The present era of the Internet of Things (IoT) having intelligent functionalities in solving problems pertaining to realtime mission-critical systems has brought an immense revolution in diverse fields including healthcare and navigation systems. However, to the best of our knowledge, the potential of IoT has not been fully exploited yet in the field of the energy sector. We argue that there is an immense need to shift the traditional mission-critical electric power system architecture to IoT-based fully orchestrated architecture in order to increase efficiency, as billions of investment is reserved for the energy sector globally. Since network orchestration deals with auomating the interaction between multiple components involved to execute a particular service, therefore, scheduling the relevant processes within strict deadlines becomes the core pillar of the architecture. The mission-critical systems with urgent task execution often suffer from issues of missing task deadlines. In this study, we present a novel IoT task orchestration architecture for efficient energy management of a nanogrid system that focuses on minimizing the use of nonrenewable energy resources and maximizing the use of renewable energy resources. Moreover, major components of IoT task orchestration such as task mapping and task scheduling are also enhanced using NLP and PSO optimization modules. The proposed task scheduling algorithm incorporates the optimized surplus time, and efficiently executes the energy management-related tasks contemplating to their types. The study utilizes sensors to obtain data from physical IoT devices, including photovoltaic (PV), Energy Storage System (ESS), and diesel generator (DG). The performance of the proposed model is evaluated using data set of nanogrid houses. The outcomes revealed that IoT-task orchestration has played a pivotal role in efficient energy management for nanogrid mission-critical system. Furthermore, the comparison with state-of-the-art scheduling algorithms showed that the task starvation rate is reduced to 16% and 12% when compared with RR and FEF algorithms, respectively.

Mediterranean coastal lagoons and their peripheral areas often provide a collection of habitats for many species, and they often face significant threats from anthropogenic activities. Diverse human activities in such areas directly affect the spatio-temporal dynamic of surface water and its ecological characteristics. Monitoring the surface water dynamic, and understanding the impact of human activities are of great significance for coastal lagoon conservation. The Regional Natural Park of Narbonne includes a typical Mediterranean lagoon complex where surface water dynamic and its potential link with local diverse human activities has not yet been studied. In this context, based on all the available Landsat images covering the study area during 2002-2016, this study identified the water and non-water classes for each satellite observation by comparing three widely used water indices (i.e., NDVI, NDWI and MNDWI) and using the Otsu method. The yearly water frequency index was then computed to present the spatio-temporal dynamic of surface water for each year, and three water dynamic scenarios were also identified for each year: permanent water (PW), non-permanent water (NPW) and non-water (NW). The spatial and inter-annual variation in the patterns of the three water scenarios were characterized by computing the landscape metrics at scenario-level quantifying area/edge, shape, aggregation and fragmentation. Finally, the quantitative link between different land use and land cover (LULC) types derived from the LULC maps of 2003, 2012 and 2015 and the surface water dynamic scenarios was established in each of the 300 m x 300 m grid cells covering the study area to determine the potential impact of human activities on the surface water dynamic. In terms of the inter-annual variation during 2002-2016, PW presented an overall stability, and NPW occupied only a small part of the water surface in each year and presented an inter-annual fluctuation. NPW had a smaller patch size, with lower connectivity degree and higher fragmentation degree. In terms of spatial variation during 2002-2016, NPW often occurred around PW, and its configurational features varied from place to place. Moreover, PW mostly corresponded to natural lagoon, and salt marsh (as a part of lagoons), and NPW had a strong link with arable land (agricultural irrigation) and salt marsh (salt production), sand beach/dune, coastal wetlands and lagoon for the LULC maps of 2003, 2012 and 2015. However, more in-depth analysis is required for understanding the impact of sand beach/dune, coastal wetlands and lagoon on surface water dynamics. This study covers the long-term variations of surface water patterns in a Mediterranean lagoon complex having intense and diverse human activities, and the potential link between LULC types and the water dynamic scenarios was investigated on different dates. The results of the study should be useful for environmental management and protection of coastal lagoons.

An open source computational fluid dynamics (CFD) solver has been incorporated into the WindNinja modeling framework widely used by wildland fire managers as well as researchers and practitioners in other fields, such as wind energy, wind erosion, and search and rescue. Here we describe incorporation of the CFD solver and evaluate its performance compared to the conservation of mass (COM) solver in WindNinja and previously published large-eddy simulations (LES) for three field campaigns conducted over isolated terrain obstacles of varying terrain complexity: Askervein Hill, Bolund Hill, and Big Southern Butte. We also compare the effects of two important model settings in the CFD solver and provide guidance on model sensitivity to these settings. Additionally, we investigate the computational mesh and difficulties regarding terrain representation. Two important findings from this work are: (1) the choice of discretization scheme for advection has a significantly larger effect on the simulated winds than the choice of turbulence model and (2) CFD solver predictions are significantly better than the COM solver predictions at windward and lee side observation locations, but no difference was found in predicted speed-up at ridgetop locations between the two solvers.

Research subjects of this study are four representative locations in the industrial complex, in the city of Banja Luka, Republic of Srpska, Bosnia and Herzegovina. 16 polycyclic aromatic hydrocarbons (PAHs) (∑16PAHs), humus and pH were determined. The main objective of the paper is to determine the concentration levels, to assess the probable sources of PAHs contamination in soil and groundwater and to determine the ecological risk. The ∑16PAHs in soil (at depths of 30 cm, 100 cm, 200 cm, 300 cm and 400 cm) ranged from 0.99 to 2.24 mg/kg, from 0.34 to 0.46, from 0.24 to 0.32, from 0.13 to 0.27 and from 0.13 to 0.47, with mean values of 1.70 mg/kg, 0.40 mg/kg, 0.28 mg/kg, 0.20 mg/kg and 0.26 mg/kg, respectively. The ∑16PAHs in groundwater ranged from 0.23 to 4.50 mg/m³, with a mean value of 1.42 mg/m³. Surface soil and groundwater are heavily contaminated. All values of ∑PAHs in soil layers were lower in the depths of the soil. Factor analysis indicates three sources of contamination, i.e. principal component (PC) PC1 (pyrogenic), PC2 (petrogenic) and PC3 (biomass), with 52.39%, 26.14% and 8.46% of the total variance, respectively. ∑PAH and PAHs indicate high ecological risk for most PAHs, which decreases with soil depth.

A good recommender system can infer customers’ preferences based on their historical purchase records, and recommend products that the customers may be interested in, saving them a lot of time and energy. For enterprises, it is difficult to recommend accurately to each customer, and the bad recommendation may be counterproductive. Customer loyalty is an indicator that measures the preference relationship between customers and products in the field of marketing. A hypothesis is proposed in this study: if companies can divide customers into different groups based on customer loyalty, the recommendation effect on certain groups is better than that on overall customers. In this study, customer loyalty is measured by four features of the RFML model. All customers are viewed as points on a four-dimensional space, which are clustered by the k-means model. Two recommendation algorithms based on complex networks are tested: recommendation algorithm based on bipartite graph and PersonalRank (BGPR), and recommendation algorithm based on a single vertex set network and DeepWalk (SVDW). The experimental results show that customer loyalty has improved the effectiveness of the two algorithms over 14%, and the recommendation effect is the best on customer groups with a loyalty level of 4 (the highest level is 5). The recommendation algorithms with customer loyalty are better than using them alone.

The definition of a Smart-complex of educational discipline and its technology is given. Attention is focused on the form of the Smart-complex and constructive elements: the creative educational environment, the author's environment, the non-verbal environment, the encyclopedia, the creative / self-realization environment, the monitoring / self-evaluation environment.A feature of the Smart-complex of the academic discipline is the integration into it of the structural equalization block. Constructive alignment (alignment) is based on the design of the student's own learning participation in educational projects. Alignment refers to creating an appropriate learning environment and involves selecting the most appropriate training activities and evaluating each learning outcome. If the result of the training is to develop analytical skills, then for the assessment it is necessary to build questions and scenarios for their development.Two main components of the structural alignment are considered: 1) the first component is based on cognitive psychology and constructivist theory, recognizes the importance of linking new material with the concepts and experiences of students and extrapolation to possible future scenarios in the process of mission activity - they comprehend what they are doing during training; 2) the second component is based on the declaration by the teacher of the correspondence between the planned educational activities and the results of the training of students. This makes planning of educational activities and development of self-assessment criteria for organizing feedback. It is necessary to take into account the impact of Smart-complexes of educational disciplines on three think-tank training networks: 1) effective networks (why learn) - several ways of presenting to give students different ways of obtaining information and knowledge; 2) recognition networks (learning outcomes) - several ways of expressing them to provide them with an alternative for demonstrating what they know; 3) strategic exercises (how to learn) - several ways to increase the motivation for learning to attract their attention to both their own learning project and its technical and historical decision. Smart-complexes of educational disciplines should be: 1) scientific; 2) with user-friendly interface; 3) have a connection with LMS; 4) structured; 5) with visual material; 6) working in Off-line mode; 7) used on various devices in an educational institution, as well as at home.

Being able to forecast events is of great importance in many fields, from brain behavior to earthquakes or stock markets. Because each dynamical system has intrinsic features, different statistical tools have to be used for each system. Here we study the time series of the output intensity of a fiber laser with an ordinal patterns analysis, and we look for temporal correlations in order to statistically forecast the most intense events. We set two thresholds, a low one and a high one, to distinguish between low intensity versus high intensity events. We find that when the time series is performing events below the low threshold it shows some preferred temporal patterns before performing events above a high threshold.

As a complex system, our body acts as a whole system connected to the environmental incitements. It is ordered, coherent, and tries to maintain the least possible entropy, saving the greatest amount of energy. In order to explain the dynamics of the systemic regulative network, a theoretical and speculative model is proposed, with a comprehensive approach that allows seeing the entire regulative system as a continuous unicuum. This paper covers two themes: 1) the connections between the quantum level and the classical one, through some principles of the QFT and through the Coherence Domains. The system is modeled as a field described by the wave function, with synchronous and consistent events, driven in a global computing by the quantum potential Q. The quantum potential implies the non-locality, and it needs only ultra-weak waves to occur, so it may explain how the rapid and global activation of the organism in response to perturbation/punctiform information works. The initial hypothesis is that some consistent quantum phenomena are amplified through the systemic regulative network until they become macroscopic observable. This is possible because of Coherence Domains. 2) The reactions of the different systemic networks to perturbations/punctiform information, with the attempt to model and measure information in biology, going beyond the Shannon and Turing theories. Hopfield Networks and an informational point of view are used to address the crucial informational and organizational role of proteins and nucleic acids.

Accurate repair of DNA is critical for genome stability and cancer prevention. DNA double-strand breaks are one of the most toxic lesions and can be repaired using homologous recombination (HR). HR is a high-fidelity DNA repair pathway that uses a homologous template for repair. One central HR step is RAD51 nucleoprotein filament formation on the single-stranded DNA ends, a step required for the homology search and strand invasion steps of HR. RAD51 filament formation is tightly controlled by many positive and negative regulators, collectively termed the RAD51 mediators. The RAD51 mediators function to nucleate, elongate, stabilize, and disassemble RAD51 during repair. In model organisms, RAD51 paralogs are RAD51 mediator proteins that structurally resemble RAD51 and promote its HR activity. New functions for the RAD51 paralogs during replication and in RAD51 filament flexibility have recently been uncovered. Mutations in the human RAD51 paralogs (RAD51B, RAD51C, RAD51D, XRCC2, XRCC3, and SWSAP1) are found in a subset of breast and ovarian cancers. Despite their discovery three decades ago, few advances have been made in understanding the function of the human RAD51 paralogs. Here we discuss the current perspective on the RAD51 paralogs in vivo and in vitro function and their relationship with cancer in vertebrate models.

Washing hands, social distancing and staying at home are the preventive measures set in place to contain the spread of the COVID-19, a disease caused by SARS-CoV-2. These measures, although straightforward to follow, highlight the tip of an imbalanced socio-economic and socio-technological iceberg. Here, a System Dynamic (SD) model of COVID-19 preventive measures and their correlation with the 17 Sustainable Development Goals (SDGs) is presented. The result demonstrates a better informed view of the COVID-19 vulnerability landscape. This novel qualitative approach refreshes debates on the future of SDGS amid the crisis and provides a powerful mental representation for decision makers to find leverage points that aid in preventing long-term disruptive impacts of this health crisis on people, planet and economy. There is a need for further tailor-made and real-time qualitative and quantitative scientific research to calibrate the criticality of meeting the SDGS targets in different countries according to ongoing lessons learned from this health crisis.

Many complex networks have a connectivity that might be only partially detected or that tends to grow over time, hence the prediction of non-observed links is a fundamental problem in network science. The aim of topological link prediction is to forecast these non-observed links by only exploiting features intrinsic to the network topology. It has a wide range of real applications, like suggesting friendships in social networks or predicting interactions in biological networks.The Cannistraci-Hebb theory is a recent achievement in network science that includes a theoretical framework to understand local-based link prediction on paths of length n. In this study we introduce two innovations: theory of modelling (science) and theory of realization (engineering). For the theory of modelling we first recall a definition of network automata as a general framework for modelling the growth of connectivity in complex networks. We then show that several deterministic models previously developed fall within this framework and we introduce novel network automata following the Cannistraci-Hebb rule. For the theory of realization, we present how to build adaptive network automata for link prediction, which incorporate multiple deterministic models of self-organization and automatically choose the rule that better explains the patterns of connectivity in the network under investigation. We compare Cannistraci-Hebb adaptive (CHA) network automaton against state-of-the-art link prediction methods such as structural perturbation method (SPM), stochastic block models (SBM) and artificial intelligence algorithms for graph embedding. CHA displays an overall higher link prediction performance across different evaluation frameworks on 1386 networks. Finally, we highlight that CHA offers the key advantage to explicitly explain the mechanistic rule of self-organization which leads to the link prediction performance, whereas SPM and graph embedding not. In comparison to CHA, SBM unfortunately shows irrelevant and unsatisfactory performance demonstrating that SBM modelling is not adequate for link prediction in real networks.

