Recurrent neural networks (RNNs) transmit information over time through recurrent connections. In contrast, biological neural networks use many other temporal processing mechanisms. One of these mechanisms is the inter-neuron delays caused by varying axon properties. Recently, this feature was implemented in echo state networks (ESNs), a type of RNN, by assigning spatial locations to neurons and introducing distance-dependent inter-neuron delays. These delays were shown to significantly improve ESN task performance. However, thus far it is still unclear why distance-based delay networks (DDNs) perform bettern than ESNs. In this paper, we show that by optimizing inter-node delays, the memory capacity of the network matches the memory requirements of the task. As such, networks concentrate their memory capabilities to the points in the past which contain the most information for the task at hand. Moreover, we show that DDNs have more total linear memory capacity, with the same amount of non-linear processing power.

Abstract: Guanxi, a Chinese term that defines social networks of power and benefits, can be divided into inter-personal and inter-organizational relationships, and guanxi significantly influences construction innovation in China. Many studies have examined the relationship between guanxi and construction innovation at the project or organizational level. However, few of these studies explained how guanxi could affect an individual’s innovative behaviour from a double-level perspective. This paper builds on social capital theory and social exchange theory to examine guanxi’s role in motivating innovative behaviour in a China-specific construction context. It investigates the main effects of inter-personal relationships on innovative behaviour, the mediating effects of knowledge sharing, and the cross-level moderating effects of inter-organizational relationships. These elements were tested using a survey that received 178 responses from 35 different organizations. The results were analysed using Hierarchical Linear Modelling (HLM) and revealed that inter-personal relationships have positive influences on innovative behaviour, thus highlighting the partial mediating effects of knowledge sharing. In addition, the analyses showed that inter-organizational relationships augment inter-personal relationships and knowledge sharing on innovative behaviour by cross-level interaction. The research findings enhance an understanding of guanxi and innovative behaviour in China-specific construction project settings, as well as verifying the significance of guanxi in stimulating innovative behaviour.

Nanomagnetism and spintronics are currently active areas of research, with one of the main goals being the creation of low-energy-consuming magnetic memories based on nanomagnet switching. These types of devices could also be implemented in neuromorphic computing by crafting artificial neurons (ANs) that emulate the characteristics of biological neurons, through the implementation of neuron models such as the widely used leaky integrate-and-fire (LIF) with a refractory period. In this study, we have carried out numerical simulations of a 120 nm diameter, 250 nm length ferromagnetic nanowire (NW) with the aim of exploring the design of an artificial neuron based on the creation and destruction of a Bloch-point domain wall. To replicate signal integration, we applied pulsed trains of spin-currents to the opposite faces of the ferromagnetic NW. These pulsed currents (previously studied only in the continuous form) are responsible for inducing transitions between the stable single vortex (SV) state to the metastable Bloch point domain wall (BP-DW) state. To ensure the system exhibits the leak and refractory properties, the NW was placed in an homogeneous magnetic field of the order of mT in the axial direction. The suggested configuration fulfills the requirements and characteristics of a biological neuron, potentially leading to the future creation of Artificial Neural Networks (ANNs) based on reversible changes in the topology of magnetic NWs.

The retina is the sensory tissue responsible for the first stages of visual processing, with a conserved anatomy and functional architecture among vertebrates. To date, retinal eye diseases, such as diabetic retinopathy, age-related macular degeneration, retinitis pigmentosa, glaucoma and others, affect nearly 170 million people worldwide, resulting in vision loss and blindness. To tackle retinal disorders, the developing retina has been explored as a versatile model to study intercellular signaling, as it presents a broad neurochemical repertoire. Retina, dissociated and arranged as typical cultures, as mixed or neuron- and glia-enriched, and/or organized as neurospheres or as organoids are valuable to understand both neuronal and glial compartments which have contributed to reveal roles and mechanisms of transmitter systems as well as antioxidants, trophic factors, and extracellular matrix proteins. Overall, contributions in understanding neurogenesis, tissue development, differentiation, connectivity, plasticity, and cell death are widely described. A complete access to the genome of several vertebrates, as well the recent transcriptome at the single cell level at different stages of development also anticipates future advances in providing cues to target blinding diseases or retinal dysfunctions.

Inter-industry has various capital structures to take advantage of growth opportunities due to agency differences and information asymmetric problems. This research aims to analyze: (1) the differences in leverage between industries; (2) the impact of shareholders-debtholders conflict and information asymmetric on growth opportunities. The findings show that there are differences in leverage between industries. However, they are relatively stable and not excessive for assets to prevent conflicts between managers and shareholders and debtholders. Equity is also not used to utilize growth because it is used to reduce the discretionary power (dilution) of shareholders. As a result, the use of opportunities and growth is limited.

Introduction: The primary objective of researchers in the biology of ageing is to gain a comprehensive understanding of the ageing process while developing practical solutions that can enhance the quality of life for older individuals. This involves a continuous effort to bridge the gap between fundamental biological research and its real-world applications. Purpose: In this narrative review, we attempt to link research findings concerning the hormetic relationship between neurons and germ cells, and translate these findings into clinically relevant concepts. Methods: We conducted a literature search using PubMed, Embase, PLOS, Digital Commons Network, Google Scholar and Cochrane Library from 2000 to 2023, analyzing studies dealing with the relationship between hormetic, cognitive, and reproductive aspects of human ageing. Results: The process of hormesis serves as a bridge between the biology of neuron-germ cell interactions on one hand, and the clinical relevance of these interactions on the other. Details concerning these processes are discussed here, emphasizing new research which strengthens the overall concept. Conclusions: This review presents a scientifically and clinically relevant argument, claiming that maintaining a cognitively active lifestyle may decrease age-related degeneration, and improve overall health in ageing.

Brain aging causes a wide variety of changes at molecular and cellular levels, leading to the decline of cognitive functions and increased vulnerability to neurodegenerative disorders. The research aimed at understanding the aging of the brain has made much progress in recent decades. Technological innovations such as single-cell RNA-sequencing (scRNA-seq), proteomic analyses, and spatial transcriptomic analyses have facilitated the research on the dynamic changes occurring within neurons, glia, and other cells along with their impacts on intercellular communication during aging. In this review, we introduce recent trends of how neurons and glia change during aging and discuss the impact of the brain microenvironment such as the blood-brain barrier (BBB).

The circadian clock is a 24-hour cycle within the body that regulates various factors, including sleep, body temperature, and hormone secretion. It allows the body to adjust to the light and dark cycle. Disruptions to the circadian rhythm are important risk factors for many diseases, including neurodegenerative illnesses. The central clock is controlled by the clock genes in the suprachiasmatic nucleus (SCN) of the brain, and one of the main functions of the circadian clock is to regulate lipid metabolism. There has been a lack of investigation on the circadian regulation of lipid metabolism-related apolipoprotein genes in the brain; thus, this study sought to summarize the rhythmic expression of clock genes and lipid metabolism-related apolipoprotein genes within the SCN of Mus musculus. Out of the 20 apolipoprotein genes that were studied by the published database, all 9 genes were highly expressed in the SCN. Most of the 6 genes showed rhythmic expression in the brain of mice, suggesting that the master clock might regulate them. The results, therefore, reveal a potential target for preventing and treating circadian disorders. We summarized most studies of lipid-related apolipoprotein genes within limited locations of the SCN and brain to further understand how disordered cerebral lipid metabolism causes multiple brain diseases and disorders. We reviewed recent studies, determined the unexplored questions, and identified a potential direction for further research.

In bilaterians organism, the signaling of pyramidal neurons (PyrNs) is linked to the relative (prevalent) molecular chirality and physiological, perceptual, cognitive, and psychological functions and dysfunctions, providing the coupling of the central nervous system downstream and upstream evolutionary and developmental processes. The most apparent and discriminating morphological specificity of PyrNs is the geometry of the cell body. However, the question "why/how PyrNs soma gains the shape of quasi-tetrahedral symmetry" has never been explicitly articulated. If the basic function of PyrNs is sensory space perception, supporting the orientation, and movement coordination, then the pyramidal shape of soma is the best evolutionary-selected geometry to perform sensory-motor coupling. In biology, the impact of chiral symmetry (handedness) is evident at all levels of biological organization, from the prevalent symmetry of biological molecules to the morphology and function of bilateral organisms. How the tetrahedral symmetry of biomolecules is linked to the morphology and functions of bilateral organisms remains a challenging question. Cell chirality represents an intermediate point connecting two poles of biochirality. In this holistic perspective, examining the PyrNs' morphology-circuitry-function link is crucial to understanding the complex interaction between genetic, epigenetic, and environmental factors in the evolution of the CNS. The predictive power of our hypothesis can be partially expressed by the statement that the most integral and reliable biomarker of the neurodegenerative (including aging) and mental (including all variants of psychiatric illness) disorders would be the detection of the hemispheric asymmetry of D-amino acids (D-AAs) level in pyramidal neurons (PyrNs).

