that has not been done before. To test the validity of the method, both linear and non-linear circuits are proposed and solved by applying voltages and currents with harmonic and interharmonic components. The results obtained show that power flow can be analyzed under the prism of the principle of energy conservation (PoCoE) in a way that allows a better understanding of the power spectrum due to the interaction of harmonics and interharmonics of voltage and current.

In the NCBI database, as on June 6, 2020, total number of available complete genome sequences of SARS-CoV2 across the world is 3617. The envelope protein of SARS-CoV2 possesses several non-synonymous mutations over the transmembrane domain and (C)-terminus in 0.414\% of these 3617 genomes. The C-terminus motif DLLV has been changed to DFLV and YLLV in the proteins QJR88103 (Australia: Victoria) and QKI36831 (China: Guangzhou) respectively, which might affect the binding of this motif with the host protein PALS1.

Subsurface drainage systems remove excess water from the soil profile thereby improving crop yields in poorly drained farmland. Knowledge of the position of the buried drain lines is important: 1) to improve understanding of leaching and offsite release of nutrients and pesticides, and 2) for the installation of a new set of drain lines between the old ones for enhanced soil water removal efficiency. Traditional methods of drainage mapping involve the use of tile probes and trenching equipment. While these can be effective, they are also time-consuming, labor-intensive, and invasive, thereby entailing an inherent risk of damaging the drainpipes. Non-invasive geophysical soil sensors provide a potential alternative solution. Previous research has focused on the use of time-domain ground penetrating radar (GPR), with variable success depending on local soil and hydrological conditions and the central frequency of the specific equipment employed. The objectives of this study were 1) to test the use of a stepped-frequency continuous wave (SFCW) 3D-GPR (GeoScope Mk IV 3D-Radar with DXG1820 antenna array) for subsurface drainage mapping, and 2) to evaluate the performance of a 3D-GPR with the use of a single-frequency multi-receiver electromagnetic induction (EMI) sensor (DUALEM) in-combination. The 3D-GPR system offers more flexibility for application to different (sub)surface conditions due to the coverage of wide frequency bandwidth. The EMI sensor simultaneously provides information about the apparent electrical conductivity (EC_a) for different soil volumes, corresponding to different depths. This sensor combination was evaluated on twelve different study sites with various soil types with textures ranging from sand to clay till. While the 3-D GPR showed a high success rate in finding the drainpipes at five sites (sandy, sandy loam, loamy sand, and organic topsoils), the results at the other seven sites were less successful due to limited penetration depth (PD) of the 3D-GPR signal. The results suggest that the electrical conductivity estimates produced by the inversion of EC_a data measured by the DUALEM sensor could be a useful proxy to explain the success achieved by the 3D-GPR in finding the drain lines. The high attenuation of electromagnetic waves in highly conductive media limiting the PD of the 3D-GPR can explain the findings obtained in this research.

Contemporary literature dealing with the governance and exploitation of common-pool natural resources was initiated by Elinor Ostrom in 1990, and has been growing fast ever since. On the contrary, within the same research stream, the study of the presence and economic role of common resources in entrepreneurial organizations is, to date, under-researched. This work endeavors to fill some gaps in this research perspective by: (i) spelling out a new-institutionalist framework for the analysis of the accumulation and governance of common capital resources within organizational boundaries; (ii) considering co-operative enterprises as the organizational form that, on the basis of historical record, and of behavioral and institutional characteristics, demonstrated to be most compatible with a substantial role for common and non-divided asset-ownership and with its governance thereof; (iii) evidencing and explaining the strong connection between cooperative longevity and the presence of non-divided asset ownership. The economic forces influencing the optimal level of self-financed common capital resources in co-operatives are enquired. Conclusions to the paper evidence the main reasons why the new approach can better explain than preceding ones the economic sustainability and longevity of cooperative enterprises.