Specialized, reductionist, and linear approaches are applied in clinical research; they are based on linear logic and used towards therapeutic molecule-based targets. However, those approaches do not consider a systemic vision that describes the remote cause of the pathogenic activation. We propose new theoretical and practical methods for the next drug generation development. Self-organization, network structure, hierarchical organization, non-linearity, feedback circuits, reactions to information, and the view of drugs as information clarify the existing pharmacological methods. We suggest a perspective and hierarchical vision of the human organism based on six levels (mechanic and structural; metabolic; bodily dynamic; emotional, cognitive, spiritual). The therapy should restore the self-organization of every level using the “intelligent” modulation of the network responses. Multi-targeted drugs should act on the remote cause of the pathogenic cascade and be administered based on personal variability and networks. This approach may help the development of individualized, precise, and integrated medicine.

We explore the possibility to form a physical theory in $C^4$. We argue that the expansion of our usual 4-d real space-time to a 4-d complex space-time, can serve us to describe geometrically electromagnetism and nuclear fields and unify it with gravity, in a different way that Kaluza-Klein theories do. Specifically, the electromagnetic field $A_\mu$, is included in the free geodesic equation of $C^4$. By embedding our usual 4-d real space-time in the symplectic 8-d real space-time (symplectic $R^8$ is algebraically isomorphic to $C^4$), we derive the usual geodesic equation of a charged particle in gravitational field, plus new information which is interpreted. Afterwards, we formulate and explore the extended special relativity and extended general relativity an $C^4$ or$R^8$. After embedding our usual 4-d space-time in $R^8$, two new phenomena rise naturally, that are interpreted as "dark matter" and "dark energy". A new cosmological model is presented, while the geometrical terms associated with "dark matter" and "dark energy" are investigated. Similarities, patterns and differences between "dark matter", "dark energy", ordinary matter and radiation are presented, where "dark energy" is a dynamic entity and "dark matter" reveal itself as a "mediator" betwen ordinary matter and "dark energy". Moreover, "dark matter" is deeply connected with "dark energy". Furthermore, the extended Hamilton-Jacobi equation of the extended space-time, is transformed naturally as an extended Klein-Gordon equation, in order to get in contact with quantum theories. By solving the Klein-Gordon equation analytically, we derive an eigenvalue for Higg's boson mass value at 125,173945 $Gev/c^{2}$. The extended Klein-Gordon equation, also connects Higg's boson (or vacuum) with Cosmology, due to the existence of our second "time" T (cosmological time), which serve us to connect quantum theories with Cosmology. Afterwards, in the general case, we explore the symmetries of the curved Hamilton-Jacobi equation locally, in order to investigate the consequences of a $C^4$ space-time in Standard Model. An extension to Standard Model is revealed, especially in the sector of strong nuclear field. The Stiefel manifold $SU(4)/SU(2)$ seems capable not only to describe the strong nuclear field but give us,as well, enough room to explore in the future, the possibility to explain quark confinment. Our extension, flavors firstly the unification of nuclear fields and afterwards the unification of nuclear fields with electromagnetic field. The desired grand unification, is achieved locally, through the symmetry group $GL(4,C)\simeq SO(4,4)\cap U(4)$ and we present a potential mechanism to reduce the existing particle numbers to just six. Afterwards,23 present the extended Dirac equation in $C^4$ space-time (Majorana-Weyl representation) plus a preliminary attempt to introduce a pure geometric structure for fermions. Finally, we consider a new geometric structure through n-linear forms in order to give geometric explanation for quantisation

Aboriginal Australians have a fundamental human right to opportunities that lead to healthy and flourishing lives. While the impact of trauma on Aboriginal Australians is well-documented, a pervasive deficit narrative that focuses on problems and pathology persists in research and policy discourse. This narrative risks further exacerbating Aboriginal disadvantage, through a focus on ‘fixing what is wrong’ with Aboriginal Australians, and the internalising of these narratives by Aboriginal Australians. While a growing body of research adopts strength-based models, limited research has sought to explore Aboriginal flourishing. This conceptual paper seeks to contribute to a burgeoning paradigm shift in Aboriginal research, seeking to understand what can be learned from Aboriginal people who flourish, how we best determine this, and in what contexts this can be impactful. Within, we argue the case for a new approach to exploring Aboriginal wellbeing that integrates salutogenic, positive psychology concepts with complex systems theory to understand and promote Aboriginal wellbeing and flourishing, While deeper work may be required to establish the parameters of a strength-based, culturally aligned Aboriginal conceptualisation of positive psychology, we suggest the integration of Aboriginal and Western methodologies offer unique and potent means of shifting the dial on seemingly intractable problems.

This work presents some characteristics of MoNet, a computerized platform for the modeling and visualization of complex systems. Emphasis is on the ideas that allowed the successful progressive development of this modeling platform, which goes along with the implementation of applications to the modeling of several studied systems. The platform has the capacity to represent different aspects of systems modeled at different observation scales. This tool offers advantages in the sense of favoring the perception of the phenomenon of the emergence of information, associated with changes of scale. Some criteria used for the construction of this modeling platform are included. The power of current computers has made practical representing graphic resources such as shapes, line thickness, overlaying-text tags, colors and transparencies, in the graphical modeling of systems made up of many elements. By visualizing diagrams conveniently designed to highlight contrasts, these modeling platforms allow the recognition of patterns that drive our understanding of systems and their structure. Graphs that reflect the benefits of the tool regarding the visualization of systems at different scales of observation are presented to illustrate the application of the platform.

The fusion of "innovation theory" and "ecology" gave birth to a large number of studies on "innovation ecology", which mainly studies how to build an industrial ecological chain at the regional level, focusing on self-evolution, achieving ecological balance, and enabling the regional economy to take the path of sustainable innovation. This type of research borrows a lot of concepts from ecology, and very vividly describes the competition and cooperation relationships formed by various agents in the innovation system, laying a good foundation for qualitative analysis of the inherent dynamics of innovation development. However, many studies focus on the analogous description of ecosystems and economic systems, lacking scientifically and rigorously quantitative empirical research as a support. This paper uses network-based indicators such as degree, cluster coefficient, and betweenness centrality to measure the function and position of high-tech enterprises in the Z-Park in a business environment, so as to clarify the socio-economic meaning of the topological structure of the regional innovation system. On this basis, it provides theoretical references for regional innovation development and sustainable development policy formulation.

Complex modeling has received significant attention in recent years and is increasingly used to explain the statistical phenomenon with increasing and decreasing fluctuations such as the similarity or difference of spike protein charge patterns of coronaviruses. Different from the existing covariance or correlation coefficient methods in traditional integer dimension construction, this study proposes a simplified novel fractional dimension derivation with the exact Excel tool algorithm. It involves the fractional center moment extension to covariance, which ends up a complex covariance coefficient that is better than the Pearson correlation coefficient, in the sense that the nonlinearity relationship can be further depicted. The spike protein sequences of coronaviruses were obtained from the GenBank and GISAID database, including the coronaviruses from pangolin, bat, canine, swine (three variants), feline, tiger, SARS-CoV-1, MERS, and SARS-CoV-2 (including the strains of Wuhan, Beijing, New York, German, and UK variant B.1.1.7) were used as the representative examples in this study. By examining the values above and below the average/mean based on the positive and negative charge patterns of the amino acid residues of the spike proteins from coronaviruses, the proposed algorithm provides deep insights into the nonlinear evolving trends of spike proteins for understanding the viral evolution and identifying the protein characteristics associated with viral fatality. The calculation results demonstrate that the complex covariance coefficient analyzed by this algorithm is capable of distinguishing the subtle nonlinear differences in the spike protein charge patterns with reference to Wuhan strain SARS-CoV-2 for which the Pearson correlation coefficient may overlook. Our analysis reveals the unique convergent (positive correlative) to divergent (negative correlative) domain center positions of each virus. The convergent or conserved region may be critical to the viral stability or viability; while the divergent region is highly variable between coronaviruses suggesting high frequency of mutations in this region. The analyses show that the conserved center region of SARS-CoV-1 spike protein is located at amino acid residues 900, but shifted to the amino acid residues 700 in MERS spike protein, and then to amino acid residues 600 in SARS-COV-2 spike protein, indicating the evolvement of the coronaviruses. Interestingly, the conserved center region of the spike protein in SARS-COV-2 variant B.1.1.7 shifted back to amino acid residues 700, suggesting this variant is more virulent than the original SARS-COV-2 strain. Another important characteristic our study reveals is that the distance between the divergent mean and the maximal divergent point in each of the viruses (MERS>SARS-CoV-1>SARS-CoV-2) is proportional to viral fatality rate. This algorithm may help to understand and analyze the evolving trends and critical characteristics of SARS-COV-2 variants, other coronaviral proteins and viruses.

Medical Trust-Network is one of the most promising fields of study in network science. Establishment of trust within medical entities ensures better treatment and increases better medical facilities. The word ‘Trust’ signifies a very important behavioral aspect between any human entities, especially among doctors and patients. To represent such relationships Trust Network Models are built to express the interactions between human entities within such networks. Though the idea of a Trust-Network has traditionally been one of the major areas of research, yet the concept of a medical trust network model is relatively a new domain. In this paper, we introduce an overall multilayered Trust Network to represent the entire healthcare architecture. More specifically our model is based on an evolutionary graph system with a discrete relationship between the three most important entities of any healthcare system, namely – Doctors, Departments, and Hospitals. Observations indicate that based on our model, the medical healthcare system is a multilayered model unlike a feed-forward model as indicated by previous studies.

The importance of antibodies in health care and the biotechnology research and development demands not only knowledge of their experimental structures at high resolution, but also practical implementation of this knowledge for both effective and efficient design and production of antibody for its use in both medical and research applications. While the experimental wet-lab approach is usually costly, laborious and time-consuming, computational (dry-lab) approaches, in spite of their intrinsic limitations in comparison with its experimental (wet-lab) counterpart, provide a cheaper and faster alternative option. For the first time, this article reports a comprehensive set of structural electrostatic features extracted from experimentally determined antigen-antibody-related structures, including especially those structural electrostatic features at the interfaces of all experimentally determined antigen-antibody complex structures as of February 29, 2020, to facilitate effective and efficient machine learning-based computational antibody design using currently available experimental structures inside Protein Data Bank.

Distributed Systems architectures are becoming the standard computational model for processing and transportation of information, especially for Cloud Computing environments. The increase in demand for application processing and data management from enterprise and end-user workloads continues to move from a single-node client-server architecture to a distributed multitier design where data processing and transmission are segregated. Software development must considerer the orchestration required to provision its core components in order to deploy the services efficiently in many independent, loosely coupled - physically and virtually interconnected - data centers spread geographically, across the globe. This network routing challenge can be modeled as a variation of the Travelling Salesman Problem (TSP). This paper proposes a new optimization algorithm for optimum route selection using Algorithmic Information Theory. The Kelly criterion for a Shannon-Bernoulli process is used to generate a reliable quantitative algorithm to find a near optimal solution tour. The algorithm is then verified by comparing the results with heuristic solutions in 3 test cases. A statistical analysis is designed to measure the significance of the results between the algorithms and the entropy function can be derived from the distribution. The tested results shown an improvement in the solution quality by producing routes with smaller length and time requirements. The quality of the results proves the flexibility of the proposed algorithm for problems with different complexities without relying in nature-inspired models such as Genetic Algorithms and Simulated Annealing. This algorithm can be used by orchestration applications to deploy services across large cluster of nodes by making better decision in the route design.

The purpose of work is to quantify the changes of the organism functional reserves during the successive phases of the human health Space-Time Continuum (STC) on the basis of postulates of reliability complex systems theory. The study is devoted to the problem of age-related human involution, which is evaluated not from the causal, but from the kinetic point of view. The analysis of 10 most important basic life support systems of human body — cardiovascular (CVS), respiratory (RS), nervous (NS), digestive (DS), endocrine (ES), immune (IS), excretory (EXS), brain (BS), musculo-skeletal (MSS), hematopoietic (HS) was carried out. Based on this analysis two levels of ensuring the reliability of organism’s work were revealed: sequential and parallel. The system of logical equations for reduced sequential system is: Ys1 = CVS ∧ RS ∧ BS, where ∧ is the notation for the conjunctions of set elements. The system of logical equations for the reduced parallel system is: Ys2 = NS ∨ DS ∨ ES ∨ IS ∨ HS ∨ EXS ∨ MSS ,where ∨ is the disjunction of the scheme elements. Visualization of human STC changes the concept of the kinetics of age-related changes in the organism and the role of determinants of health as a stable factor accompanying a uniform, smooth transition from the most pronounced functions of the body to their gradual extinction. For human STC is formulated the following regularity kinetics of involutionary processes: after 30 years of age in the human body morphological changes regress in arithmetic progression, and the functions of organs in a geometric one. Assumption of health as a state redundancy of functions is suggested.

The present article addresses the long-standing problem of the polymer brush bilayers under stationary shear flow at non-linear response regime where the system gets a non-Newtonian fluid. The main idea behind this research would be the fact that the immense lubricity of the polymer brush bilayers originates from a global restructuring that takes place at large shear rates. It is shown here that physical quantities like, stress tensor, viscosity tensor, the friction coefficient and the chain extensions could become dependent on the shear rate at non-Newtonian regime. Apparently, the sub-linear scaling of the physical quantities at large shear rates is solely due to the fact that the chains stretch in the shear direction.

We explore several ways, in order to include fermionic structures naturally in a physical theory in C⁴. We begin with the standard Dirac formalism and we proceed by using Cartan's property of triality as a second option. Afterwards, we suggest a new approach (in a preliminary basis), by introducing an 1-linear form, as the "square root of the geometry" derived by the usual 2-linear forms (quadratic forms). Keeping this way, we introduce n-linear forms, in order to formulate a new geometric structure, which could be suitable for the formulation of a pure geometric unied theory.

We explore the field equations in a 4-d complex space-time, in the same way, that general relativity does for our usual 4-d real space-time, forming this way, a new "general relativity" in C⁴ space-time, free of sources. Afterwards, by embedding our usual 4-d real space-time in C⁴ space-time, we describe geometrically the energy-momentum tensor T_μν as the lost geometric information of this embedding. We further give possible explanation of dark eld and dark energy.