In recent years, artificial neural networks (ANNs) have won numerous contests in pattern recognition, machine learning, and artificial intelligence. The basic unit of an ANN is to mimic neurons in the brain. Neuron in ANNs is expressed as f (wx+b) or f (wx). This structure does not consider the information processing capabilities of dendrites. However, recently, studies shown that dendrites participate in pre-calculation in the brain. Concretely, biological dendrites play a role in the pre-processing to the interaction information of input data. Therefore, it is time to perfect the neuron of the neural network. This paper, add dendrite processing section, presents a novel artificial neuron, according to our previous studies (CR-PNN or Gang transform). The dendrite processing section can be expressed as . Because I perfected the basic unit of ANNs— neuron, there are so many networks to try. This article gives the basic architecture for reference in future research.

Five years after the introduction of the Prescribing Safety Assessment (PSA) in the UK, the role pharmacists play to help prepare medical students for this challenge is uncertain. Our study explored pharmacists’ perceptions about their role in undergraduate medical training for the Prescribing Safety Assessment (PSA). Study participants were emailed a qualitative questionnaire aimed at ascertaining their current involvement in undergraduate medical education, particularly the preparation for PSA. Responses received were thematically-analysed. A total of 27 UK hospital pharmacists and 3 pharmacists from local education and training boards completed the questionnaire. Pharmacists were positive about their involvement in medical student training, recognising the added value they could provide in prescribing practice. However, respondents expressed concerns in relation to resource availability and the need for formal educational practice mentoring. This research highlights the potential value of pharmacists’ input into medical education and the need for a discussion on strategies to expand this role to maximise the benefit from pharmacist skill mix in teaching safe prescribing.

Present work investigates, in photon energy domains of specific interest for medical imaging, the effect of the escape of X-ray fluorescence from the scintillator materials on the energy resolution of scintillation detector itself. Monolithic as well as pixelated crystals differently sized are considered, in the case of the NaI because it is the gold standard in the field. The volumetric ratio is introduced, as a figure of merit, taking into account, alongside the surface-to-volume ratio, the geometric shape, the elemental composition and also the mean-free-path for the given scintillator and energy. The inter-crystal XRF escape is finally suggested to be considered among the effects producing image blurring in segmented scintillatros due to the spread of events between the primary pixel and the first neighbors ones.

The highly specialized structure and function of neurons depend on a sophisticated organization of the cytoskeleton, which supports a similarly sophisticated system to traffic organelles and cargo vesicles. Mitochondria sustain crucial functions by providing energy and buffering calcium where is needed. Accordingly, the distribution of mitochondria is not even in neurons and is regulated by a dynamic balance between active transport and stable docking events. This system is finely tuned to respond to changes in environmental conditions and neuronal activity. In this review, we summarize the mechanisms by which mitochondria are selectively transported in different compartments taking into account the structure of the cytoskeleton, the molecular motors and the metabolism of neurons. Remarkably, the motor proteins driving the mitochondrial transport in axons have been shown to mediate also their transfer between cells. This so-named intercellular transport of mitochondria is opening new exciting perspectives in the treatment of multiple diseases.

Growing evidence suggests a possible involvement of the intestinal microbiota in generating new neurons, but a detailed breakdown of the microbiota composition is lacking. In this report, we systematically reviewed preclinical rodent reports addressing the connection between the composition of the intestinal microbiota and neurogenesis and neurogenesis-affecting neurotrophins in the hippocampus. Various changes in bacterial composition from low taxonomic resolution at the phylum level to high taxonomic resolution at the species level were identified. As for neurogenesis, studies predominantly used doublecortin (DCX) as a marker of newly formed neurons or bromodeoxyuridine (BrdU) as a marker of proliferation. Brain-derived neurotrophic factor (BDNF) was the only neurotrophin found researched in relation to the intestinal microbiota. Phylum Actinobacteria, genus Bifidobacterium and genus Lactobacillus found the strongest positive while phylum Firmicutes, phylum Bacteroidetes and family Enterobacteriaceae as well as germ-free status, showed the strongest negative correlation towards neurogenesis or BDNF mRNA expression. Age, short-chain fatty acids (SCFA), obesity and chronic stress were recurring topics in all studies identified. Overall, these findings add to the existing evidence of a connection between microbiota and processes in the brain. To better understand this interaction, further investigation based on analyses of higher taxonomic resolution and clinical studies would be a gain to the matter.

The most common and taught membrane theory assumes that the membrane behaves as a kind of electrical capacitance that is exposed to an electrical current generated by an ionic flow. If this statement is verifiable, it can be confirmed by the laws of physics, mathematics and in particular electricity. We will demonstrate that this hypothesis is not verified and that it is necessary to modify biophysics according to already established and experimentally verified principles of physics.

Our aim was to compare the inter-rater agreement of Transvaginal ultrasonography (TVS) with Magnetic Resonance Imaging (MRI) regarding diagnosing adenomyosis and for various predefined imaging features of adenomyosis in the same set of women. MRIs were assessed by four experienced radiologists and 2D TVS videoclips and 3D ultrasound volumes were assessed by five experienced sonographers. Each rater subjectively evaluated the presence or absence of adenomyosis, assessed various imaging. Fleiss kappa (κ) was used to reflect inter-rater agreement for categorical data and the Intraclass correlation coefficient (ICC) to reflect the reliability of quantitative data. Agreement between raters for diagnosing adenomyosis was higher for TVS than for MRI (κ =0.42 vs.0.28). MRI had a higher inter-rater agreement in assessing wall asymmetry irregular Junctional Zone (JZ) presence of myometrial cysts, while TVU had a better agreement for globular shape. MRI showed a moderate-good reliability for measuring the JZ (ICC=0.57-0.82). For TVS, JZ was unmeasurable in > 50% of cases and the remaining cases had a low reliability (ICC=-0.31-0.08). We found that Inter-rater agreement for diagnosing adenomyosis was higher for TVS than for MRI, despite that MRI showed a higher inter-rater agreement in most specific features. Measurements of JZ in the coronal plane with 3D TVS were unreliable and thus unlikely to be useful for diagnosing adenomyosis.

Molecular communication (MC) is a promising bio-inspired paradigm for exchanging molecule information among nanomachines. This paper proposes a synchronisation-assist photolysis MC system that aims to transmit the bio-sensing signal of the tumour microenvironment, facilitated by mitigating redundant molecules for improved bit error rate (BER) performance. Benefits from bio-compatible MC, biosensors could transmit bio-sensing signals of the tumour in $vivo$ instead of converting them to electrical signals. Due to diffusion motion's slow and stochastic nature, inter-symbol interference (ISI), resulting from previous symbols' residual information molecules, inevitably occurs in diffusion-based MC. ISI is one of the challenges in diffusion-based MC, which significantly impacts signal detection. Inspired by on-off keying (OOK) modulation, the proposed modulation implements a switch of molecules and light alternatively. The light emitted is triggered by a synchronisation signal, and the photolysis reactions could reduce the redundant molecules. An expression for the relevant channel impulse response (CIR) is derived from a hybrid channel model of diffusion and photolysis-reaction. This paper implements the maximum posterior estimation scheme to find the optimal decision threshold and analysis the BER performance in terms of different time intervals of the system. Numerical simulations demonstrate that the proposed method can improve the channel capacity and BER performance. We believe that our work may pave the way for MC application in bio-sensing.

Recently, inter-vehicle communication, which helps to avoid collision accidents (by driving safety support system) and facilitate self-driving (by dissemination of road and traffic information), has attracted much attention. In this paper, in order to efficiently collect road / traffic information in the request / response manner, first a basic method, Content-centric network (CCN) for Vehicular network (CV), is proposed, which applies CCN cache function to inter-vehicle communication. Content naming and routing, which take vehicle mobility into account, are investigated. On this basis, the CV method is extended (named as ECV) to avoid the cache miss problem caused by vehicle movement, and is further enhanced (named as ECV+) to more efficiently exploit cache buffer in vehicles, caching content according to a probability decided by channel usage rate. Extensive evaluations on network simulator Scenargie, with realistic open street map, confirm that the CV method and its extensions (ECV, ECV+) effectively reduce the average number of hops of data packets (by up to 47%, 63%, 83% respectively) and greatly improve the content acquisition success rate (by up to 356%, 444%, 689%, respectively), compared to the method without cache mechanism.

The PILAR model provides a dynamical systems perspective on collaboration. Two studies are performed using peer assessment data, both testing empirical support for the five Pillars (prospects, involved, liked, agency, respect) that constitute member’s perceptions of collaboration viability. The first study analyses peer-assessment data collected online from 458 first-year engineering students (404 males; 54 females). A nine-item instrument was inherited from past year’s usage in the course, expanded with four additional items to elaborate upon the agency and liked Pillars. Exploratory factor analysis was conducted on student responses to test whether they thematically aligned to constructs consistent with the five Pillars. As anticipated, twelve of the thirteen items grouped into five components, each aligned with a Pillar, providing empirical evidence that the five Pillars represent perceptions of collaboration. The second study replicated the first study using a retrospective analysis of 87 items included in the Comprehensive Assessment of Team Member Effectiveness (CATME) peer-assessment tool. The associated factor analyses resulted in five components and conceptual alignment of these components with Pillars was evident for three of five CATME components. We recommend a peer-assessment instrument based upon PILAR as potentially more parsimonious and reliable than an extensive list of behaviours, such as employed by CATME. We also recommend including items that target inter-rater bias, which is aligned with the liked Pillar, that instruments such as CATME exclude.

Chronic pain has increasingly become a significant health challenge, not just as a symptomatic manifestation but also as a pathological condition with profound socioeconomic implications. Despite the expansion of medical interventions, the prevalence of chronic pain remains remarkably persistent, prompting a turn towards non-pharmacological treatments, such as therapeutic education, exercise and cognitive-behavioral therapy. With the advent of cognitive neuroscience, pain is often presented as a primary output derived from the brain, aligning with Engel's Biopsychosocial Model which views disease not solely from a biological perspective but also considering psychological and social factors. This paradigm shift, brings forward potential misconceptions and over-simplifications. The current review delves into the intricacies of nociception and pain perception. It questions long-standing beliefs like the cerebral-centric view of pain, the forgotten role of the peripheral nervous system in pain chronification, misconceptions around central sensitization syndromes, the controversy about the existence of a dedicated pain neuromatrix, the consciousness of the pain experience and the possible oversight of factors beyond the nervous system. In re-evaluating these aspects, the review emphasizes the critical need for understanding the complexity of pain, urging the scientific and clinical community to move beyond reductionist perspectives and consider the multifaceted nature of this phenomenon.

Nervous systems evolved around 560 million years ago to coordinate and empower animal bodies. Ctenophores – one of the earliest-branching lineages – are thought to share few neuronal genes with bilaterians and may have evolved neurons convergently. Here we review our current understanding of the evolution of neuronal molecules in non-bilaterians. We also reanalyse single-cell sequencing data in light of new cell-cluster identities from a ctenophore and uncover evidence supporting the homology of one ctenophore neuron-type with neurons in Bilateria. The specific coexpression of the presynaptic proteins Unc13 and RIM with voltage-gated channels, neuropeptides and homeobox genes pinpoint a spiking sensory-peptidergic cell in the ctenophore mouth. Similar Unc13-RIM neurons may have been present in the first eumetazoans to rise to dominance only in stem Bilateria. We hypothesize that the Unc13-RIM lineage ancestrally innervated the mouth and conquered other parts of the body with the rise of macrophagy and predation during the Cambrian explosion.

Cisplatin induces early-onset ototoxicity, resulting in hearing loss. The exact mechanism by which cisplatin causes ototoxicity remains unclear. The purpose of this study was to identify the involvement of receptor-interacting protein kinase(RIP)3-dependent necroptosis in cisplatin-induced ototoxicity in animal models. Sprague–Dawley rats (SD, 8 week) were treated via intraperitoneal (i.p) injection with cisplatin (16 mg/kg for 1 day), and their hearing thresholds were was measured by the auditory brainstem response (ABR) method. Hematoxylin and eosin (H-E) staining, immunohistochemistry, and western blots were performed to determine the effect of cisplatin-induced ototoxicity on cochlear morphology. H-E stains outlined necroptotic changes in the organ of Cortis (OCs) and spiral ganglion neurons (SGNs). Additionally, immunohistochemistry and western blot analysis showed overexpression of RIP3 in the OCs and SGNs that were treated with cisplatin. These results suggest that RIP3-dependent necroptosis was substantial in cisplatin-induced ototoxicity; inner cochlear regions, the OCs, and SGNs were especially sensitive to necroptosis.

The cytostatic agent hydroxyurea (HU) has proven to be beneficial for a variety of conditions in the disciplines of oncology, hematology, infectious disease and dermatology. It disrupts the S-phase of the cell cycle by inhibiting the ribonucleotide reductase enzyme, thus blocking the transformation of ribonucleotides into deoxyribonucleotides, a rate limiting step in DNA synthesis. HU is listed as an essential medicine by the World Health Organization. Several studies have indicated that HU is well tolerated and safe in pregnant women and very young pediatric patients. To our knowledge, only a few controlled studies about the adverse effects of HU therapy have been done in humans. Despite this, the prevalence of central nervous system abnormalities, including ischemic lesions and stenosis have been reported. This review will summarize and present the effects of HU-exposure on the prenatal and perinatal development of the rat cerebellar cortex and deep cerebellar nuclei neurons. Our results call for the necessity to better understand HU effects and define the administration of this drug to gestating women and young pediatric patients.

Amyotrophic lateral sclerosis (ALS) is a rare, progressive, neurodegenerative disorder caused by degeneration of upper and lower motor neurons. The disease process leads from lower motor neuron involvement to progressive muscle atrophy, weakness, fasciculations for the upper motor neuron involvement to spasticity. Muscle atrophy in ALS is caused by a dysregulation in the molecular network controlling fast and slow muscle fibres. Denervation and reinnervation processes in skeletal muscle occur in the course of ALS and are modulated by rehabilitation. MicroRNAs (miRNAs) are small non-coding RNAs that modulate a wide range of biological functions under various pathophysiological conditions. MiRNAs can be secreted by various cell types and they are markedly stable in body fluids. MiR-1, miR-133 a, miR-133b, and miR-206 are called “myomiRs” and are considered markers of myogenesis during muscle regeneration and neuromuscular junction stabilization or sprouting. We observed a positive effect of a standard aerobic exercise rehabilitative protocol conducted for six weeks in 18 ALS patients during hospitalization in our center. We correlated clinical scales with molecular data on myomiRs. After six weeks of moderate aerobic exercise, myomiRNAs were down-regulated, suggesting an active proliferation of satellite cells in muscle and increased neuromuscular junctions. Our data suggest that circulating miRNAs modulate during skeletal muscle recovery in response to physical rehabilitation in ALS.

The diverse physical appearances and wide density range of polymer bead foams offer immense potential across various applications and future advancements. The multi-scale and multi-level structural features of bead foams involve many fundamental scientific topics. This review presents a comprehensive overview of recent progress in bead foams preparation and molding techniques. Initially, a comparative analysis is conducted among bead foam characteristics of distinct polymers, based on their unique properties. Subsequently, a summary and comparison of molding processes employed for fabricating bead foam parts are provided. Beyond traditional methods like steam-chest molding (SCM) and adhesive-assisted molding (AAM), emerging techniques like in-mold foaming and molding (IMFM) and microwave selective sintering (MSS) are highlighted. Lastly, the bonding mechanisms behind the diverse molding methods are discussed.

Forensic hospitals throughout the country house individuals with severe mental illness and history of criminal violations. Insomnia affects 67.4% of hospitalized patients with chronic neuropsychiatric disorders, indicating that these conditions may hijack human somnogenic pathways. Conversely, somnolence is a common adverse effect of many antipsychotic drugs, further highlighting a common etiopathogenesis. The role of dysfunctional mitochondria in psychopathology is well-established, however, the association of these organelles with sleep physiology is novel. Indeed, reducing neuronal oxidative stress by importing mitochondria from astrocytes, may be the purpose of human slumber. This model may explain mitochondrial dysfunction during anesthesia as well as in the rare genetic disease, fatal familial insomnia. In this narrative review, we focus on the salience network of the brain, a common denominator for insomnia, neuropsychiatric and neurodegenerative disorders. We also discuss mitochondria-protecting strategies, including membrane lipid replacement, natural and synthetic phenazine and phenothiazine derivatives.

This research investigates the implementation of complex exponential-based neurons in FPGA, which can pave the way for implementing bio-inspired spiking neural networks to compensate for the existing computational constraints in conventional artificial neural networks. The increasing use of extensive neural networks and the complexity of models in handling big data lead to higher power consumption and delays. Hence, finding solutions to reduce computational complexity is crucial for addressing power consumption challenges. The complex exponential form effectively encodes oscillating features like frequency, amplitude, and phase shift, streamlining the demanding calculations typical of conventional artificial neurons through levering simple phase addition of complex exponential functions. The article implements such a two-neuron and a multi-neuron neural model using Xilinx system generator and Vivado design suite, employing 8-bit, 16-bit, and 32-bit fixed-point data format representations. The study evaluates the accuracy of the proposed neuron model across different FPGA implementations while also providing a detailed analysis of operating frequency, power consumption, and resource usage for the hardware implementations. BRAM-based Vivado designs outperformed Simulink regarding speed, power, and resource efficiency. Specifically, the Vivado BRAM-based approach supported up to 128 neurons, showcasing optimal LUT and FF resource utilization. Such outcomes accommodate choosing the optimal design procedure for implementing spiking neural networks on FPGAs.