Reservoir computers (RCs) are a biology inspired computational framework for signal processing typically implemented using recurrent neural networks. Recent work has shown that Boolean networks (BN) can also be used as reservoirs. We analyze the performance of BN RCs, measuring their flexibility and identifying factors that determine effective approximation of Boolean functions that are applied in a sliding-window fashion over a binary signal, either non-recursively or recursively. We train and test BN RCs of different sizes, signal connectivity, and in-degree to approximate 3-bit, 5-bit and 3-bit recursive binary functions. We analyze how BN RC parameters and function average sensitivity, a measure of function smoothness, affect approximation accuracy as well as the spread of accuracies for a single reservoir. We found that approximation accuracy and reservoir flexibility are highly dependent on RC parameters. Overall, our results indicate that not all reservoirs are equally flexible and RC instantiation and training can be more efficient if this is taken into account. The optimum range of RC parameters opens up an angle of exploration for understanding how biological systems might be tuned to balance system restraints with processing capacity.

Abstract5′,8-Cyclo-2′-deoxyadenosine (cdA), in the 5′R and 5′Sdiastereomeric forms, are typical non strand-break oxidative DNA lesions, induced by hydroxyl radicals, with emerging importance as a molecular marker. These lesions are exclusively repaired by nucleotide excision repair (NER) mechanism with a low efficiency, thus readily accumulating in the genome. Poly(ADP-ribose) polymerase1 (PARP1) acts as an early responder to DNA damage and plays a key role as a nick sensor in the maintenance of the integrity of the genome by recognizing nicked DNA. So far, it was unknown whether the diastereomeric cdA lesions could induce specific PARP1 binding. Here we provide the first evidence of PARP1 to selectively recognize the diastereomeric lesions 5′S-cdA and 5′R-cdA in vitro as compared to deoxyadenosine in model DNA substrates (23-mers) by using circular dichroism,fluorescence spectroscopy, immunoblotting analysis and gel mobility shift assay. Several features of the recognition of the damaged and undamaged oligonucleotides by PARP1were characterized. Remarkably, PARP1 efficiently binds to both cdA lesions in the double stranded (ds)-oligonucleotides. In particular, PARP1 proved to bind 5′S-cdAwith a higher affinity constant for the 5'S lesion in a model of ds DNA than 5′R-cdA, showing different recognition patterns, also compared with undamaged dA. This new finding highlights the ability of PARP1 to recognize and differentiate the distorted DNA backbone in a biomimetic system caused by different diastereomeric forms of a cdA lesion.

The World Health Organization has developed the Integrated Care of Older People (ICOPE) strategy, a program based on the measurement of intrinsic capacity (IC) as “the composite of all physical and mental attributes on which an individual can draw”. Multicomponent interventions appear to be the more effective approach to enhance IC and to prevent frailty and dependence, being adapted physical activity is the preventive intervention that has shown more evidence in the treatment of frailty and risk of falls. The present study aims to describe the development of a multi-domain group-based intervention addressed to frail older people living in the community aimed to improve and/or maintain intrinsic capacity by means of promoting physical activity, healthy nutrition, and psychological wellbeing in frail older people. We used the GUIDED checklist to describe the development process of AMICOPE (Aptitude Multi-domain group-based intervention to improve and/or maintain IC in frail Older PEople). The intervention was built upon the ICOPE framework and it is described with Template for Intervention Description and Replication (TIDieR) guidelines and it includes dietary advice, cognitive stimulation strategies, medication review, goal setting, and activities to strengthen social support and manage depressive symptoms, as well as strength, balance and flexibility exercise using the Vivifrail program. The study represents the first stage of the UK Medical Research Council framework for developing and evaluating a complex intervention. The next step should be carrying out a feasibility study for the AMICOPE intervention, and in a later stage, assessing the effectiveness in a randomized controlled trial.

After developed the formulation of a "general relativity" in C⁴ [2], we proceed with the formulation of a Hamilton-Jacobi equation in C⁴. We argue that in this consideration, the usual problems of the ADM formalism, do not exist, due to the complex time as it exists in our consideration. Specically, we can derive a suitable dispersion relation in order to work with and nd a generalised super Hamiltonian

The retrieval of sun-induced chlorophyll fluorescence is greatly beneficial to studies of marine phytoplankton biomass, physiology, and composition and is required for user applications and services. Customarily phytoplankton chlorophyll fluorescence is determined from satellite measurements through a fluorescence line-height algorithm using three bands around 680 nm. We propose here a modified retrieval, making use of all available bands in the relevant wavelength range with the goal to improve the effectiveness of the algorithm in optically complex waters. For the Ocean and Land Colour Instrument (OLCI) we quantify a Fluorescence Peak Height from fitting a Gaussian function and related terms into the top-of-atmosphere reflectance bands between 650 and 750 nm. This algorithm retrieves, what we call Fluorescence Peak Height from fitting a Gaussian function upon other terms to top-of-atmosphere reflectance bands between 650 and 750 nm. This approach is applicable to Level-1 and Level-2 data. We find a good correlation of the retrieved fluorescence product to global in-situ chlorophyll measurements, as well as a consistent relation between chlorophyll concentration and fluorescence from radiative transfer modelling and OLCI/in-situ comparison. The algorithm is applicable to complex waters without needing an atmospheric correction and vicarious calibration and features an inherent correction of small spectral shifts, as required for OLCI measurements.

System level diagnosis is an abstraction of high level and, thus, its practical implementation to particular cases of complex systems is the task which requires additional investigations, both theoretical and modeling. Mostly, diagnosis at system level intends to identify only permanently faulty units. In the paper, we consider the case when both permanently and intermittently faulty units can occur in the system. Identification of intermittently faulty units has some specifics which we have considered in this paper. We also suggest the method which allows distinguishing among different types of intermittent faults. Diagnosis procedure was suggested for each type of intermittent faults.

We explore the possibility to nd the usual quantum theories, within the formulation of a classic theory of mechanics in C⁴. Specically, by releasing the end-point of the integral of the action derived in C⁴, we derive the dynamic path length of the geodesic equation in C⁴. In the at case, the derived Hamilton-Jacobi equations, were identied as the usual Klein-Gordon equation, where the complex functional action S(z_i), is identied as the usual complex scalar field φ. Afterwards, we study the energy-momentum 4-d complex vector, in order to re-establish the usual covariant derivative of gauge theories.

A recent paper demonstrates the importance of the linker region joining the two SNARE motifs of the neuronal t-SNARE SNAP25 for maintaining rates of secretion with roles for distinct segments in speeding fusion pore expansion (Shaaban et al., 2019, Elife. 8). Remarkably, lipid perturbing agents rescue a palmitoylation-deficient phenotype that includes slow fusion pore expansion, suggesting that protein-protein interactions have a role not only in bringing together the granule or vesicle membrane with the plasma membrane but also in orchestrating protein-lipid interactions leading to the fusion reaction. Furthermore, biochemical investigations demonstrate the importance of the C-terminal domain of the linker in the formation of the plasma membrane t-SNARE acceptor complex for synaptobrevin2 (Jiang, et al., 2019, FASEB J. 33:7985-7994;Shaaban et al., 2019, Elife. 8). This insight, together with biophysical and optical studies from other laboratories (Wang, et al., 2008, Molecular Biology of the Cell. 19:3944-3955; Zhao, et al., 2013, Proc Natl Acad Sci U S A. 110:14249-14254) suggests that the plasma membrane SNARE acceptor complex between SNAP25 and syntaxin and the resulting trans SNARE complex with the v-SNARE synaptobrevin form just milliseconds before fusion.

The dominant paradigm holds that spontaneous and therapeutically induced anti-tumor responses are mediated mainly by CD8 T cells and directed against tumor-specific antigens (TSAs). The presence of specific TSAs on cancer cells can only be proven by mass spectrometry analyses. Bioinformatic predictions and reverse immunology studies cannot provide this type of conclusive evidence. Most TSAs are coded by unmutated non-canonical transcripts that arise from cancer-specific epigenetic and splicing aberrations. When searching for TSAs, mass spectrometry analyses must therefore interrogate not only the canonical reading frame of annotated exome but all reading frames of the entire translatome. The majority of aberrantly expressed TSAs (aeTSAs) derive from unstable short-lived proteins that are good substrates for direct MHC I presentation but poor substrates for cross-presentation. This is an important caveat because cancer cells are poor antigen-presenting cells and the immune system therefore depends on cross-presentation by dendritic cells (DCs) to detect the presence of TSAs. We therefore postulate that, in the untreated host, most aeTSAs are undetected by the immune system. We present evidence suggesting that vaccines inducing direct aeTSA presentation by DCs represent an attractive strategy for cancer treatment.

Probability is an open question in the ontological interpretation of quantum mechanics. It has been discussed in some trajectory interpretations such as Bohmian mechanics and stochastic mechanics. New questions arise when the domain of probability extends to the complex space, including the generation of complex trajectories, the definition of the complex probability, the relation of the complex probability to the real quantum probability, and so on. The complex treatment proposed here applies the optimal quantum guidance law to derive the stochastic differential (SD) equation governing the particle’s random motions in the complex plane. The ensemble of the complex quantum random trajectories (CQRTs) solved from the complex SD equation is used to construct the probability distribution ρc(t,x,y) of the particle’s position over the complex plane z=x+iy. The correctness of the obtained complex probability is confirmed by the solution of the complex Fokker-Planck equation. The significant contribution of the complex probability is that it can be used to reconstruct both quantum probability and classical probability, and to clarify their relationship. Although quantum probability and classical probability are both defined on the real axis, they are obtained by projecting complex probability onto the real axis in different ways. This difference explains why the quantum probability cannot exactly converge to the classical probability when the quantum number is large.

Peptide-based drugs are promising anticancer candidates due to their biocompatibility, and low toxicity. Particularly, tumor homing peptides (THPs) have the ability to bind specifically to can-cer cells receptors and tumor vasculature. Despite their potential to develop antitumor drugs, there are few available prediction tools to assist the discovery of new THPs. Two webservers based on machine learning models are currently active, the TumorHPD (https://webs.iiitd.edu.in/raghava/tumorhpd) and the THPep (http://codes.bio/thpep), and more recently the SCMTHP (SCMTHP (pmlabstack.pythonanywhere.com), based on scoring card method. Herein, a novel method based on network science and similarity searching implemented in the starPep toolbox (http://mobiosd-hub.com/starpep/) is presented for THPs discovery. The approach leverages from exploring the structural space of THPs with Chemical Space Networks (CSNs) and from applying centrality measures to identify the most relevant and non-redundant THPs sequences within the CSN. Such THPs were considered as queries (Qs) for multi-query similarity searches that applies a group fusion (MAX-SIM rule) model. The resulting multi-query similarity searching models (SSMs) were validated with three benchmarking datasets of THPs/non-THPs. Predictions achieved accuracies ranged from 92.64 to 99.18% and Matthews Correlation Coefficients between 0.894-0.98, outperforming state-of-the-art predictors. The best model was applied to repurpose AMPs from the starPep database as THPs, which were subse-quently optimized for the TH activity. Finally, 54 promising THP leads were discovered, and their sequences were analyzed to encounter novel motifs. These results demonstrate the potential of CSNs and multi-query similarity searching for a rapid and accurate identification of THPs.

Link prediction is an iconic problem in complex networks because deals with the ability to predict nonobserved existing or future parts of the network structure. The impact of this prediction on real applications can be disruptive: from prediction of covert links between terrorists in their social networks to repositioning of drugs in molecular diseasome networks. Here we compare: (1) an ensemble meta-learning method (Ghasemian et al.), which uses an artificial intelligence (AI) stacking strategy to create a single meta-model from hundreds of other models; (2) a structural predictability method (SPM, Lü et al.), which relies on a theory derived from quantum mechanics and does not assume any model; (3) a modelling rule named Cannistraci-Hebb (CH, Muscoloni et al.), which relies on one brain-bioinspired model adapting to the intrinsic network structure.We conclude that brute-force stacking of algorithms by AI does not perform better than (and is often significantly outperformed by) SPM and one simple brain-bioinspired rule such as CH. This agrees with the Gödel incompleteness: stacking is optimal but incomplete, you cannot squeeze out more than what is already in your features. Hence, we should also pursue AI that resembles human-like physical ‘understanding’ of simple generalized rules associated to complexity. The future might be populated by AI that ‘steals for us the fire from Gods’, towards machine intelligence that creates new rules rather than stacking the ones already known.

A developed six-port reflectometry (SPR) system was integrated to measure the relative permittivity of tumor and normal breast tissue for medical diagnostic purpose. In order to obtain an accurate and precise measurement, the calibration process was done to the SPR using the well-known three-standard technique. Next, the studied dielectric probe was connected to the calibrated measurement-port of the SPR. The open end of the probe aperture was dibbed into the normal and tumor synthetic breast tissue samples to measure the synthetic breast tissues dielectric constant, ɛrʹ, and loss factor, ɛrʺ in the frequency range of 1.5 GHz to 3.3 GHz. Finally, the comparative studies were conducted between commercial VNA with Keysight 85070E dielectric probe and the studied SPR-probe system based on the measured magnitude of the reflection coefficient, phase shift, dielectric constant, and loss factor of the synthetic breast samples. The maximum absolute errors of the measured reflection coefficient magnitude, phase shift, dielectric constant, and loss factor were found to be 0.01, 1.07°, 1.12, and 0.75, respectively. It was ascertained that the predicted dielectric constant, ɛrʹ, is able to differentiate between normal, (ɛrʹ < 50) and tumor, (ɛrʹ > 50) breast tissues.

We propose a notion of $(q,\sigma,\tau)$-differential graded algebra, which generalizes the notions of $(\sigma,\tau)$-differential graded algebra and $q$-differential graded algebra. We construct two examples of $(q,\sigma,\tau)$-differential graded algebra, where the first one is constructed by means of generalized Clifford algebra with two generators (reduced quantum plane), where we use a $(\sigma,\tau)$-twisted graded $q$-commutator. In order to construct the second example, we introduce a notion of $(\sigma,\tau)$-pre-cosimplicial algebra.