In network analysis, links depict the connections between each pair of network nodes. However, such pairwise connections fail to consider the interactions among more agents, which may be indirectly connected. Such non-pairwise or higher-order connections can be signified by involving simplicial complexes. The higher-order connections become even more noteworthy when it comes to neuronal network synchronization, an emerging phenomenon responsible for the many biological processes in real-world phenomena. However, involving higher-order interactions may considerably increase the computational costs. To confound this issue, map-based models are more suitable since they are faster, simpler, more flexible, and computationally more optimal. Therefore, this paper addresses the impact of pairwise and non-pairwise neuronal interactions on the synchronization state of 10 coupled memristive Hindmarsh-Rose neuron maps. To this aim, electrical, inner linking, and chemical synaptic functions are considered as 2- and 3-body interactions in three homogenous and two non-homogenous cases. The results show that through chemical pairwise and non-pairwise synapses, the neurons achieve synchrony with the weakest coupling strengths.

Working memory refers to the capability of the nervous system to selectively retain short-term memories in an active state. The long-standing viewpoint is that neurons play an indispensable role and working memory is encoded by synaptic plasticity. Furthermore, some recent studies have shown that calcium signaling assists the memory processes and the working memory might be affected by the astrocyte density. Over the last few decades, growing evidence has also revealed that astrocytes exhibit diverse coverage of synapses which are considered to participate in neuronal activities. However, very little effort has yet been made to attempt to shed light on the potential correlations between these observations. Hence, in this article we will leverage a computational neuron-astrocyte model to study the short-term memory performance subject to various astrocytic coverage and we will demonstrate that the short-term memory is susceptible to this factor. Our model may also provide plausible hypotheses for the various sizes of calcium events as they are reckoned to be correlated with the astrocytic coverage.

For more than 70 years, biologists and biophysicists have been trying to unravel the mystery that exists regarding the saltatory conduction of so-called myelinated neurons. Albert Einstein used the train metaphor to explain the theory of relativity. It is possible to use a similar metaphor to better understand this transient functioning of the neuron: the action potential. We will, once again, use a train to demonstrate unequivocally that the action potential does not jump from node of Ranvier to node of Ranvier (noR) as we thought it would. It is possible to describe that the neuron uses an elegant method to increase the speed of transmission of the neural message. It is also important to conclude that this increase in speed, contrary to the common idea, has a certain energy cost that is proportional to speed and in accordance with thermodynamics.

In the Versatile Video Coding (VVC) standard, affine motion models have been applied to enhance the resolution of complex motion patterns. However, due to the high computational complexity involved in affine motion estimation, real-time video processing applications face significant challenges. This paper focuses on optimizing affine motion estimation algorithms in the VVC environment and proposes a fast gradient iterative algorithm based on edge detection for efficient computation. Firstly, we establish judging conditions during the construction of affine motion candidate lists to streamline the redundant judging process. Secondly, we employ the Canny edge detection method for gradient assessment in the affine motion estimation process, thereby enhancing the iteration speed of affine motion vectors. Experimental results demonstrate that our affine motion estimation algorithm reduces encoding time by approximately 15%-35% while maintaining video bitrate and quality.

Background: To implement the new marker in clinical practice, reliability assessment, validation, and standardization of utilization must be applied. This study evaluated the reliability of TILs and TSR assessment through conventional microscopy by comparing observers’ estimations. Methods: Intratumoral and tumor-front stromal TILs, and TSR were assessed by three pathologists using 86 HE slides CRC. TSR and TILs were categorized using one and four different proposed cut-off systems, respectively and agreement was assessed using the intraclass coefficient (ICC) and Cohen’s kappa statistics. Pairwise evaluation of agreement was performed using the Fliess Kappa statistic and the concordance rate and it was visualized by Bland-Altman plots. Results: For the evaluation of intratumoral stromal TILs, ICC of 0.505 (95% CI:0.35-0.64) was obtained, Kappa values were in the range of 0.21 to 0.38, and concordance rates in the range of 0.61 to 0.72. For the evaluation of tumor-front TILs, ICC was 0.52 (95% CI:0.32 - 0.67), the overall kappa value ranged from 0.24 to 0.30, and the concordance rate ranged from 0.66 to 0.72. For estimating the TSR, the ICC was 0.48 (95% CI:0.35 - 0.60), the kappa value was 0.49 and the concordance rate was 0.76. Conclusion: The agreement between pathologists in estimating these markers corresponds to poor to the moderate agreement, however, implementing immune scores in daily practice requires more concentration in inter-observer agreements.

The results of experimental studies of ohmic conductivity degradation in the ensembles of nanostructured anatase bridges under long-term effect of direct current are presented. Stochastic sets of interelectrode partially conducting bridges consisting of close-packed anatase nanoparticles were formed by the seeding particles from drying aqueous suspensions on the surfaces of silica substrates with interdigital platinum electrodes. Multiple-run experiments at room temperature have shown that ohmic conductivity degradation in these systems is irreversible. It is presumably due to accumulated capture of conduction electrons by deep traps in anatase nanoparticles. The scaling analysis of voltage drops across the samples at the final stage of degradation gives a critical exponent for ohmic conductivity as 1.597. This value satisfactorily agrees with the reported model data for percolation systems. At an early stage of degradation, the spectral density of conduction current fluctuations wihin the frequency range of 0.01 Hz - 1 Hz decreases approximately as , while near the percolation threshold the decrease trend changes to . This transition is interpreted in terms of an increasing contribution of blockages and subsequent avalanche-like breakdowns of part of the local conduction channels in the bridges into electron transport near the percolation threshold.

A procedure, dedicated to superconductivity, is extended to study the properties of interacting electrons in normal metals in the thermodynamic limit. Each independent-electron band is shown to split into two correlated-electron bands. Excellent agreement is achieved with Bethe's wave-function for the one-dimensional Hubbard model. The groundstate energy, reckoned for the two-dimensional Hubbard Hamiltonian, is found to be lower than values, obtained thanks to the numerical methods. This analysis applies for any spatial dimension and temperature.

Brain is the most complex organ in the human body and it is divided into two hemispheres - left and right hemispheres. Left hemisphere is responsible for control of right side of our body whereas right hemisphere is responsible for control of left side of our body. Brain image segmentation from different neuroimaging modalities is one of the important parts in clinical diagnostic tools. Neuroimaging based digital imagery generally contain noise, inhomogeneity, aliasing artifacts, and orientational deviations. Therefore, accurate segmentation of brain images is a very difficult task. However, the development of accurate segmentation of brain images is very important and crucial for a correct diagnosis of any brain related diseases. One of the fundamental segmentation tasks is to identify and segment inter-hemispheric fissure/mid-sagittal plane, which separate the two hemispheres of the brain. Moreover, the symmetric/asymmetric analyses of left and right hemispheres of brain structures are important for radiologists to analyze diseases such as Alzheimer's, Autism, Schizophrenia, Lesions and Epilepsy. Therefore, in this paper we have analyzed the existing computational techniques used to find brain symmetric/asymmetric analysis in various neuroimaging techniques (MRI/CT/PET/SPECT), which are utilized for detecting various brain related disorders.

Recent studies, typically using patient cerebrospinal fluid (CSF), have suggested that different autoantibodies (Aabs) acting on their respective receptors, may underlie neuropsychiatric disorders. The NR1 subunit of the N-methyl-D-aspartate receptor (NMDAR) has been identified as a target of anti-NMDAR Aabs in a number of central nervous system (CNS) diseases including encephalitis and autoimmune epilepsy. However, the role or the nature of Aabs responsible for effects on neuronal excitability and synaptic plasticity is yet to be established fully. Patient-derived anti-NMDAR Aabs have been shown to bind to specific regions within the NR1 subunit; here, peptide immunisation was used to generate Aabs against selected specific NR1 extracellular sequences. ‘Protein A’ purification was used to obtain total IgG and further peptide purification used to obtain a greater percentage of NMDAR-target specific IgG Aabs. Binding and specificity of these anti-NMDAR Aabs was determined using a range of methodologies including enzyme-linked immunosorbent assay, immunocytochemistry and immunoblotting. Functional effects were determined using different in vitro electrophysiology techniques: two-electrode voltage-clamp in Xenopus oocytes and measures of long-term potentiation (LTP) in ex vivo hippocampal brain slices using multi-electrode arrays. We show that anti-NMDAR Aabs generated from peptide immunisation had specificity for NR1 immunisation peptides as well as target-specific binding to the native protein. Anti-NMDAR Aabs had no clear effect on isolated NMDARs in an oocyte expression system. However, we show that peptide-purified anti-NMDAR Aabs prevented the induction of LTP at Schaffer collateral-CA1 synapses in ex vivo brain slices. Our data demonstrate that anti-NMDAR Aabs cause synaptic NMDAR hypofunction at a network level. This work provides a solid basis to address outstanding questions regarding anti-NMDAR Aabs mechanisms of action and, potentially, development of therapies against CNS diseases.

With the explosion of the generation, transmission and sharing of image data over the Internet and other unsecured networks, the need and significance for the development of novel image encryption algorithms is unprecedented. In this research work, we propose a novel framework for image encryption that is based on two hyperchaotic maps, utilized in conjunction with the single neuron model (SNM). The framework entails three successive stages, where in every stage, a substitution box (S-box) is applied, then XORing with an encryption key is carried out. The S-boxes and the encryption keys are generated from the numerical solutions of the hyperchaotic maps and the SNM. The performance of the proposed framework is gauged through a number of metrics, reflecting superior performance and complete asymmetry between the plain images and their encrypted versions. However, the main advantages of this work are: (1) The attained width of the key space; and (2) The achieved efficiency in software implementation. The superior key space of 2^{2551} is the result of employing the two hyperchaotic maps, while the improved efficiency, resulting in an average encryption rate of 8.54 Mbps, is the result of the utilization of the single neuron model, as well as the employment of optimized parallel processing techniques. In addition, the proposed encryption framework is shown to output encrypted images that pass the NIST SP 800 suite.

Long-term potentiation (LTP) is a molecular basis of memory formation. Here, we demonstrate that LTP critically depends on muscle fructose 1,6-bisphosphatase 2 (Fbp2) – a glyconeogenic enzyme and moonlighting protein protecting mitochondria against stress. We show that LTP induction regulates Fbp2 association with neuronal mitochondria and Camk2, and that the Fbp2-Camk2 interaction correlates with Camk2 autophosphorylation. Silencing of Fbp2 expression or simultaneous inhibition and tetramerization of the enzyme with a synthetic effector mimicking the action of physiological inhibitors (NAD⁺ and AMP) abolishes Camk2 autoactivation and blocks formation of the early phase of LTP and expression of the late phase LTP markers. Astrocyte-derived lactate reduces NAD⁺/NADH ratio in neurons and thus, diminishes the pool of tetrameric and increases the fraction of dimeric Fbp2. We therefore hypothesize that this NAD⁺-level-dependent increase of the Fbp2 dimer/tetramer ratio might be a crucial mechanism in which astrocyte-neuron lactate shuttle stimulates LTP formation.

Recent technological advancements in conservation genetics and genomics have resulted in diverse tools for aiding conservation of species. The precision and resolution of high throughput sequencing technologies provide valuable insights to aid conservation decisions, but these technologies are often financially unfeasible or unavailable in resource constrained countries. Inter-Simple Sequence Repeat (ISSR) markers, when combined with sensitive automated detection systems, provide a simple, cheap means to investigate genetic diversity and discriminate closely related species. Here we apply this technology to assess genetic diversity and taxonomic delimitation in the Encephalartos eugene-maraisii species complex, a highly threatened, taxonomically dubious group of cycads in South Africa. Silica dried cycad leaflets were extracted using the Oktopure robot employing Sbeadex chemistry and amplified with fluorescently tagged ISSR primers. Band presence was scored with an ABI 3130 genetic sequencer under three different fluorescence cut-off values. Phenetic analyses were performed in NTSYS software while Bayesian analysis was performed in STRUCTURE, and haplotype network analysis, AMOVA and Tajima’s D statistic was computed with PopART. Our analyses support taxonomic singularity of E. dyerianus, E. dolomiticus and E. eugene-maraisii. Relationships between E. nubimontanus and E. cupidus remain uncertain. E. middelburgensis samples showed no clustering but had poor amplification success. This study demonstrated the suitability of automated ISSR fingerprinting as a method for plant conservation studies, especially in resource-constrained countries.

Several long-term monitoring of aerosol datasets from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra/Aqua, Multi-angle Imaging SpectroRadiometer (MISR), Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) are used to derive the dust aerosol optical depth (DOD) in Central Asia based on the Angstrom exponent parameter and/or the particle shape. All sensors agree very well on the interannual variability of DOD. The seasonal analysis of DOD and dust occurrences identified the largest dust loading and the most frequent dust occurrence in the spring and summer, respectively. No significant trend is found during the research period in terms of both DOD and the dust occurrence. Further analysis of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) aerosol products on a case-by-case basis in most dust months of 2007 suggested that the vertical structure is varying in terms of the extension and the dust loading from one event to another, although dust particles of most episodes have similar physical characteristics (the particle shape and size). Our analysis on the vertical structure of dust plumes, the layer-integrated color ratio and depolarization ratio indicates a varied climate effect (e.g., the direct radiative impact) by mineral dust, dependent on the event being observed in Central Asia.

Cellular therapies have started an important new therapeutic direction for Autistic Spectrum Disease (ASD), and the ample diversity of ASD pathophysiology and the different types of cell therapies need an equally ample effort for studying the applicable ASD causes and the specific benefits of cell therapies via clinical studies.CORDUS Clinical Study is a crossover study in which autologous cord blood was administered intravenously to 56 patients between January 2019 and July 2023, and has compared its efficacy versus an individualized combination of supplements; both treatments were administered in a different sequence to all participants. Treatment efficacy was evaluated pre- and post- treatments by an independent psychotherapist with ATEC, Q-CHAT and a 16-item comparative table score, after interviews with the children’s parents and therapists.Cord blood was beneficial in the group of 3–7-year-old children (n=28; 3 out of 4 children – 78.57% - improved scores), but was much less effective in kids older than 8 years or with body weight of more than 35 kg (n=28; 1 out of 10 children improved scores). Individualized supplements were more efficacious than cord blood in 5 cases out of 28, while in 23 kids cord blood brought more improvement than supplements; 6 kids registered minor or no improvement. Statistically significant improvements were seen after cord blood infusion on areas such as verbalization and social interaction, but not on irritability or aggressive behavior; also ample individual differences were noted. No serious adverse reactions were noted during and after cord blood or supplement administration.

Abstract: Objectives: To establish the expression profile of N6-methyladenosine(m6A) modifications in the hippocampus of mice with diabetic cognitive impairment (DCI) and elucidate the potential regulatory mechanism. Methods: A DCI model was established by feeding a high-fat diet to C57BL/6J mice. m6A and RNA sequencing was conducted to profile the m6A-tagged transcripts in the hippocampus. Results: Methylated RNA immunoprecipitation with next-generation sequencing and RNA sequencing analyses yielded differentially m6A-modified and expressed genes in the hippocampus of DCI mice, which were enriched in pathways involving synaptic transmission and axonal guidance. Mechanistic analyses revealed a remarkable change in m6A modification levels through alteration of the mRNA expression of m6A methyltransferases (METTL3 and METTL14) and demethylase (FTO) in the hippocampus of DCI mice. Conclusions: We identified a co-mediated specific RNA regulatory strategy that broadens the epigenetic regulatory mechanism of RNA-induced neurodegenerative disorders associated with metabolic and endocrine diseases.

Recent biotechnological innovations make feasible the new paradigm of creating biological neural circuits de novo. With advances in protein, cell and tissue engineering techniques, as well as cellular reprogramming methods, we are entering an era where the construction of neural circuits can open completely new ways for studying nervous systems and for treating nervous system disorders. I explore here three technologies, namely cellular engraftment, neuronal reprogramming and transsynaptic molecule engineering, and delineate how they are being used in a variety of basic research and translational medicine contexts. In basic neuroscience, neural circuit construction methods are enabling ways to study causality in neural development (e.g. neural precursor differentiation and migration) and circuit function (e.g. excitation/inhibition balance, neural population dynamics). In translational neuroscience, they are providing opportunities for the targeted correction of circuit malfunction in brain disorders, both psychiatric (e.g. schizophrenia) and neurological (e.g. Parkinson’s, Huntington’s and Alzheimer’s disease, as well as epilepsy). I discuss the challenges that these methods currently face, such as targeting specificity and cell survival, and outline future paths and opportunities to realize the full potential of technologies for creating new biological neural circuits.

The receptor tyrosine kinase Ret plays a critical role in regulating enteric nervous system (ENS) development. Ret is important for proliferation, migration, and survival of enteric progenitor cells (EPCs). Ret also promotes neuronal fate, but its role during neuronal differentiation and in the adult ENS is less well understood. Inactivating RET mutations are associated with ENS diseases, e.g. Hirschsprung Disease, in which distal bowel lacks ENS cells. Zebrafish is an established model system for studying ENS development and modeling human ENS diseases. One advantage of the zebrafish model system is that their embryos are transparent allowing visualization of developmental phenotypes in live animals. However, we lack tools to monitor Ret expression in live zebrafish. Here, we developed a new BAC transgenic line that expresses GFP under the ret promoter. We find that EPCs and the majority of ENS neurons express ret:GFP during ENS development. In the adult ENS, GFP+ neurons are equally present in female and male. In homozygous mutants of ret and sox10 – another important ENS developmental regulator gene – GFP+ ENS cells are absent. In summary, we characterize a ret:GFP transgenic line as a new tool to visualize and study the Ret signaling pathway from early development through adulthood.

Current hypotheses implicate insulin resistance of the brain as a pathogenic factor in the development of Alzheimer’s disease and other dementias, Parkinson’s disease, type 2 diabetes, obesity, major depression, and traumatic brain injury. A variety of genetic, developmental, and metabolic abnormalities that lead to disturbances in the insulin receptor signal transduction may underlie insulin resistance. Insulin receptor substrate proteins are generally considered to be the node in the insulin signaling system that is critically involved in the development of insulin insensitivity during metabolic stress, hyperinsulinemia, and inflammation. Emerging evidence suggests that lower activation of the insulin receptor (IR) is another common, while less discussed, mechanism of insulin resistance in the brain. This review aims to discuss causes behind the diminished activation of IR in neurons, with a focus on the functional relationship between mitochondria and IR during early insulin signaling and the related roles of oxidative stress, mitochondrial hypometabolism, and glutamate excitotoxicity in the development of IR insensitivity to insulin.