For the first time in the world, we provided a phenomenologically verifiable proof for the validation of origin of universe and perceivable reality from the unperceivable information based on Ayurveda. We also provided the axiomatic definitions for the terminologies used to deliver the theoretical framework for the same based on Bharatheeya Knowledge Systems. The presented manuscript provides a corelation between quantum information transport and emergence of gunam “Laghu” and gunam “Guru”. We identified that this point of emergence can be considered as the origin point in the continuous process of generation of Perceivable Reality “Vyaktham” from Unperceivable Information “Avyaktham”. In this context we can consider the unperceivable information in “Avyaktham” as dark matter. So, we must develop methods like gunascopy or informationscopy to understand the types of information imbibed in the quantum matter of a dravyam to understand its original physico-chemical-biological and information state of the constituent matter. This is possible through the assessment of Dravya Guna aspects and panchabhootha tatwas of the dravyas. For the first time in the world, we have developed the method to derive all the gunas from “guru” and “Laghu” and calculated the mass of the finitie components of Nava Dravyas including Mann, Aatma, Kaal, Disha, Aakash, Vaayu, Agni, Jal and Prithvi from the quantum information emergence equation. We strongly believe that this work will open up new avenues to explore the frontiers of reality and universe through natural cognition. The solutions to the Yang-Mill conjecture is achieved by our team using the Quantum Information Emergence and Transport Equations. We proved that the information bounded in the quantum states of the constituent quantum matter of quantum particles will provide them positive masses, even though they travel at the speed of light. Based on the phenomenologically verifiable axioms proposed in this work, we proved that the space on the topologically invarient 2D Poincare Sphere which is equivalent to a 2D space without boundaries can facilitate the never-ending loop of continuous quantum information transport between “Avyaktham” and “Vyaktham”. So the information availabe in the constituent quantum states of “Avyaktham” is equal to the postiive mass of quantum systems travelling at the speed of light. In such condition all the mass of the quantum particles will be converted in to information bounded in the corresponding quantum states of the quantum matter. This complete conversion of mass of the quantumparticles into information will happen only at maximum entropy. Thus at maximum entropy the information which is self information entangled with its own quantum states in “Avyaktham” will have a positive mass equal to the mass gap proposed in the Yang-Mill conjecture.

Background and objectives: Only a few studies analyzed the physical activity level of elderly people living alone in local communities and evaluated the relationship between it and mental health. The purpose of this study was to investigate the relationship between physical activity and depression in the elderly living alone and to provide basic data for the prevention of depression in the elderly. Materials and Methods: We analyzed 256 elderly people living alone aged 65 years or older who completed the 2014 Korea National Health and Nutrition Examination Survey. Depression was defined as a score of 10 or higher using Patient Health Questionnaire-10(PHQ-9). This study investigated walking per week, days of muscular strength exercise performance in the past one week, days of flexibility exercise in the past one week, mean hours in a sitting position per day, the numbers of days and hours conducting a high intensity physical activity in the past one week, and numbers of days and hours conducting a medium intensity physical activity in the past one week to define physical activity. Our study presented prevalence odds ratios (pOR) and 95% confidence interval (CI) by using complex sample logistic regression analysis in order to identify the relationship between physical activity and depression. Results: The results of complex sample logistic regression analysis showed that flexibility exercise was significantly related to depression (p <0.05). On the other hand, the mean hours in a sitting position per day, aerobic physical activity, walking, and muscular strength exercise were not significantly related to geriatric depression. Conclusions: The results of our study implied that persistent flexibility exercise might be more effective to maintain a healthy mental status than muscular strength exercise. A longitudinal study is required to prove the causal relationship between physical activity and depression in the old age.

In the paper, the author finds bounds of the sine and cosine along a circle on the complex plane in terms of two double inequalities for the norms of the sine and cosine along a circle on the complex plane.

Fourier transform infrared (FTIR) absorption spectroscopy of cold molecules and clusters in supersonic slit jet expansions complements and extends more sensitive action spectroscopy techniques and provides important reference data for the latter. We describe how its major drawback, large substance and carrier gas consumption, can be alleviated by one to two orders of magnitude via direct and continuous recycling of the gas mixture. This is achieved by a combination of dry rotary lobe and screw pump compression. The signal-to-noise ratio is boosted by the established buffered giant gas pulse technique with full interferogram synchronization. The buildup of water impurities typically limits the recycling gain, but is turned into a feature for the study of hydrate complexes of volatile molecules. Continuous operation with a single gas filling over several days becomes practical and useful. Decadic absorbances in the low ppm range are detectable and the mid infrared range can be recorded simultaneously with the near infrared. The less straightforward hydration number assignment of spectral features in direct absorption spectroscopy is supported by a gradual water buildup at a rate of less than 0.5 mg/h. A recent reassignment proposal for the water dimer OH stretching spectrum is refuted and vibrational spectra of vacuum-isolated 18O-water clusters are presented for the first time. Methanol docking on asymmetric ketones is used to illustrate the advantages and limitations of the recycling concept. Previous assignments of the hydrate complex of 1-phenylethanol are confirmed. Additional features of the setup await testing and refinement, but the recycling technique already substantially widens the applicability of direct absorption spectroscopy of neutral molecular clusters. It may be attractive for other high-throughput jet spectrometers.

Quantum computers are invaluable tools to explore the properties of complex quantum systems. We show that dynamical localization of the quantum sawtooth map, a highly sensitive quantum coherent phenomenon, can be simulated on actual, small-scale quantum processors. Our results demonstrate that quantum computing of dynamical localization may become a convenient tool for evaluating advances in quantum hardware performances.

To date, theoretical analyses have provided several useful methods/algorithms for studying transition states and non-covalent interactions. Potential Energy Scan (PES) is one such method that has found wide application in the physicochemical community. Analyzing the PES profiles of the catalytic system of FeBr3 in Electrophilic Aromatic Substitution (EAS) with molecular halogens, one can notice an obvious difference from the modern textbook mechanisms proposed in this area of study. Moreover, the newly presented Graphic Methodology (GM) allows a simple and reliable transition state determination even for very weakly bound charge transfer complexes using second-order derivatives as an efficient tool in the graphical analysis. Relative errors that can be reduced to a few parts per thousand in transition state estimation make this method a potentially very useful tool in further graphical studies of non-covalent interactions. Studies performed using high-precision semiempirical methods suggest that the process of halonium ion quenching proceeds along a completely different pathway, suggesting a possible novel transition metal-nonmetal catalytic system involved in the EAS electrophilic quenching step. The results presented here strongly suggest a future GM application that is widely used and the introduction of pseudo and pre-transition states as new terms in the description of non-covalent interactions.

Information can be considered as the most fundamental, philosophical, physical and mathematical concept originating from the totality by means of physical and mathematical transcendentalism (the counterpart of philosophical transcendentalism). Classical and quantum information, particularly by their units, bit and qubit, correspond and unify the finite and infinite. As classical information is relevant to finite series and sets, as quantum information, to infinite ones. A fundamental joint relativity of the finite and infinite, of the external and internal is to be investigated. The corresponding invariance is able to define physical action and its quantity only on the basis of information and especially: on the relativity of classical and quantum information. The concept of transcendental time, an epoché in relation to the direction of time arrow can be defined. Its correlate is that information invariant to the finite and infinite, therefore unifying both classical and quantum information.

This article presents, for the first time, the kinetics and the general conversion features of a 3-initiator system (A/B/N), based on proposed mechanism of Mokbel et al, for both free radical polymerization (FRP) of acrylates and the free radical promoted cationic polymerization (CP) of epoxides using copper complex as the initiator. Higher FRP and CP conversion can be achieved by co-initiators concentration [B] and [N], via the dual function of (i) regeneration [A], and (ii) generation of extra radicals S' and S. The FRP and CP conversion is proportional to, respectively, the nonlinear and linear power of bI[A][B], where b and I are the absorption coefficient and the light intensity, respectively. System in air has lower conversion than in laminate due to the oxygen inhibition effects. For thick samples (with thickness z), there is an optimal concentration [A*] which is inverse proportional (bzI), in contrast with very thin sample, in which the conversion is an increasing function of [A] and [B]. The unique feature of dark polymerization in CP conversion enables the polymerization to continue in living mode, in contrasts with that of the radical-mediated pathway in most conventional FRP. The measured results of Mokbel et al are well analyzed and matching the predicted features of our modeling.

A series of dinuclear copper(I) N,C,N- and P,C,P-carbodiphosphorane (CDP) complexes using multidentate ligands CDP(Py)2 (1) and (CDP(CH2PPh2)2 (13) have been isolated and characterized. Detailed structural information was gained by single crystal XRD analyses of nine representative examples. The common structural motive is the central double ylidic carbon atom with its characteristic two lone-pairs involved into binding of two geminal L-Cu(I) fragments at Cu-Cu distances in the range 2.55 – 2.67 Å. In order to enhance conformational rigidity within the characteristic Cu-C-Cu triangle, two types of chelating side arms were symmetrically attached to each phosphorus atom: two 2-pyridyl functions in ligand CDP(Py)2 (1) and its dinuclear copper complexes 2-9 and 11, as well as two diphenylphosphinomethylene functions in ligand CDP(CH2PPh2)2 (13) and its di- and mononuclear complexes 14-18. Neutral complexes were typically obtained via reaction of 1 with Cu(I) species CuCl, CuI, and CuSPh or via salt elimination reaction of [(CuCl)2(CDP(Py)2] (2) with sodium carbazolate. Cationic Cu(I) complexes were prepared upon treating 1 with two equivalents of [Cu(NCMe)4]PF6, followed by the addition of either two equivalent of an aryl phosphine (PPh3, P(C6H4OMe)3) or one equivalent of a bisphosphine ligands DPEPhos, XantPhos or dppf. For the first time carbodiphosphorane CDP(CH2PPh2)2 (13) could be isolated upon treating its precursor [CH(dppm)2]Cl (12) with NaNH2 in liquid NH3. A protonated and a deprotonated derivative of ligand 13 were prepared and their coordination was compared to neutral CDP ligand 13. NMR analysis and DFT calculations reveal, that the most stable tautomer of 13 does not show a CDP (or carbone) structure in its uncoordinated base form. For most of the prepared complexes, photoluminescence upon irradiation with UV light at room temperature was observed. Quantum yields (PL) were determined to 36% for dicationic [(CuPPh3)2(CDP(Py)2)](PF6)2 (4) and to 60% for neutral [(CuSPh)2(CDP(CH2PPh2)2] (16).

Using optical characterization, it is evident that the spin state of the spin crossover molecular complex [Fe{H2B(pz)2}2(bipy)] (pz = tris (pyrazol-1-1y)-borohydride, bipy = 2,2’-bipyridine) depends on the ferroelectric polarization of an adjacent thin film of the polymer ferroelectric polyvinylidene fluoride-hexafluoropropylene (PVDF-HFP). The UV-Vis spectroscopy reveals that room temperature switching of [Fe{H2B(pz)2}2(bipy)] molecules in bilayers of PVDF-HFP/[Fe{H2B(pz)2}2(bipy)] as a function of ferroelectric polar polarization. The electric polarity dependence of bilayers of PVDF-HFP/[Fe{H2B(pz)2}2(bipy)] shows a strong dependence on the thickness of the PVDF-HFP layer. The PVDF-HFP/[Fe{H2B(pz)2}2(bipy)] interface may affect polarization retention in the PVDF-HFP thin film limit.

This paper uses the complex regression analysis method to establish the customer’s load regression models, which consider economic indicators, temperature and rainfall. Furthermore, the proposed models are used to study the forecasting feasibility of the future energy sales and summer peak load demand. At first, this paper used least-squares techniques to derive regression models for considering economic indicators and temperature of 34 customer energy sales and total energy sales. Besides, the AMI high voltage customer demand data and system generating capacity for 24 hours were adopted to forecast summer peak load. The above-mentioned data analysis tool is used by EViews software to achieve, in order to verify the feasibility of the research framework. The study found that although its forecasting model accuracy is low only when mixed with temperature and high voltage demands. So, when mixed with high voltage demand data and system generating capacity for 24 hours to forecast peak load, the average error is ± 0.87% and in the majority of its energy sales forecasting model of average error is ±3%. This result can provide power company as future reference.

Viscoelastic testing (VET) by both TEG and ROTEM has demonstrated hypercoagulability early in Covid Associated Coagulopathy (CAC). Additional VET studies demonstrated fibrinolytic shutdown late in a majority of severely ill Covid-19 patients with associated elevation of D-dimer. Elevated d-dimer confirms that coagulation, followed by fibrinolysis, has occurred. These findings imply that, during CAC, three enzymes—thrombin, Factor XIIIa and plasmin—must have acted in sequence. However, limitations in standard VET analyses preclude exploration of the earliest phases of clot induction, as well as clot formation and clot dissolution in flowing blood. Herein we describe a novel method illuminating aspects of this unexplored area. In addition, we created an ex vivo blood flow model in which the interactions of thrombin, Factor XIII and plasmin with fibrinogen can be studied, allowing determination of Soluble Fibrin (SF), the highly unstable form of fibrin that precedes the appearance of a visible clot. This model allows determination of the SF level at which fibrin microclots begin to form and the length of time the resulting microclots persist under normal fibrinolytic attack. In addition, the flow model allows exploration of the late fibrinolytic shutdown that VET has previously demonstrated in CAC through standard methodology.

The strong couplings among ecological, economic, social and technological processes explains the complexification of human-made systems, and phenomena such as globalization, climate change, the increased urbanization and inequality of human societies, the power of information, and the COVID-19 syndemics. Among complexification’s essential features are non-decomposability, asynchronous behavior, components with many degrees of freedom, increased likelihood of catastrophic events, irreversibility, nonlinear phase spaces with immense combinatorial sizes, and the impossibility of long-term, detailed prediction. Sustainability for complex systems implies enough efficiency to explore and exploit their dynamic phase spaces and enough flexibility to coevolve with their environments. This in turn means solving intractable nonlinear semi-structured dynamic multi-objective optimization problems, with conflicting, incommensurable, non-cooperative objectives and purposes, under dynamic uncertainty, restricted access to materials, energy and information, and a given time horizon, aiming at enhancing the co-evolutionary power of the Biosphere and its human subsystems. Giving the high-stakes, the need for effective, efficient, diverse solutions, their local-global, present-future effects, and their unforeseen short, medium and long-term impacts, achieving sustainable complex systems implies the need for Sustainability-designed Universal Intelligent Agents, harnessing the strong functional coupling between human, artificial and nonhuman biological intelligence in a no-zero-sum game to achieve sustainability.