Current hypotheses implicate insulin resistance of the brain as a pathogenic factor in the development of Alzheimer’s disease and other dementias, Parkinson’s disease, type 2 diabetes, obesity, major depression, and traumatic brain injury. A variety of genetic, developmental, and metabolic abnormalities that lead to disturbances in the insulin receptor signal transduction may underlie insulin resistance. Insulin receptor substrate proteins are generally considered to be the node in the insulin signaling system that is critically involved in the development of insulin insensitivity during metabolic stress, hyperinsulinemia, and inflammation. Emerging evidence suggests that lower activation of the insulin receptor (IR) is another common, while less discussed, mechanism of insulin resistance in the brain. This review aims to discuss causes behind the diminished activation of IR in neurons, with a focus on the functional relationship between mitochondria and IR during early insulin signaling and the related roles of oxidative stress, mitochondrial hypometabolism, and glutamate excitotoxicity in the development of IR insensitivity to insulin.

Oxidative stress is known to be critically implicated in the pathophysiology of several neurological disorders, including Alzheimer’s disease and ischemic stroke. The remarkable neurotrophic activity of Gelidium amansii, has been reported consistently in a series of our previous studies, inspired us to investigate whether this popular agarophyte could protect against hypoxia/reoxygenation (H/R)-induced oxidative injury in hippocampal neurons. The primary culture of hippocampal neurons challenged with H/R suffered from a significant loss of cell survival, accompanied by apoptosis and necrosis, DNA damage, generation of reactive oxygen species (ROS), and dissipation of mitochondrial membrane potential (MMP) which were successfully attenuated when the neuronal cultures were preconditioned with GAE, an optimized ethanolic extract of G. amansii. Moreover, the expression of N-methyl-D-acetate receptor subunit 2B (GluN2B), an extrasynaptic glutamate receptor, was significantly repressed in GAE-treated neurons as compared to those without GAE intervention. Together, this study demonstrates that GAE attenuated H/R-induced oxidative injury in hippocampal neurons through, at least in part, a potential neuroprotective mechanism that involves inhibition of GluN2B-mediated excitotoxicity and suppression of ROS production, and suggest that this edible seaweed could be a potential source of bioactive metabolites having therapeutic significance against oxidative stress-related neurodegeneration, including ischemic stroke and neurodegenerative diseases.

Key features of glycogen metabolism in excitable tissues are not well-explained by current concepts. Glycogen stores in brain and skeletal muscle are generally considered to function as local glucose reserves, to be utilized during transient mismatches between glucose supply and demand; however, quantitative measures show that blood glucose supply is likely never rate-limiting for energy metabolism in either brain or muscle under physiological conditions. These tissues nevertheless do normally utilize glycogen during intervals of increased energy demand, despite the availability of free glucose, and despite the ATP cost of cycling glucose through glycogen polymer. This seemingly wasteful shunt can be explained by considering the effect of glycogenolysis on the amount of energy derived from ATP (ΔG’ATP). ΔG’ATP is diminished by elevations in Pi, such as occur at sites of rapid ATP hydrolysis and net phosphocreatine consumption. Glycogen utilization counters this effect by sequestering Pi in glycolytic metabolites (glycogen_n + Pi → glycogen_n-1 + glucose-1-phosphate → phosphorylated glycolytic intermediates), and thereby maintains the amount of energy obtained from ATP at sites of rapid ATP consumption. This thermodynamic effect may be particularly important in the narrow, spatially constricted astrocyte processes that ensheath neuronal synapses. This effect can also explain the co-localization of glycogen and cytosolic phosphocreatine in brain astrocytes, glycolytic super-compensation in brain when glycogen is not available, and aspects of exercise physiology in muscle glycogen phosphorylase deficiency (McArdle’s disease).

Understanding morphological and genetic diversity of forest trees is essential to facilitate their conservation, sustainable management and genetic improvement for addressing the economic and environmental demands and challenges. We have examined variation in morphometric seed and pod traits and seed germination of multipurpose and widely distributed forest tree Albizia lebbek (Indian siris) from 12 provenances covering the species’ range in northern India and its relationships with bioclimatic factors. Highly significant inter-provenance variation was observed in seed size (seed length (SL), seed width (SW), SW/SL, SL×SW), seed mass (1000 seed weight), pod size (pod length (PL), pod width (PW), PW/PL), seed germination, number of seeds per pod, and insect infected seeds (IIS). The provenance effect contributed a major portion to the total phenotypic variance. Morphometric variation in all traits except for IIS was not clinal related to longitude, latitude, altitude or rainfall. There was an indication of the presence of ecotypic variation. IIS showed clinal variation with significant negative correlation with latitude. Most seed size and pod size traits showed positive correlations with several temperature bioclimatic factors and negative correlations with several precipitation bioclimatic factors. Our results have significance for genetic improvement, population genetics and genomics studies and conservation and sustainable management of A. lebbek genetic resources.

Electrical rotating machines like Induction Motors (IMs) are widely used in several industrial applications since their robust elements, provide high efficiency and give versatility in industrial applications. Nevertheless, the occurrence of faults in IMs is inherent to their operating conditions, hence, Inter-turn short-circuit (ITSC) is one of the most common failures that affect IMs and its appearance is due to electrical stresses leads to the degradation of the stator winding insulation. In this regard, this work proposes a diagnosis methodology for the assessment and detection of incipient ITSC in IMs, the proposed method is based on the processing of vibration, stator currents and magnetic stray-flux signals. Certainly, the novelty and contribution include the characterization of different physical magnitudes by estimating a set of statistical time domain features, as well as, their fusion and reduction through the Linear discriminant Analysis technique within a feature-level fusion approach. Furthermore, the fusion and reduction of information from different physical magnitudes leads to perform the automatic fault detection and identification by a simple Neural-Network (NN) structure. The proposed method is evaluated under a complete set of experimental data and the obtained results demonstrate that the fusion of information from different sources (physical magnitudes) allows to improve the accuracy during the detection of ITSC in IMs , the results make this proposal feasible to be incorporated as a part of condition-based maintenance programs in the industry.

The easternmost Mediterranean is a distinct transition zone from the ocean to the continent located at the junction between the largest Earth's lithospheric segments: Eurasian and African. The methodology of paleomagnetic mapping of such transition zones is based on integrating the mapping techniques for both continental and oceanic platforms: paleomagnetic reconstructions, results of radiometric dating of magnetized rocks, tectonic-structural reconstructions, biogeography, and utilization of the results of various geophysical surveys. The geodynamic-paleomagnetic mapping makes it possible to reveal the multilevel structural heterogeneity and display complex elements of the geodynamics of different ages inherent in this transition zone. Northern Israel is obviously the most complex area in the easternmost Mediterranean. For the combined paleomagnetic mapping, well-studied paleomagnetically and radiometrically areas were selected: (1) the Carmel area, (2) the Atlit area (internal part of the Carmel area), (3) the Sea of Galilee with the adjoining zones (primarily, the Kinnarot Valley), and (4) the area of the Hula Basin with adjacent areas of the Golan Plateau, Hermon Mt., and Galilea uplift. The constructed paleomagnetic profiles for the Carmel area (on the top of the accumulative surface of the Lower Cretaceous traps), and the Kinnarot Valley – Sea of Galilee – Hula Basin, evidently indicate the complex history of the paleogeodynamic evolution of the region. These studies demonstrate the effectiveness of paleomagnetic mapping interated with paleomagnetic profiling, which crosses these geologically complex areas.

Human induced pluripotent stem cell (hiPSC)-derived neural cells have been used at the preclinical stage of drug development. As previously reported, hiPSC-derived neurons exhibit greater tolerance to excitotoxicity than that of primary cultures of rodent neurons; however, the underlying mechanisms remain unknown. We therefore investigated the functions of L-glutamate (L-Glu) transporters, the most important machinery used to maintain low extracellular L-Glu concentrations, in hiPSC-derived neural cells. We also clarified the contribution of each L-Glu transporter subtype. At 63 days in vitro (DIV), we detected neuronal circuit functions in hiPSC-derived neural cells by a microelectrode array system (MEA). Exposure to 100 μM L-Glu for 24 hrs did not affect the viability of these 63 DIV neural cells. Pharmacological inhibition of excitatory amino acid transporter 1 (EAAT1) and EAAT2 blocked almost 100% of L-Glu uptake. In this condition, L-Glu exposure dramatically decreased cell viability. These results suggest that in hiPSC-derived neural cells, EAAT1 and EAAT2 are predominant L-Glu transporters, and their uptake potentials are stronger than those of primary cultures of rodent neurons. Furthermore, hiPSC-derived neural cells may be useful for screening drugs that target L-Glu transporters.