Complex systems exhibit critical thresholds at which they transition among alternative phases. Complex systems theory has been applied to analyze disease progression, distinguishing three stages along progression: (i) a normal non-infected state, (ii) a pre-disease state in which the host is infected and responds; therapeutic interventions could still be effective, (iii) an irreversible state, where the system is seriously threatened. The Dynamical Network Biomarker (DNB) theory sought for early-warnings of the transition from health to disease. Such DNBs might range from individual genes to complex structures in transcriptional regulatory or protein-protein interaction networks. Here we revisit transcriptomic data obtained during infection of tobacco plants with tobacco etch potyvirus to identify DNBs signaling the transition from mild/reversible to severe/irreversible disease. We identified genes showing a sudden transition in expression along disease. Some of these genes cluster in modules that show the properties of DNBs. These modules contain both genes known to be involved in response to pathogens (e.g., ADH2, CYP19, ERF1, KAB1, LAP1, MBF1C, PR1, or TPS5) and other genes not previously related to biotic stress responses (e.g., ABCI6, BBX21, NAP1, OSM34, or ZPN1).

β-cyclodextrin (CD) derivatives containing aromatic triazole ring were studied as potential carriers of drugs containing an anthraquinone moiety in the structure: anthraquinone-2-sulfonic acid (AQ2S), anthraquinone-2-carboxylic acid (AQ2CA) and a common anthracycline, daunorubicin (DNR). UV-Vis and voltammetry measurements were carried out to determine the solubilities and stability constants of the complexes formed and revealed the unique properties of the chosen CDs as effective pH dependent drug complexing agents. The stability constants of the drug complexes with the CDs containing triazole: βCDLip and βCDGAL were significantly larger than with the native βCD. The AQ2CA and AQ2S drugs are ill-soluble and their solubilities increased as the result of complex formation with βCDLip and βCDGAL ligands. AQ2CA, AQ2S were negatively charged at pH 7.4 and therefore they were less prone to form inclusion complex with the hydrophobic CD cavity than at pH 3 (characteristic of gastric juices) when they were protonated. βCDTriazole and βCDGAL ligands were found to form weaker inclusion complexes with the positively charged drug DNR at acidic pH (pH 5.5) than in the neutral medium (pH 7.4) when the drug dissociates to the neutral, uncharged form. This pH dependence is favorable for anti-tumor applications.

This article presents a review of the distribution system state estimation (DSSE) algorithms from the model-based approach to the recent data-driven methodologies. The insufficient measurements which result in low observability have motivated the need to shift from the conventional algorithm to data-driven approaches that can successfully estimate states despite the DSSE challenges. This article discusses the nonlinearity in the DSSE problem formulation and how different model-based methods have been proposed to mitigate the problems of robustness, ill-conditioning, and complexity. Moreover, approximate DSSE to obviate nonlinearity were discussed: complex linearization, small angle approximation, convexification and compressed sensing. Furthermore, probabilistic DSSE methods were also discussed in the need to quantify the uncertainty associated with the state estimation results. Also, data-driven methods applicable to DSSE, pseudo measurement generations, and topology identification were also discussed using machine and deep learning methods. Lastly, a recent approach that employs a hybrid of model-based and data-driven methods using matrix and tensor completion is surfacing because they work in a low observable condition of the network and can estimate the states satisfactorily. With this review, researchers can look further into developing and improving on the model-based data-driven methods less susceptible to the barriers in conventional DSSE algorithms.

A new type of ordinary differential equation is introduced and discussed, namely, the time-dependent order ordinary differential equations. These equations can be solved via fractional calculus and are mapped into Volterra integral equations of second kind with singular integrable kernel. The solutions of the time-dependent order differential equations smoothly deforms solutions of the classical integer order ordinary differential equations into one-another, and can generate or remove singularities. An interesting symmetry of the solution in relation to the Riemann zeta function and Harmonic numbers was also proved.

Gas turbine installations (GTIs) are widely used to generate electrical and thermal energy mainly by burning gaseous fuels. The use of GTIs to burn hydrogen as part of the development of hydrogen energy technology is currently of particular interest. In order to assess the prospects of using GTIs in such a way, it is necessary, among other things, to understand the carbon footprint of the gas turbine as part of the carbon footprint of the entire life cycle of hydrogen. The article provides an overview of the results of previously published studies on life cycle assessment (LCA) of technically complex devices associated with the production and consumption of fuel and energy, which, from the point of view of the complexity of LCA, are most similar to gas turbine installation. The characteristics of the considered stages and resources used in the assessment of the stages of the life cycle of technically complex equipment are presented, including an analysis of the amount of materials used in production and construction. Taking into account its specific application in Russia, an assessment of greenhouse gas emissions at the stages of the GTI life cycle per MWh of produced capacity was carried out.

Iloperidone (ILO) is a second-generation antipsychotic drug and a first-line treatment approved by USFDA in May 2009. Iloperidone belongs to Biopharmaceutical Classification Systems (BCS) class II; thus, it is poorly water-soluble, highly permeable, and has pH-dependent solubility. Cyclodextrins and their derivatives have a wide range of applications in different formulations due to their complexation ability, which improves the solubility, stability, safety, and bioavailability of a drug. We have tried the complexation of iloperidone with sulfobutyl ether-β-cyclodextrin (SEβCD) to improve its solubility and dissolution. Complexation was done by the kneading method. The characterization of the SEβCD complexes with Iloperidone was done by FTIR, differential scanning calorimetry (DSC), saturation solubility, etc. A multimedia dissolution of the complex was carried out and compared with the plain drug. A significant improvement in drug release was found from SEβCD complexes in all media when compared with the drug alone.

Recently, a paper was written to reformulate and strengthen the theory of semi-structured complex numbers H (a new number set invented to enable division by zero). Whilst the paper had profound results, the application of this number set in many areas of engineering and science has not been fully explored. Consequently, the aim of this paper was to establish the number set H as a useful mathematical tool by providing an amalgam of results arising from its application in several areas of engineering and science. In the process, this paper makes four major contributions: these are (1) determining the product of the gradients of a horizontal and vertical line; (2) developing new Euler formulas relating exponential, trigonometric and hyperbolic functions in the 3D semi-structured complex number Euclidean space; (3) establishing semi-structured complex numbers as a better extension of the complex number set than quaternions; (4) resolving singularities that may arise in engineering and science equations (because of division by zero) to develop reasonable conclusions in the absence of experimental data. These results and their applications provide a firm foundation to advance the number set H as a useful mathematical tool.

The term ‘Hallmarks of Cancer’ was coined by Hanahan and Weinberg in their influential reviews and they described genome instability as a property of cells enabling cancer development [1, 2]. Accurate DNA replication of genomes is central to diminish genome instability. Here, the understanding of the initiation of DNA synthesis in origins of DNA replication to start leading strand synthesis and the initiation of Okazaki fragment on the lagging strand are crucial to control genome instability. Recent findings have provided new insights into the mechanism of the remodelling of the prime initiation enzyme, DNA polymerase α-primase, during primer synthesis, how the enzyme complex achieves lagging strand synthesis, and how it is linked to replication forks to achieve optimal initiation of Okazaki fragments. Moreover, the central roles of RNA primer synthesis by Pol-prim in multiple genome stability pathways such as replication fork restart and protection of DNA against degradation by exonucleases during double-strand break repair is discussed.

Since certain Mycobacterium tuberculosis complex (MTBC) members, like M. bovis, are endemic in specific South African wildlife reserves and zoos, cases of clinically important nontuberculous mycobacteria (NTM) in wildlife may be neglected. Additionally, due to the inability of tests to differentiate between host responses to MTBC and NTM, the diagnosis of MTBC may be confounded by the presence of NTMs. This may hinder control efforts. These constraints highlight the need for enhanced rapid detection and differentiation methods for MTBC and NTM, especially in high MTBC burden areas. We evaluated the use of the GeneXpert MTB/RIF Ultra, the Hain CMdirect V1.0, and novel amplicon sequencing PCRs targeting the mycobacterial rpoB and ku gene targets, directly on antemortem respiratory samples from known MTBC-infected and NTM culture-positive African elephants (n=26 animals) and rhinoceros (n=23 animals). Our findings suggest that the Ultra is the most sensitive diagnostic test for MTBC DNA detection directly in raw antemortem respiratory specimens and that the rpoB PCR is ideal for Mycobacterium genus DNA detection and species identification through amplicon sequencing.

Maxwell equation for the electric field has been solved for any medium by suggesting the wavenumber and angular frequency be complex quantities. This accounts for the field decay by interaction with the medium.This expression for the time and special decay of the electric field in a medium is used to construct a new wave function sensitive to the medium physical properties. This new wave function, unlike the conventional one, differentiates between a beam of particles in a vacuum and that enters a medium which is an attenuated due to the scattering effect.Another expression for time decaying electric field was obtained using Newton’s laws for frictional medium. This expression shows that the electric field diminishes due to friction.Fortunately, this time decaying part of the electric field is typical to that derived from Maxwell’s equations. Finally, a new Schrodinger equation sensitive to the medium properties was derived. This equation, fortunately, describes some scattering processes for Protein scattering, scattering of x-rays, opto-acoustic phonons, and Raman scattering for some materials successfully .

Diffuse interstitial lung diseases (DILD) are a heterogeneous group of over 200 entities, some with dramatical evolution and poor prognostic. Because of their overlapping clinical, physiopathological and imagistic nature, successful management requires early detection and proper progression evaluation. This paper tests a complex networks (CN) algorithm for imagistic aided diagnosis fitness for the possibility of achieving relevant and novel DILD management data. 65 DILD and 31 normal high resolution computer tomography (HRCT) scans were selected and analyzed with the CN model. The algorithm is showcased in two case reports and then statistical analysis on the entire lot shows that a CN algorithm quantifies progression evaluation with a very fine accuracy, surpassing functional parameters’ variations. The CN algorithm can also be successfully used for early detection, mainly on the ground glass opacity Hounsfield Units band of the scan.

The COVID-19 pandemic has profoundly changed the world and human society in various ways. Infection-related figures are key indicators of the direct impact of the pandemic. In addition to the virus, many vulnerable populations (e.g. patients with complex health conditions) have suffered direct or indirect health impacts, such as delayed treatment or diagnosis of cancer and severe mental illness due to stay-at-home restrictions, or financial issues. Studying these kinds of impacts can provide the community with insights and understanding of how the pandemic has affected patients with health conditions and help inform decision-makers design policies that support various vulnerable populations. This paper surveys analytical work conducted on how COVID-19 has impacted patients with complex health conditions. We categorise vulnerable populations into three specific cohorts: patients with chronic disease, patients with cancer and patients with end-of-life care. We then investigate how each of these cohorts has been impacted by the pandemic. We also identify each cohort from an analytics perspective by leveraging various data collection strategies and analytical methods. The goals of this paper are to provide evidence on how to improve the quality of life for vulnerable populations and to inform a national response strategy for future pandemics, which seems inevitable in a highly globalised economy.

Immune complexes (ICs) made of antibody-bound antigens exhibit immunomodulatory activities exploitable in a vaccination strategy to optimize vaccine efficacy. The modulatory effects of ICs are typically attributed to the Fc fragments of the antibody components, which engage Fc receptors, complement and complement receptors on various immune cells. These Fc-mediated functions facilitate the critical interplay between innate and adaptive immune systems to impact the quality and quantity of the elicited adaptive responses. In addition to the Fc contribution, the Fab fragment also plays an immunoregulation role. The antigen-binding domains of the Fab fragment can bind their specific epitopes at high affinity to sterically occlude these antigenic sites from recognition by other antibodies. Moreover, the Fab-mediated binding have been demonstrated to induce allosteric alterations at nearby or distant antigenic sites. In this review article, we survey published studies to illuminate how the immunomodulatory functions of ICs have been investigated or utilized in a vaccination strategy to fight against an array of infectious pathogens, culminating with IC vaccine designs aimed at preventing HIV-1 infection. In particular, we highlight IC vaccine candidates that exploit Fab-mediated steric and allosteric effects to direct antibody responses away or toward the V1V2 domain, the V3 loop, and other antigenic sites on the HIV-1 envelope gp120 glycoprotein. Like other HIV-1 vaccine approaches, the path for IC-based vaccines to reach the clinic faces major hurdles yet to be overcome; however, investigations into this vaccine strategy have provided insights into the multifaceted activities of antibodies beyond their conventional roles in the host defense against HIV-1 and other microbial pathogens.

. This article presents, for the first time, the kinetics and the general conversion features of a 3-component system (A/B/N), based on proposed mechanism of Mau et al, for both free radical polymerization (FRP) of acrylates and the free radical promoted cationic polymerization (CP) of epoxides using various new copper complex (G2) as the initiator. Higher FRP and CP conversion can be achieved by co-additive of [B] and N, via the dual function of (i) regeneration [A], and (ii) generation of extra radicals. The FRP and CP conversion efficacy (CE) are proportional to the nonlinear power of bI[A][B], where b and I are the effective absorption coefficient and the light intensity, respectively. In the interpenetrated polymer network (IPN) capable of initiating both FRP and CP in a blend of TMPTA and EPOX, (as the monomer for FRP and CP, respectively), the synergic effects due to CP include:: (i) CP can increase viscosity limiting the diffusional oxygen replenishment, such that oxygen inhibition effects are reduced; (ii) the cationic monomer also acts as a diluting agent for the IPN network , and (iii) the exothermic property of the CP. Many new findings are explored via our analytical formuals include: (i) the CE of FRP is about twice of the CE of CP, due to the extra radicals involved in FRP; (ii) the catalytic cycle enhancing the efficacy is mainly due to the regenaration of the initiator, and (iii) the nonlinear dependence of light intensity of the CE (in both FRP and CP). For the first time, the catalytic cycle, synergic effects, and the oxygen inhibition are theoretically confirmed to support the experimental hypothesis. The measured results of Mau et al are well analyzed and matching the predicted features of our modeling. .

A severe flash flood hit Luwu, Sulawesi, Indonesia, on 13 July 2020. This flood was preceded by persistent heavy rainfall from 11 to 13 July 2020. In this study, we explore both the physical and dynamical processes that caused the heavy rainfall using a convection-permitting model with 1-km resolution. The heavy rainfall was modulated by the development of a pair of Mesoscale Convective Complexes (MCCs) during the night. The pair of MCCs was triggered by an anti-cyclonic vorticity anomaly over the Makassar Strait and was maintained by the warm front passing between the sea and land over central Sulawesi. This front was characterized by moist-warm and cold-dry low-level air, which may have helped to extend the lifetime of the MCCs. The northwestward propagation of the MCCs was due to the interaction between predominantly southeasterly monsoon and sea surface temperature anomalies.

It is widely recognized that public health interventions benefit from community engagement and leadership, yet there are challenges to evaluating complex, community-led interventions assuming hierarchies of evidence derived from laboratory experimentation and clinical trials. Particular challenges include, first, inconsistency of the intervention across sites; and second, absence of researcher control over the sampling frame and methodology. This report highlights these challenges as they played out in the evaluation of a community-organized health project in South London. The project aimed to benefit maternal mental health, health literacy and social capital, and especially to engage local populations known to have reduced contact with statutory services. We evaluated the project using two studies with different designs, sampling frames and methodologies. In one the sampling frame and methodology were under community control, permitting comparison of change in outcomes from before to after participation in the project. In the other, the sampling frame and methodology were under researcher control, permitting a case-control design. The two evaluations led to different results however: participants in the community-controlled study showed benefits, while participants in the researcher-controlled study did not. The principal conclusions are that while there are severe challenges to evaluating a community-led health intervention using a controlled design, measurement of pre-/post-participation changes in well-defined health outcomes should typically be a minimum evaluation requirement, and confidence in attributing causation of any positive changes to participation can be increased by use of interventions in the project and in the engagement process itself that have a credible theoretical and empirical basis.

From the formalism of the thermodynamics of irreversible processes and the theory of complex systems, characterization of longevity and aging and its relationship with the emergence and evolution of cancer was carried out. It was found that: 1. The rate of entropy production can be used as an index of robustness, plasticity, the aggressiveness of cancer, and as a measure of biological age; 2. The aging process, as well as the evolution of cancer, goes through what we have called “biological phase transition”; 3. The process of metastasis, which occurs through epithelial-mesenchymal transition (EMT), appears as a phase transition far from thermodynamic equilibrium and exhibits Shilnikov chaos-like dynamic behavior. This dynamic guarantees the robustness of the process and, in turn, its unpredictability; 4. It was shown that as the ferroptosis process is strengthened, the complexity of the dynamics associated with the emergence and evolution of cancer decreases. The theoretical framework developed contributes to a better understanding of the biophysical-chemical phenomena of longevity and aging and their relationship with cancer.

Mediterranean Ridge accretionary complex (MAC) is one of the most critical subduction zones in the world. It is known that the region exhibits a continuous mass change (horizontal/vertical movements). This process is associated with the devastating and tragic earthquakes shaking the MAC for centuries. Here, we investigate the ocean bottom pressure (OBP) anomalies in the MAC derived from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow On (GRACE-FO) satellite missions. The OBP time series for the MAC comprises a decreasing trend in addition to 1-, 1.53-, 2.36-, 3.67-, and 9.17-year periodic components partially explained by the atmosphere, oceans, and hydrosphere (AOH) processes, and Earth's pole movement. We noticed that the OBP anomalies appear to link to a rising trend and periods in earthquakes' power time series. This finding sheds new light on the mechanisms controlling the most destructive natural hazard.

Let f : V → V be a Cohomological Expanding Mapping¹ of a smooth complex compact homogeneous manifold with $ dim_{\mathbb{C}}(\Vc)=k \ge 1$ and Kodaira Dimension $\leq 0$. We study the dynamics of such mapping from a probabilistic point of view, that is, we describe the asymptotic behavior of the orbit $ O_{h} (x) = \{h^{n} (x), n \in \mathbb{N} \quad \mbox{or}\quad \mathbb{Z}\}$ of a generic point. Using pluripotential methods, we have constructed in our previous paper \cite{Armand4} a natural invariant canonical probability measure of maximal Cohomological Entropy $ \nu_{h} $ such that ${\chi_{2l}^{-m}} (h^m)^\ast \Omega \to \nu_h \qquad \mbox{as} \quad m\to\infty$ for each smooth probability measure $\Omega $ in $\Vc$ . We have also studied the main stochastic properties of $ \nu_{h}$ and have shown that $ \nu_{h}$ is a smooth equilibrium measure , ergodic, mixing, K-mixing, exponential-mixing. In this paper we are interested on equidistribution problems and we show in particular that $ \nu_{h}$ reflects a property of equidistribution of periodic points by setting out the Third and Fourth Main Results in our study. Finally we conjecture that $$\nu_h:=T_l^+ \wedge T_{k-l}^-,$$ $$\dim_\HH(\nu_h)= \Psi h_{\chi}(h) , $$ $$\dim_\HH( \mbox{Supp} T_l^+) \geq 2(k-l) + \frac{\log \chi_{2l}}{\psi_l},$$ $$|\langle \nu_m^x-\nu_h,\zeta\rangle|\leq M \Big[1+\log^+{1\over D(x,\Tc)}\Big]^{\beta/2}\|\zeta\|_{\Cc^\beta} \gamma^{-\beta m/2}$$ and $$|\langle \nu_m^x-\nu_h,\zeta\rangle|\leq M \Big[1 +\log^+{1\over D(x,E_\gamma)}\Big]^{\beta/2}\|\zeta\|_{\Cc^\beta} \gamma^{-\beta m/2}.$$

Let $f:V\rightarrow V $ be a Cohomological Expanding Mapping¹ of a smooth complex compact homogeneous manifold with dim_C(V) = k ≥ 1 and Kodaira Dimension $\leq 0$. We study the dynamics of such mapping from a probabilistic point of view, that is, we describe the asymptotic behavior of the orbit $ O_{f} (x) = \{f^{n} (x), n \in \mathbb{N} \quad \mbox{or}\quad \mathbb{Z}\}$ of a generic point. Using pluripotential methods, we construct a natural invariant canonical probability measure of maximum Cohomological Entropy $ \mu_{f} $ such that ${\chi_{2l}^{-m}} (f^m)^\ast \Omega \to \mu_f \qquad \mbox{as} \quad m\to\infty$ for each smooth probability measure $\Omega $ on V . Then we study the main stochastic properties of $ \mu_{f}$ and show that $ \mu_{f}$ is a measure of equilibrium, smooth, ergodic, mixing, K-mixing, exponential-mixing and the unique measure with maximum Cohomological Entropy. We also conjectured that $\mu_f:=T_l^+ \wedge T_{k-l}^-$, $\dim_\H(\mu_f)= \Psi h_{\chi}(f) $ and $\dim_\H( \mbox{Supp} T_l^+) \geq 2(k-l) + \frac{\log \chi_{2l}}{\psi_l}.$

In this paper we explore how we can use catchment resilience as a unifying concept to manage and regulate catchments, using structured reviews to support our perspective. River catchments are physical boundaries which delineate where all surface water (e.g. precipitation, snow, meltwater) falling on a piece of land runs off or flows to a single point at a lower elevation, where the river meets a larger body of water (e.g. sea, lake). Catchments are complex systems with interrelated natural, social, and technical aspects. The exposure, vulnerability, and resilience of these aspects (separately and in combination) are the latent conditions which when triggered by a specific hazard, result in catchment impacts. In complex catchment systems, resilience is the ability to bounce-back, the ability to absorb, and the ability to transform. When all three abilities are accounted for, we are forced to consider the interactions of the catchment system. Six main complexity concepts can be used to frame how we approach evaluating catchment resilience. These concepts are: natural-social-technical aspects, interactions, spatial scales, time scales, multiple forms of evidence, and uncertainty. In analysing these complexity concepts we have found that there are several gaps in current practice. For example critical interactions which need further methodological study are the linkages between the natural-social-technical realms, as well as across spatial scales (e.g. households or communities) and time scales (e.g. days or years). Requirements for future methodological approaches are suggested. Central to these is (1) the study of interactions linking the short- to medium-term time scales (2) better integration of bottom-up and top-down approaches, to link local context with higher-level decision-making, and (3) developing ‘hazard-agnostic’ methods which can address the impacts of floods, droughts – even acknowledging dormant ‘socio-technical hazards’. There is no ‘one size fits all’ approach to catchment resilience. Mixed method approaches are required and their selection will depend on contextual issues identified early in the process for specific catchments. Central to any effective approach is the incorporation of a linking systems or interaction analysis, which draws together the natural-social-technical system in a meaningful way. If our approaches do not begin to acknowledge the interdependencies and interactions, we may miss substantial opportunities to enhance catchment resilience.

. This article presents, for the first time, the kinetics and the general features of a photopolymerization system (under visible light) G1/ Iodonium/ TEA/gold chloride (or A/B/N/G), having initial concentrations of A0, B0, N0 and G0, based on the proposed mechanism of Tar et al. Analytic formulas are developed to explore the new features including: (i) both FRP efficacy and the production of nanogold (NG) are proportional to the relative concentration ratios of (A0+B0+N0)/G0, which may be optimized for maximum efficacy; (ii) the two competing procedure of NG production and efficacy of free radical photopolymerization (FRP) can be tailored for optimal system with nanogold in the polymer matrix;(ii) the FRP efficacy is contributed by 3 components: the coupling of the excited state of copper complex (T) with the radicals (R and S) produced by the iodonium and the amine; (iii) the production of NG is contributed by 2 components: the coupling of T and radical (S) with gold ion; (iv) NG production has a transient state value which is an increasing function of light intensity and the combined concentration ratio [(A0/G0)+(N0/(K'M0). whereas it has a steady-state independent to the light intensity.

The Burkholderia cepacia complex (Bcc) are a group of increasingly multi-drug resistant opportunistic bacteria that can cause severe pulmonary infections. This resistance is driven through a combination of intrinsic factors and the carriage of a broad range of conjugative plasmids harbouring virulence determinants. Therefore, novel treatments are required to not only treat Bcc infection but also to prevent further spread of these virulence determinants. In the search for phages infective for two clinical Bcc isolates, CSP1 phage, a PRD1-like phage was isolated. CSP1 phage was found to require pilus machinery commonly encoded on conjugative plasmids to facilitate infection of multiple Gram-negative bacteria genera including Escherichia and Pseudomonas. Whole genome sequencing and characterisation of one of the clinical Burkholderia isolates revealed it to be Burkholderia contaminans. B. contaminans 5080 was found to contain a genome of over 8 Mbp encoding multiple intrinsic resistance factors, such as efflux pump systems, but more interestingly, carried three novel plasmids encoding multiple putative virulence factors for increased host fitness, including antimicrobial resistance. Even though PRD1-like phages are broad host range, their use in novel antimicrobial treatments shouldn’t be dismissed, as the dissemination potential of conjugative plasmids is extensive. Continued survey of clinical bacterial strains is

According to the current European and Italian scenario related to urban re-generation, cultural and landscape heritage, valorisation is being also enhanced by the activation of innovative processes. These involve the development of methodologies and tools that are able to address decision-making processes among low entropy economy, complex values and creative practices. In this perspective, the research aims to investigate the possibilities of developing a Cultural Heritage Low Entropy Enhancement (CHLEE) approach by considering how the complex values of cultural heritage can vary not only through a physical transformation of spaces but also through a program of uses and activities able to produce new values, where the human experience is essential. This type of model modifies the objectives that characterise the valorisation of cultural heritage and landscape, recognising that the fruition is no longer “consumerist” but “experiential”. A crucial role is represented by the heterogeneity of creative practices that contribute to the identificationidentifying and implementation ofimplementing innovative management and governance models. The present paper explores the components of creative regenerative processes, based upon the ex-post evaluation of some Italian experiments, across the PROMETHEE-GAIA multi-criteria method, to understand how creative experiences are building innovation ecosystem thanks to low entropy economy and improve the ex-ante evaluation for new strategies and policies.

The connection of two phenomena - non-conservative friction forces and dissipation-induced instability can lead to many interesting engineering problems. The paper studies general material-dependent damping influence on dynamical instability of disc brake systems leading to brake squeal. The effect of general damping is demonstrated on a minimal and complex model of a disc brake. A complex system including material-dependent damping is defined in the commercial finite element software. The finite element model validated by experimental data on the brake-disc test bench is used to compute the influence of a pad and a disc damping variations on system stability by complex eigenvalue analysis. Analyzes show a significant sensitivity of the experimentally verified unstable mode of the system to the ratio of the damping between the disc and the friction material components.

Background: Traumatic events adversely affect the clinical course of obsessive-compulsive disorder (OCD). Our investigation explores the correlation between prolonged interpersonal trauma and the severity of symptoms related to obsessive-compulsive and anxiety disorders. Methods: The study follows a cross-sectional and observational design, employing the International Trauma Questionnaire (ITQ) to examine areas linked to interpersonal trauma, the Hamilton Anxiety Rating Scale (HAM-A), and the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) to assess anxious and obsessive-compulsive symptoms, respectively. Descriptive analysis, analysis of variance (ANOVA), and logistic regression analyses were conducted. Results: We recruited 107 OCD-diagnosed patients, categorizing them into subgroups based on the presence or absence of complex post-traumatic stress disorder (cPTSD). The ANOVA revealed statistically significant differences between the two groups in the onset age of OCD (p=0.083), psychiatric familial history (p=0.023), HAM-A, and Y-BOCS (p=0.000). Logistic regression indicated a statistically significant association between the presence of cPTSD and Y-BOCS scores (p=0.000). Conclusion: The coexistence of cPTSD in OCD exacerbates obsessive-compulsive symptoms and increases the burden of anxiety. Further advancements in this field are crucial for mitigating the impact of early trauma on the trajectory of OCD and associated anxious symptoms.

Sepsis is a major health problem and accounts for 20 per cent of deaths worldwide. It is the most expensive condition treated in United States hospitals at $27 billion per year or about $20,000 per patient. Treatment consisting largely of fluid resuscitation and antibiotics has only marginal impact. Mortality is about 27 per cent for hospitalized patients and about 42 per cent for patients in intensive care.There are two phases of sepsis – a hyper inflammatory phase and a subsequent hypo inflammatory phase.During the hyper inflammatory phase the metabolic rate increases associated with an increase in body temperature and a rapid escalation of immune system functioning including increased numbers of leucocytes and migration of those leucocytes to infected and damaged tissues and an increased supply and consumption of glucose to fuel this immune system.During the subsequent hypo inflammatory phase the metabolic rate declines and this is associated with a decrease in body temperature and a generalized decrease in the physiological activity of many organs including the immune system akin to hibernation. The activated immune system has priority for the available glucose over most other organs and physiological functions during such potentially life threatening circumstances. Thus adenosine triphosphate (ATP) production by mitochondria (the source of energy at the cellular level for the organism as a whole) also has a lower priority for the available glucose relative to the activated immune system. If glucose availability is threatened then mitochondrial production of ATP is partially or substantially suppressed in favor of glycolysis because glycolysis can rapidly produce large quantities of ATP that are necessary for immune cell function in infected, anaerobic, ischemic, or damaged tissues.However, glycolysis is only a temporary fix as it cannot produce the quantities of ATP necessary on an ongoing basis for the normal functioning of the healthy animal. Mitochondrial production of ATP must be recommenced for full recovery.It appears that the partial or substantial suppression of mitochondrial production of ATP by activation of the immune response becomes relatively fixated in some patients leading to a substantial ATP deficit. This is the fundamental issue of sepsis.This paper reviews the metabolism of glucose and insulin during sepsis and concludes that high dose insulin with mild hyper glycaemia in conjunction with the intravenous administration of thiamine, an inhibitor of the pyruvate dehydrogenase kinase enzymes, to re-establish physiological ATP production by mitochondria, administered early in the hypo metabolic (hypo inflammatory) phase of sepsis should significantly improve survival.