In a dynamic production processes, mechanical degradation poses a significant challenge, impacting product quality and process efficiency. This paper explores a novel approach for monitoring degradation in the context of viscose fiber production, a highly dynamic manufacturing process. Using causal discovery techniques, our method allows domain experts to incorporate background knowledge into the creation of causal graphs. Further, it enhances the interpretability and increases the ability to identify potential problems via changes in causal relations over time. The case study employs a comprehensive analysis of the viscose fiber production process within a prominent textile industry, emphasizing the advantages of causal discovery for monitoring degradation. The results are compared with state-of-the-art methods, which are not considered to be interpretable, specifically LSTM-based autoencoders, showcasing the alignment and validation of our approach. This paper provides valuable information on degradation monitoring strategies, demonstrating the efficacy of causal discovery in dynamic manufacturing environments. The findings contribute to the evolving landscape of process optimization and quality control.

There are increasing calls in education for deeper integration of disciplines and better preparation for the personal and job challenges of a fast-changing and smarter society. Thus, we need to search for new effective didactic strategies. However, current classrooms are isolated. They practically never connect. This hinders the exchange of ideas. It inhibits imitation and recombination, the basic blocks of cultural evolution and innovation. In this paper, we analyze online inter-class tournaments. These are lessons where entire elementary or middle school classes interconnect synchronously and play an educational game. These are new types of academic activities, and only possible thanks to digital communication technology. In this paper, we examine four online tournaments, we analyze how feasible it is to carry them out and the benefits they bring. One tournament is for teaching machine learning and statistics. The second one teaches the conservation of momentum in physics and an engineering optimization challenge. The third tournament is for learning to solve word problems. The fourth one is for teaching natural and sexual selection along with developing statistical and population thinking. We found that these inter-class tournaments are feasible to implement in schools and that they are a promising mechanism to facilitate imitation, recombination, and innovation of teaching strategies.

With the rise of powerful computational technologies, healthcare systems are going through a paradigm shift to the era of healthcare 5.0, also known as" smart healthcare". This new-age healthcare system not only enhances the life of patients but also aims to reduce healthcare costs significantly. People's health data collected through various means, including various Internet of Things (IoT) devices, is too sensitive to be regulated by particular organisations owing to increasing privacy and security threats. The sheer size of data makes it difficult for centralised bodies to regulate, due to which third-party involvement is introduced, which again poses threats to the privacy of the data holder. Motivated by the abovementioned gaps, we propose a decentralised approach using Ethereum blockchain technology and Oasis protocol. The patient-driven solution approach effectively solves the privacy problem by providing complete control of data to the owner. Along with this, byproducts such as fine-grained access control and on-chain data processing capabilities are also obtained.

Earthworm invasions often reduce biodiversity and affect the ability of ecosystems to perform ecosystem functions. Over the past few decades, European lumbricide species have spread widely in natural habitats in Western Siberia, without completely displacing the native species. The aim of the present experiment is to study the survival, reproductive potential, vertical distribution, abundance, and biomass of Aporrectodea caliginosa and Lumbricus rubellus invasive for the region and the native species Eisenia nordenskioldi and their influence on each other. For this purpose, winter and vegetation experiments were conducted in mesocosms simulating the real situation of invasions in the same communities on the same types of soils with the same amount and composition of litter. The authors found that the native species was significantly inferior to A. caliginosa in reproduction rate, number of offspring, and final biomass, but had an advantage over L. rubellus. The native species was positively influenced by the presence of A. caliginosa. In the experiment, there was a significant rejuvenation of the populations of the studied species, an increase in abundance and relative mass under interaction conditions compared to mono variants. The native species had advantages over the invasive species in terms of winter survival. The natural volume of litter used in the experiment was insufficient for L. rubellus. According to the results of the experiment, it can be assumed that the spread of L. rubellus will continue to be limited to non-freezing biotopes rich in organic matter. A. caliginosa will spread in natural communities and agrocenoses of Western Siberia.

Repetitive nature of the ribosomal DNA (rDNA) gene makes the sequencing of hundreds copies of mammalian 45S rDNA (about 45-kb per copy) extremely difficult and its assembly is often excluded. Increasing evidence shows that 45S rDNA variations (copy number or single nucleotide), structural ribosomal RNA (rRNA) transcript variants, and non-structural rRNA transcripts (sense and anti-sense long noncoding rRNAs that include promoter rRNAs, and rRNA-derived fragments) play essential roles in mammalian development and diseases. Complete pictures of the hundreds copies of 45S rDNA and their rRNA transcripts require further innovation in sequencing techniques that include bioinformatics. The advancements in mammalian rDNA and rRNA sequencings and the discoveries of novel functions of the rDNA variants and rRNA transcripts are discussed here.

To define and evaluate the areas of consideration concerning in identifying the critical factors that top universities in Nueva Ecija, Philippines can be used for triangulating the courses of actions that can be applied to improve the current practices of universities towards its combat to the COVID–19 disease is the primary objective of this study. The researchers used a descriptive design of methodology by using questionnaire–checklist to scientifically describe the situation, problems, phenomenon, or program, or provide information about certain issues related to the virus outbreak. The respondents of the study were faculty and staff of five established universities in Nueva Ecija, Philippines wherein the researchers employed a non–probability sampling technique to be logically assumed as the representative of the entire population. The results of the study shown that the top universities in Nueva Ecija have made efforts to ensure the safety of university workers by complying with the Inter–Agency Task Force (IATF) protocols. It can be inferred, in reality, that there are some areas that must be improved especially when it comes to ensuring the welfare of the personnel who are still reporting to work even in this time of the pandemic. The researchers suggested an enhancement plan that can be adapted by these universities to resolve the concerns of the faculty and staff especially in reducing the spread of the virus without sacrificing the day–to–day transactions of the academic institutions.

The aim of this study was to assess if the ovine articular cartilage serine proteinase inhibitors (SPIs) were related to the Kunitz inter-α-trypsin inhibitor (ITI) family. Ovine articular cartilage was finely diced and extracted in 6M urea and SPIs isolated by sequential anion exchange, HA affinity and Sephadex G100 gel permeation chromatography. Selected samples were also subjected to chymotrypsin and concanavalin-A affinity chromatography. Eluant fractions from these isolation steps were monitored for protein and trypsin inhibitory activity and pooled fractions assessed by affinity blotting using biotinylated trypsin to detect active SPIs and by Western blotting using antibodies to α1-microglobulin, bikunin, TSG-6 and 2-B-6 (+) CS stub epitope generated by chondroitinase-ABC digestion. This identified 2-B-6 (+) positive 220-250,120, 58 and 36 kDa SPIs. The 58 kDa SPI contained α1-microglobulin, bikunin and chondroitin-4-sulphate stub epitope consistent with its identity as the α1-microglobulin-bikunin (AMBP) precursor and was also isolated by concanavalin-A lectin affinity chromatography indicating it had N-glycosylation. Kunitz protease inhibitor (KPI) species of 36, 26, 12 and 6 kDa could be autolytically generated by prolonged storage of the aforementioned 120 and 58 kDa SPIs; chymotrypsin affinity chromatography also generated the 6kDa SPI. KPI domain 1 and 2 SPIs were separated by concanavalin lectin affinity chromatography, domain 1 displayed affinity for this lectin indicating it had N-glycosylation. KPI 1 and 2 both displayed potent inhibitory activity towards trypsin, chymotrypsin, kallikrein, leucocyte elastase and cathepsin G. Localisation of versican, lubricin and HA in the surface regions of articular cartilage represented probable binding sites for the ITI SPs with likely importance in the preservation of joint function.

The accurate virus detection, strain discrimination, and source attribution of contaminated food items remains a persistent challenge because of the high mutation rates anticipated to occur in foodborne RNA viruses, such as Hepatitis A virus (HAV). This has led to predictions of the existence of more than one sequence variant between the hosts (inter-host) or within an individual host (intra-host). However, there have been no reports of intra-host variants from an infected single individual, and little is known about the accuracy of the single nucleotide variations (SNVs) calling with various methods. In this study, the presence and identity of viral SNVs, either between HAV clinical specimens or among a series of samples derived from HAV clone1-infected FRhK4 cells, were determined following analyses of nucleotide sequences generated using next-generation sequencing (NGS) and pyrosequencing methods. The results demonstrate the co-existence of inter- and intra-host variants both in the clinical specimens and the cultured samples. The discovery and confirmation of multi-viral RNAs in an infected individual is dependent on the strain discrimination at the SNV level, and critical for successful outbreak traceback and source attribution investigations. The detection of SNVs in a time series of HAV infected FRhK4 cells improved our understanding on the mutation dynamics determined probably by different selective pressures. Additionally, it demonstrated that NGS could potentially provide a valuable investigative approach toward SNV detection and identification for other RNA viruses.