A significant number and range of challenges besetting sustainability can be traced to the actions and interactions of multiple autonomous agents (people mostly) and the entities they create (e.g., institutions, policies, social network) in the corresponding social-environmental systems (SES). To address these challenges, we need to understand decisions made and actions taken by agents, the outcomes of their actions, including the feedbacks on the corresponding agents and environment. The science of Agent-based Complex Systems—ACS science—has a significant potential to handle such challenges. The advantages of ACS science for sustainability are addressed by way of identifying the key elements and challenges in sustainability science, the generic features of ACS, and the key advances and challenges in modeling ACS. Artificial intelligence and data science promise to improve understanding of agents’ behaviors, detect SES structures, and formulate SES mechanisms.

To prevent CO2 leakage and ensure the safety of long-term CO2 storage, it is essential to investigate the flow mechanism of CO2 in complex pore structures at the pore scale. This study focuses on reviewing the experimental, theoretical, and numerical simulation studies on the microscopic flow of CO2 in complex pore structures during the last decade. For example, advanced imaging techniques, such as X-ray computed tomography (CT) and nuclear magnetic resonance (NMR), are used to reconstruct the complex pore structures of rocks. Mathematical methods, such as Darcy's law, Young–Laplace’s law, and the Navier-Stokes equation, are used to describe the microscopic flow of CO2. Numerical methods, such as the lattice Boltzmann method (LBM) and pore network (PN) model, are used for numerical simulation. The application of these experimental and theoretical models and numerical simulation studies is discussed, considering the effect of complex pore structures. Finally, future research is suggested to focus on: (1) Conducting real-time CT scanning experiments of CO2 displacement combined with the developed real-time CT scanning clamping device to realize real-time visualization and provide quantitative description of the flow behavior of CO2 in complex pore structures; (2) The effect of pore structures change on the CO2 flow mechanism caused by the chemical reaction between CO2 and the pore surface, the flow theory of CO2 considering wettability and damage theory in a complex pore structures; (3) The flow mechanism of multi-phase CO2 in complex pore structures; (4) The flow mechanism of CO2 in the pore structures at multiscale and the scale upgrade from microscopic to mesoscopic to macroscopic. Generally, this study focuses on reviewing the research progress of CO2 flow mechanisms in complex pore structures at the pore scale and affords an overview of potential advanced developments to enhance the current understanding of CO2 microscopic flow mechanisms.

As a candidate for bifunctional asymmetric catalysts containing a half-sandwich C–N chelating Ir(III) framework (azairidacycle), a dinuclear Ir complex with an axially chiral linkage is newly designed. An expedient synthesis of chiral 2,2’-bis(aminomethyl)-1,1’-binaphthyl (1) from 1,1-bi-2-naphthol (BINOL) was accomplished by a three-step process involving nickel-catalyzed cyanation and subsequent reduction with Raney-Ni and KBH4. The reaction of (S)-1 with an equimolar amount of [IrCl2Cp*]2 (Cp* = 5-C5(CH3)5) in the presence of sodium acetate in acetonitrile at 80 °C gave a diastereomeric mixture of new dinuclear dichloridodiiridium (5) through the double C–H bond cleavage, as confirmed by 1H NMR spectroscopy. A loss of the central chirality on the Ir centers of 5 was demonstrated by treatment with KOC(CH3)3 to generate the corresponding 16e amidoiridium complex 6. The following hydrogen transfer from 2-propanol to 6 provided diastereomers of hydrido(amine)iridium with retaining the bis(azairidacycle) architecture. The dinuclear chlorido(amine)iridium 5 can serve as a catalyst precursor for the asymmetric transfer hydrogenation of acetophenone with a substrate to catalyst ratio of 200 in the presence of KOC(CH3)3 in 2-propanol, leading to (S)-1-phenylethanol with up to 67% ee.

A Invasive emerging pollutants from wastewater effluent discharge, such as dyes, pesticides, etc., pose a serious threat to the ecosystem. Advanced oxidation processes (AOPs) under visible light irradiation have emerged as a promising technology to overcome toxic and recalcitrant organic compounds. In this work, the impact of operational factors, including the concentration of Fe3+ or Fe2+, [H2O2], the molar ratio (Oxalate/ Fe3+ or Fe2+), and the initial pH, was studied to obtain high efficiency in the degradation and mineralization of such a food dye to reduce their pollution. The study deals with the comparison of the efficiency of UV, LED, and sunlight irradiation on the photocatalytic degradation of the dye using Fe3+/Lig and Fe2+/Lig complexes. The results showed that sunlight irradiation gave a very rapid kinetic and higher degradation efficiency of over 70%. The optimized conditions for the maximum elimination of the dye with a photocatalytic degradation efficiency (98%) and a mineralization rate of 96% were obtained with the Fe3+/Lig complex, based on the Box Benhken surface design analysis. In the presence of H2O2, the degradation reached an equilibrium stage after 15 min (97.57%) for the Fe(III)/Lig system. Moreover, the inhibition effect of inorganic ions on the photo-Fenton performance of Fe3+/Lig and Fe2+/Lig was studied. The study suggests that the use of nanocrystals of hematite as a Fenton reagent for treating textile effluents needs further investigation. The results showed that the proposed models were well-suited to batch treatment under sunlight. This study not only proposes a Fe3+/Lig and Fe2+/Lig system for the elimination of a food dye without adjusting the pH of the medium, but it also provides insight into the best source of light irradiation for the photocatalytic degradation process.

The Golgi complex (GC) dysfunctions in Parkinson’s Disease (PD), neurodevelopmental disorders (NDDs), cancer, and organelle structural biology (OSB) can provide insights into therapeutic targets, gene therapy, and drug design. Primary defects and fragmentation within the GC are implicated in a wide range of neurodegenerative diseases. GC defects typically result in mislocation of proteins, accumulation of undegraded proteins, and impaired glycosylation of proteins. Inhibition of vesicular trafficking by α-synuclein (aSyn) may affect the dopamine-producing neurons and neuromodulators. GC regulates apoptosis during pathological mechanisms of neurological diseases and could provide new avenues in treatments through translation research. PD patients bearing the hereditary E46K disease mutation manifest the clinical picture of parkinsonism. How do we provide high resolution nanoimages of the GC during disease to capture dysfunction? Could we visualize the aSyn traffic jam between vesicles in the organelles ER and GC? OSB is emerging as a field as more technology advances and is more accessible. Structural studies of the GC will advance the field of neurological disease forward with an in depth understanding of dysfunction, fragmentation, and defects. Discoveries of the GC in PD, NDDs, and cancer would break new ground and provide translational medicine data of these diseases. Future research could be visualizing high angle annular dark field-STEM (HAADF-STEM) tomograms, cryogenic electron tomography (cryo-ET), multiplex correlative light and electron microscopy (cryo-CLEM), nanobody-assisted tissue immunostaining for volumetric EM (NATIVE) and using soft X-ray tomography (SXT) and computational reconstruction of the GC.

unlike the volume, the expression for the surface area of a regular conoid has not yet been obtained by means of direct integration or a differential geometry procedure. As this non-developable form is relatively used in engineering, the difficulty to determine its surface, represents a serious shortcoming for several problems which arise in radiative transfer, lighting and construction, to cite just a few. In order to solve the problem, I conceived the surface as a set of linearly dwindling ellipses which remain parallel to a circular directrix, a typical problem appears when searching the length of such ellipses. I employed a new procedure which, in principle, consists in dividing the surface into infinitesimal elliptic strips to which we have successively applied Ramanujan’s second approximation for the longitude of the ellipse. In this manner, we can obtain the perimeter of any transversal curve pertaining to the said form as a function of the radius of the directrix and the position of the ellipse’s center on the X-axis. Integrating the so-found perimeters of the differential strips for the whole span of the conoid, an unexpected solution emerges through the newly found number psi (ψ) which seems like a refined approximation to the third decimal of Pi but derived from a definite integral equation. As the strips are in truth slanted in the symmetry axis, their width is not uniform and we need to perform some adjustments in order to complete the problem with sufficient precision, but this is discussed separately in the annexes. Relevant implications for mathematical symmetry applied to multifarious architectural and engineering forms can be derived from this finding

Antimicrobial use in agriculture has been identified as an area of focus for reducing overall antimicrobial use and improving stewardship. In this paper, we outline the design of a complex antimicrobial stewardship (AMS) intervention aimed at developing a national Veterinary Prescribing Champion programme for Welsh farm animal veterinary practices. We describe the process by which participants were encouraged to design and deliver bespoke individualised AMS activities at practice level by forging participant ‘champion’ identities and Communities of Practice through participatory and educational online activities. We describe the key phases identified as important when designing this complex intervention, namely (i) involving key collaborators in government and industry to stimulate project engagement; (ii) grounding the design in the literature, the results of stakeholder engagement, expert panel input and veterinary clinician feedback to promote contextual relevance and appropriateness; and (iii) taking a theoretical approach to implementing intervention design to foster critical psychological needs for participant motivation and scheme involvement. With recruitment of over 80% of all farm animal practices in Wales to the programme, we also describe demographic data of the participating Welsh Veterinary Prescribing Champions in order to inform recruitment and design of future AMS programmes.

We theoretically study the dynamical Casimir effect (DCE), i.e., parametric amplification of a quantum vacuum, in an optomechanical cavity interacting with a photonic crystal, which is considered to be an ideal system to study the microscopic dissipation effect on the DCE. Starting from a total Hamiltonian including the photonic band system as well as the optomechanical cavity, we have derived an effective Floquet-Liouvillian by applying the Floquet method and Brillouin-Wigner-Feshbach projection method. The microscopic dissipation effect is rigorously taken into account in terms of the energy-dependent self-energy. The obtained effective Floquet-Liouvillian exhibits the two competing instabilities, i.e., parametric and resonance instabilities, which determine the stationary mode as a result of the balance between them in the dissipative DCE. Solving the complex eigenvalue problem of the Floquet-Liouvillian, we have determined the stationary mode with vanishing values of the imaginary parts of the eigenvalues. We find a new non-local multimode DCE represented by a multimode Bogoliubov transformation of the cavity mode and the photon band. We show the practical advantage for the observation of DCE in that we can largely reduce the pump frequency when the cavity system is embedded in a narrow band photonic crystal with a bandgap.

Antibiotics have become a widely used drug classes worldwide. Its indiscriminate use in the clini-cal-hospital environment ended up causing antibiotic-resistance genes. Pharmaceutical technology is an essential ally for new formulation development in the antibacterial field. Cyclodextrins (CDs) are ap-proaches that can potentially improve the effectiveness of antibacterial drugs. Thus, this study aimed to review experimental models using CDs as inclusion complexes to improve antibacterial drugs’ physi-cochemical characteristics and biological activities. The review was carried out using the three online journals database PubMed, Scopus, and Embase, limited to Medical Subjects Headings Index. The search protocol was registered in the Open Science Framework database. The following terms and their com-binations were used: cyclodextrins and antibacterial agents in title or abstract, and a total of 1580 studies were identified in a period up to October 2022. Finally, 27 articles were selected for discussion in this review. The biological results reveal that the antibacterial effect of the compounds, complexed with CDs, was extensively improved when compared to the free drugs. CDs can improve the therapeutic effects of antibiotics, already existing on the market, natural products, and synthetic molecules. Therefore, these inclusion complexes using CDs increase the new pharmaceutical products development for clinical ap-plication.

Apple replant disease is a severe problem in orchards and tree nurseries. Evidence for the involvement of a nematode-microbe disease complex was reported. To search for this complex, plots with a history of apple replanting, and control plots cultivated for the first time with apple were sampled in two fields in two years. Shoot weight drastically decreased with each replanting. Nematodes were extracted from soil samples by floatation-centrifugation, washed on a 20 µm-sieve, and used for DNA extraction. Nematode communities and co-extracted fungi and bacteria were analyzed by high-throughput sequencing of amplified ribosomal fragments. The nematode community and co-extracted fungal and bacterial communities significantly differed between replanted and control plots. Free-living nematodes of the genera Aphelenchus, Cephalenchus, and an unidentified Dorylaimida were associated with replanted plots, as indicated by linear discriminant analysis effect size. Among the co-extracted fungi and bacteria, Mortierella was most indicative of replanting. Some genera, mostly Rhabditis, indicated healthy control plots. Isolating and investigating the putative disease complexes will help to understand and alleviate stress-induced root damage of apple in replanted soil.

Our earlier work has tentatively shown that the hierarchy of fermion masses and mixing angles follows from the universal behavior of nonlinear dynamics. In this brief sequel we survey a similar scenario in which the Cabibbo angle arises from the nonlinear dynamics of charged-current interactions.

To characterize the mechanisms by which the highly-conserved exocyst trafficking complex regulates eye physiology in zebrafish and mice, we focused on exoc5 (aka sec10), a central exocyst component. We analyzed both exoc5 zebrafish mutants and retinal pigmented epithelium (RPE)-specific Exoc5 knockout mice. Exoc5 is present in both the non-pigmented epithelium of the ciliary body and in the RPE. In this study we set out to establish an animal model to study the mechanisms underlying the ocular phenotype and to establish if loss of visual function is induced by postnatal RPE Exoc5-deficiency. Exoc5-/- zebrafish showed smaller eyes, with decreased number of melanocytes in the RPE and shorter photoreceptor outer segments. At 3.5 days post fertilization, loss of rod and cone opsins were observed in zebrafish Tg:exoc5 mutants. Mice with postnatal RPE-specific loss of Exoc5 showed retinal thinning associated with compromised visual function, and loss of visual photoreceptor pigments. This retinal phenotype in Exoc5-/- mice was present at 20-weeks, and the phenotype was more severe at 27-weeks, indicating progressive disease phenotype. We previously showed that the exocyst is necessary for photoreceptor ciliogenesis and retinal development. Here, we report that exoc5 mutant zebrafish and mice with RPE-specific genetic ablation of Exoc5 develop abnormal RPE pigmentation, resulting in retinal cell dystrophy and loss of visual pigments associated with compromised vision. As RPE cells are “downstream” of photoreceptor cells in the visual process, these data suggest exocyst-mediated retrograde communication and dependence between the RPE and photoreceptors.

Craniofacial neuropathic pain affects millions of people worldwide and is often difficult to treat. Two key mechanisms underlying this condition are a loss of the negative control exerted by inhibitory interneurons and an early microglial reaction. Basic features of these mechanisms, however, are still poorly understood. Using the chronic constriction injury of the infraorbital nerve (CCI-IoN) model of neuropathic pain in mice, we have examined the changes in the expression of GAD, the synthetic enzyme of GABA, and GlyT2, the membrane transporter of glycine, as well as the microgliosis that occur at early (5 days) and late (21 days) stages post-CCI in the medullary and upper spinal dorsal horn. Our results show that CCI-IoN induces a down-regulation of GAD at both postinjury survival times, uniformly across the superficial laminae. The expression of GlyT2 showed a more discrete and heterogeneous reduction due to the basal presence in lamina III of ‘patches’ of higher expression, interspersed within a less immunoreactive ‘matrix’, which showed a more substantial reduction in the expression of GlyT2. These patches coincided with foci lacking any perceptible microglial reaction, which stood out against a more diffuse areas of strong microgliosis. These findings may provide clues to better understand the neural mechanisms underlying allodynia in neuropathic pain syndromes.

Sacrococcygeal pilonidal disease is a chronic inflammatory condition with an incidence of 26:100,000 in the United States. However, its etiology and optimal treatment remain controversial. We included 129 and 74 patients with simple and complex sacrococcygeal pilonidal disease, respectively. The primary outcome was pilonidal sinus recurrence after unroofing curettage. Secondary outcomes were pain scores, time to return to work/school, and time to complete recovery. At a median follow-up of 53 months, the recurrence rate was 4.9% in all patients, not significantly higher in subjects with the complex disease. Duration of surgery (15.4 vs. 12.2 min), time to return to school/work (9.8 vs. 7.7 days), and complete healing time (44 vs. 36 days) were longer in patients with the complex disease. Postoperative complication rates, pain scores, and quality of life scores between the two groups did not differ. Unroofing curettage may be a good first-choice treatment for both simple and complex sacrococcygeal pilonidal disease.

Pericentromeric regions of chromosomes enriched in tandemly repeated satellite DNA although representing a significant part of eukaryotic genomes are still understudied mainly due to interdisciplinary knowledge gaps. Recent studies suggest their important role in genome regulation, karyotype stability and evolution. Thus, the idea of satellite DNA as a junk part of the genome was refuted. Integration of data about molecular composition, chromosome behaviour and details of in situ organization of pericentromeric regions is of great interest. The objective of this work was a cytogenetic analysis of the interactions of pericentromeric regions non-homologous chromosomes in mouse spermatocytes using immuno-FISH. We analysed two events: the associations between cerntomeric regions of X chromosome and autosomes, and associations between centromeric regions of autosomal bivalents forming chromocenters. We conclude that X chromosome form temporary synaptic associations with different autosomes in early meiotic prophase I which normally can be found at pachytene-diplotene without signs of pachytene arrest. These associations are formed between the satellite DNA-enriched centomeric regions of X chromosome and different autosomes but not involve the satellite-poor centromeric region of Y-chromosome. We suggest the mechanism of X chromosome competitive replacement from such associations during synaptic correction. We showed that centromeric region of the X chromosome remains free of γH2Ax-dependent chromatin inactivation, while Y chromosome is completely inactivated. This findings highlights the predominant role of associations between satellite DNA-enriched regions of different chromosomes including X. We assume that X-autosome temporary associations is a manifestation of an additional synaptic disorders checkpoint. These associations are normally corrected before the late diplotene. We revealed that the intense spreading conditions applied to the spermatocytes I nuclei did not lead to destruction of stretched chromatin fibers i.e. elongated chromocenters enriched in satellite DNA. Revealed by us tight associations between pericentromeric regions of different autosomal bivalents and X chromosome may represent the basis for repeat stability maintenance in autosomes an X chromosome. The consequences of our findings are discussed. We obtained the preparations of mouse spermatocytes nuclei in the meiotic prophase I using two approaches: standard and extremely intense surface spread techniques. Using immuno-FISH we visualized tandemly repeated mouse Major and Minor satellite DNA located in the pericentromeric regions of chromosomes and performed a morphological comparison of the standard- and intensely spreaded meiotic nuclei. Based on our results, we assume the remarkable strength of the chromocenter-mediated associations, “chromatin “bridges”, between different bivalents at the pachytene and diplotene stages. We have demonstrated that the chromocenter “bridges” between the centromeric ends of meiotic bivalents are enriched in both tandemly repeated Major and Minor satellite DNA. Association of centromeric regions of autosomal bivalents and X-chromosome but not with Y-chromosome correlates with the absence of Major and Minor satellites on Y-chromosome. We suggest that revealed tight associations between pericentromeric regions of bivalents may represent the network-like system providing dynamic stability of chromosomal territories, as well as add new data for the hypothesis of ectopic recombination in these regions which supports sequence homogeneity between non-homologous chromosomes and does not contradict the meiotic restrictions imposed by the crossing-over interference near centromeres. We conclude that nuclear architecture in meio-sis may play an essential role in contacts between the non-homologous chromosomes providing the specific characteristics of pericentromeric DNA.

The following series of Articles about a contextual system-theory, with focus on biological systems, shall give a guideline of how to explore complex systems. It is written not only for scientists, and therefore I will try to describe part of the way of understanding as an intuitive approach. This approach will also help scientists to get a deeper understanding of complexity. Some definitions and rules may seem at first simple and obvious. If practiced in a multidimensional complex system, one will see the difficulties. Even without mathematization or computer modeling the multidimensional sub space, which we try to describe phenomenologically for approaching the understanding of this Subsystem, will need a lot of training. Easily we get lost in the multidimensional world. Some of the chapters here and in the following publications of this series are written for specialists, but it will always come back to the essence of a phenomenological description. Concepts like Symbolic programming, Object oriented modeling, simulation and optimizing as well as experimental and mathematical approaches are the described tools to unpuzzle a complex scenario.

Kaposi’s sarcoma-associated herpesvirus (KSHV) is the etiologic agent of Kaposi’s sarcoma, primary effusion lymphoma (PEL) and multicentric Castleman’s disease. During KSHV lytic infection, lytic-related genes, categorized as immediate-early, early, and late genes, are expressed in a temporal manner. The transcription of late genes requires the virus-specific pre-initiation complex (vPIC), which consists of viral transcription factors. However, the characterization of the protein-protein interactions of the vPIC factors has not been completely elucidated. KSHV ORF18 is one of the vPIC factors, and its interaction with other viral factors has not been sufficiently revealed. Here, we analyzed the interaction between ORF18 and another vPIC factor, ORF30, in living cells using the bimolecular fluorescence complementation (BiFC) assay. We identified four amino-acid residues (Leu29, Gln36, His41 and Trp170) on ORF18 that were responsible for its interaction with ORF30. The artificial intelligence (AI) system AlphaFold2 predicted that identified four residues are exposed to the surface of ORF18 and located in proximity to each other in the surface of ORF18. Thus, AI-predicted model supports the importance of four residues for binding of ORF18 to ORF30. Our results indicated that wet experiments in combination with AI may enhance the structural characterization of vPIC protein-protein interactions.

All vaccines exhibit specific and nonspecific effects. Specific effects are shown by the efficacy against the target pathogen, while nonspecific effects can be detected by the change in all-cause mortality. The real-world non-COVID-19 all-cause mortality (NCACM) data for the population of England between January 2021 and May 2023 was assessed. All vaccines administered were based on the original Wuhan antigen. Each gender and age group, along with COVID-19 variant shows its own unique NCACM vaccination benefit/disbenefit time profile. The efficacy of COVID-19 vaccination against COVID-19 disease/death per se is undisputed, however, the nonspecific outcomes of COVID–19 vaccination is far more nuanced than have been widely appreciated. This confirms an earlier study on the unanticipated nonspecific effects of influenza vaccination against all-cause winter mortality. Interestingly, a high proportion of NCACM beneficial effects occurred during the first 21 days following COVID-19 vaccination, while the worst example of increased NCACM occurred during the fourth dose of COVID-19 vaccination in 19–40-year-olds for the interval &gt;21 days post vaccination which led to NCACM 3- to 10-times higher than in the unvaccinated. By the time of the Omicron variant, NCACM outcomes in those aged 90+ are mostly adverse. The beneficial nonspecific effects of COVID-19 vaccination increase with age and reach their maximum effect during the second week post vaccination for age groups below 50 years, rising to during the third week for those aged 70+. Finally, we discuss the mechanisms by which COVID-19 vaccination could induce wider nonspecific effects. Most of these mechanisms seem to depend on gene regulation by noncoding RNAs which also interact with mRNAs. We suggest that further international studies are required to discern the nonspecific NCACM effects of the different COVID-19 variants other than the three variants prevalent in the UK, and different types/manufacturer of COVID-19 vaccines which have been employed around the world. We can only speculate regarding the nonspecific effects of the COVID-19 vaccines administered to persons with an asymptomatic infection, and during vaccine waning. Vaccines not only need to be effective against the target pathogen, as primarily determined by antibody production, but need to minimize any unanticipated adverse nonspecific effects against all-cause mortality.

The microbiota–gut–brain axis has garnered increasing attention in recent years for its role in various health conditions, including neuroinflammatory disorders like complex regional pain syndrome (CRPS). CRPS is a debilitating condition characterized by chronic neuropathic pain, and its etiology and pathophysiology remain elusive. Emerging research suggests that alterations in the gut microbiota composition and function could play a significant role in CRPS development and progression. Our paper explores the implications of microbiota in CRPS and the potential therapeutic role of boron (B). Studies have demonstrated that individuals with CRPS often exhibit dysbiosis, with imbalances in beneficial and pathogenic gut bacteria. Dysbiosis can lead to increased gut permeability and systemic inflammation, contributing to the chronic pain experienced in CRPS. B, an essential trace element, has shown promise in modulating the gut microbiome positively and exerting anti-inflammatory effects. Recent preclinical and clinical studies suggest that B supplementation may alleviate neuropathic pain and improve CRPS symptoms by restoring microbiota balance and reducing inflammation. Our review highlights the complex interplay between microbiota, inflammation, and neuropathic pain in CRPS and underscores the potential of B as a novel therapeutic approach to target the microbiota–gut–brain axis, offering hope for improved management of this challenging condition.

Humanity faces serious social and environmental problems, including climate change and biodiversity loss. Risks are increasing and conditions deteriorating. Increasingly, scientists, global policy experts, and the general public conclude that incremental approaches are insufficient and transformative change is needed across all sectors of society. However, the meaning of transformation is still unsettled in the literature, as is the proper role of science in fostering it. This paper is the first in a three-part series that adds to the discussion by proposing a novel science-driven research-and-development program aimed at societal transformation. More than a proposal, it offers a perspective and conceptual framework from which societal transformation might be approached and understood. While acknowledging the necessity of reform to existing societal systems (e.g., governance, economic, and financial systems), the focus of the series is on transformation understood as systems change or systems migration—the de novo development of and migration to new societal systems. The series provides definitions, aims, reasoning, worldview, and a theory of change, and discusses fitness metrics and design principles for new systems. This first paper proposes a worldview built using ideas from evolutionary biology, complex systems science, cognitive sciences, and information theory that is intended to serve as the foundation for the R&amp;D program.

In this paper, we prove some common fixed point theorems on complex partial metric space. The presented results gener- alize and expand some of the literature well-known results. We also explore some of the application of our key results.

Since 2020 COVID-19 has caused serious mortality around the world. Given the ambiguity in es-tablishing COVID-19 as the direct cause of death we first investigate the effects of age and sex upon all-cause mortality during 2020 and 2021 in England and Wales. Since infectious agents have their own unique age profile for death, we explore several methods to adjust single year of age deaths in England and Wales during 2019 (the pre-COVID-19 base year) to a pathogen-neutral single year of age baseline. This adjusted base year is then used to confirm the widely reported higher deaths in males for most ages above 43 years in both 2020 and 2021. During 2020 (+ COVID-19 but no vac-cination) both male and female population-adjusted deaths were significantly increased above age 35. A significant reduction in all-cause mortality among both males and females aged 75+ could be demonstrated in 2021 during widespread COVID–19 vaccination, however, below age 75 deaths progressively increased. This finding arises from a mix of vaccination and year of age profiles of deaths for the different SARS-CoV-2 variants. In addition, specific effects for age around puberty were demonstrated where females had higher deaths rather than males. There is evidence that year-of-birth cohorts may also be involved, indicating that immune priming to specific pathogen outbreaks in the past may lead to lower deaths for some birth cohorts. To specifically identify the age profile for the COVID-19 variants in 2020 to 2023, we employ the proportion of total deaths at each age which are potentially due to or ‘with’ COVID-19. The original Wuhan strain, and the Alpha variant show somewhat limited divergence in the age profile with the Alpha variant shifted to a moderately higher proportion of deaths below age 84. The Delta variant specifically targeted persons below age 65. The Omicron variants showed significantly lower proportion of overall mortality, with markedly higher relative proportion of deaths above age 65 steeply increasing with age to a maximum around 100 years of age. A similar age profile for the variants can be seen in the age-banded deaths in US states – although slightly obscured by using age bands rather than single year of age. However, the US data shows that higher male deaths are greatly dependent on age and the COVID-variant. Deaths determined as ‘due to’ COVID-19 (as opposed to ‘involving’ COVID-19) in England and Wales were especially over-estimated in 2021 relative to the change in all-cause mortality. This arose as a by-product of an increase in COVID-19 testing capacity in late 2020. Potential structure-function mechanisms for the year of age specificity of SARS-CoV-2 var-iants are discussed. The question is posed as to whether vaccines based on different variants carry the specific age profile through into the vaccine.