Recently emerging data-driven citizen sciences need to harness increasing amount of massive data with varying quality. This paper develops essential theoretical frameworks and example models and examine its computational complexity for interactive data-driven citizen science within the context of guided self-organization. We first define a conceptual model that incorporates quality of observation in terms of accuracy and reproducibility, ranging between subjectivity, inter-subjectivity, and objectivity. Next, we examine the database's algebraic and topological structure in relation to informational complexity measures, and evaluate its computational complexities with respect to exhaustive optimization. Conjectures of criticality are obtained on self-organizing processes of observation and dynamical model development. Example analysis is demonstrated with the use of biodiversity assessment database, the process that inevitably involves human subjectivity for the management in open complex systems.

The effects of hypothermia on neonatal encephalopathy may vary regionally, spatially, and cytopathologically in the gyrencephalic neocortex with manifestations potentially influenced by seizures that alter the severity and distribution of neuropathology. We developed a neonatal piglet survival model of hypoxic-ischemic (HI) encephalopathy and hypothermia with continuous encephalographic (cEEG) monitoring for seizures to study injury in neocortex. Neonatal piglets were randomized to naïve, HI-normothermia (NT), overnight hypothermia (HT) initiated 2 hours after HI, sham-NT, or sham-HT treatments. Some piglets within sham and HI groups received cEEG monitoring during recovery. Survival was 2-7 days (piglets were unmedicated and those with poor recovery and unresolving seizures were euthanized early); there was no differences in survival among groups (p>0.078). Neuropathology was assessed by hematoxylin and eosin staining and immunohistochemistry for RNA Binding FOX-1 Homolog 3 (Rbfox3/NeuN). Normal and ischemic-necrotic neurons were counted (layers II-VI collectively) in somatosensory, motor, and prefrontal cortices, identified by cytoarchitecture and connectomics, and in inferior parietal cortex by layer. Seizure burden was determined. HI-NT piglets had reduced normal/total neuron ratio and increased ischemic-necrotic/total neuron ratio relative to naïve, sham-NT, and sham-HT piglets in anterior and posterior motor and somatosensory cortices. Frontal cortex was vulnerable in the prefrontal lateral bank after HI-NT with ischemic-necrosis. HI-HT piglets had higher normal/total neuron ratios and lower ischemic-necrotic/total neuron ratios than HI-NT piglets in anterior/posterior motor and somatosensory cortices. Total normal neuron density in layer III of inferior parietal cortex was reduced in HI-NT piglets compared to sham piglets and was protected by HT. Laminar analysis of Rbfox3 in somatosensory cortex revealed three types of neurons: Rbfox3-positive/normal, Rbfox3-positive/ischemic-necrotic, and Rbfox3-depleted. HI piglets had increased Rbfox3-depleted/total neuron ratio in layers II and III compared to sham-NT. Cortical neuron Rbfox3-depletion was partly rescued by HT. Seizure burden was more severe in HI piglets compared to sham piglets, but HI-NT and HI-HT piglets were similar. We conclude that 1) the neonatal piglet neocortex has a suprasylvian spatial vulnerability to HI and seizures; 2) HT protects against neuropathology in functionally different regions of the neonatal gyrencephalic neocortex; 3) neurons in neonatal neocortex have a limited cytopathology repertoire seen by H&E staining; 4) higher seizure burden correlates with more ischemic-necrotic neurons in somatosensory cortex; 5) seizure presence associates with damage spread to inferior parietal cortex; 6) seizure presence is insensitive to HT, and 7) Rbfox3 immunophenotyping identifies a novel neuronal RNA splicing protein nuclear-depletion pathology that appears reversible by HT. This work demonstrates that HT protection of neocortex in neonatal HI is topographic and laminar, seizure unmitigating, and restores depleted neuronal RNA splicing factor.

The inter-tip times (ITTs) of tipping-bucket rain gauges potentially provide the highest-resolution intensity data that can be acquired from this type of gauge. At an intensity of 100 mm h-1, a typical gauge with a sensitivity of 0.2 mm of rainfall would be expected to tip every 7.2 seconds. However, TBRGs are often equipped with syphons, to reduce the dynamic calibration error that results from continued (and unmeasured) inflow to a bucket as it tips. This increases the accuracy of rainfall depth recording, but the time to fill and empty the syphon can reduce the ability of a TBRG to respond to (and for the ITTs to reflect) short-term intensity fluctuations. This ability is already limited by the discretisation arising from the filling and emptying of the buckets themselves. Laboratory tests with controlled water inflow rates were performed using two high-quality TBRGs, one a 'straight-through' design and the other syphon-equipped. These confirmed that at all intensities at which the syphon operates, a regular sequence of fixed-duration ITTs (such as the 7.2 s mentioned above) does not occur. Rather, the ITTs are perturbed by the syphon cycling. The gauges were also co-located in the field, and linked to carefully synchronised event data loggers. Data collected during several rainfall events revealed differences in the ITTs, and again confirm that the ITT sequence of a syphon-equipped TBRG exhibits artefacts related to syphon operation, that are not present in the 'straight-through' data. These artefacts can result in ITT differences of many minutes, depending on the rainfall intensity, and are problematic for the use of ITTs to estimate intensity. Peaks and troughs in the intensity profile also differed between the two gauges. It is recommended that in the application of TBRGs for studies where short-term intensity data are required, 'straight-through' gauges should be used, and syphon-equipped gauges avoided.

Facial expression recognition is crucial for understanding human emotions and nonverbal communication. With the growing prevalence of facial recognition technology and its various applications, accurate and efficient facial expression recognition has become a significant research area. However, most previous methods have focused on designing unique deep-learning architectures while overlooking the loss function. This study presents a new loss function that allows simultaneous consideration of inter- and intra-class variations to be applied to CNN architecture for facial expression recognition. More concretely, this loss function reduces the intra-class variations by minimizing the distances between the deep features and their corresponding class centers. It also increases the inter-class variations by maximizing the distances between deep features and their non-corresponding class centers, and the distances between different class centers. Numerical results from several benchmark facial expression databases, such as Cohn-Kanade Plus, Oulu-Casia, MMI, and FER2013, are provided to prove the capability of the proposed loss function compared with existing ones.

More and more people quantify their sleep using wearables and are getting obsessed in their pursuit of optimal sleep (“orthosomnia”). However, it is criticized that many of these wearables are giving inaccurate feedback and even can lead to negative daytime consequences. Acknowledging these facts, we here aim to extend previous findings [] in a new sample of 136 self-reported poor sleepers by implementing optimization procedures to minimize erroneous classification when ambulatory sensing sleep. Firstly, here, we introduce an advanced interbeat-interval (IBI) quality control using a random forest method to account for wearable recordings in naturalistic and more noisy settings. We further aim to improve sleep classification by opting for a loss function model instead of overall epoch-by-epoch accuracy to avoid model biases towards the majority class (i.e., “light sleep”). Using these implementations, we compare the classification performance between the optimized (loss function model) and the accuracy model. We use signals derived from PSG, one-channel ECG, and two consumer wearables: the ECG breast belt Polar® H10 (H10) and the Polar® Verity Sense (VS), an optical Photoplethysmography (PPG) heart-rate sensor. Results reveal high overall accuracy for the new model for ECG (86.3 %, κ=.79), H10 (84.4%, κ=.76), and VS (84.2%, κ=.75) with intended improvements in deep sleep and wake. In addition, the new optimized model displays moderate to high correlations and agreement with PSG on primary sleep parameters, while measures of reliability, expressed in intra-class correlations, suggest excellent reliability for most sleep parameters. Finally, it is demonstrated that the new model is still classifying sleep accurately in 4-classes in users taking heart-affecting and/or psychoactive medication which can be considered a prerequisite for use also in high age groups and/or with common disorders. Further improving and validating sleep stage classification algorithms with affordable wearables may resolve existing scepticism and open the door for such approaches in clinical practice.

Abstract:The objects of fine-grained image categories(e.g., bird species) are various subclass under different categories. Because the differences between subclass are very subtle and most of them are concentrated in multiple local areas, the task of fine-grained image recognition is very challenging. At the same time, some fine-grained networks tend to focus on a certain region when judging the target category, resulting in the lack of other auxiliary regional features. To this end, Inception V3 is used as the backbone network, and an enhanced and complementary fine-grained image classification network is designed. While adopting the method of reinforcement learning to obtain more detailed fine grain image features, the complementary network can obtain the complementary discriminant area of the target through the method of attention erasure to increase the network's perception of the overall target. Finally, experiments are conducted on CUB-200-2011, FGVC Aircraft and Stanford dogs three open datasets. The experimental results show that the proposed model has better performance.

Nowadays, frameworks and models are critical to enabling organizations to identify their current sustainability integration into business and to follow up on these initiatives over time. In this context, the maturity models offer a structured way of analyzing how a supply chain meets specific sustainability requirements and which areas demand attention to reach maturity levels. This study proposes a five-level maturity model to help supply chains identify their level of engagement with sustainability practices combining three perspectives: intra and inter-organizational sustainability practices, triple-bottom-line approach and critical areas for sustainability. All the steps followed in constructing the maturity model were based on a literature review, and case studies supported its improvement, application, and testing. The proposed model presents many advantages, such as being used as a self-assessment tool, a roadmap for sustainability behaviour improvement, and a benchmarking tool to evaluate and compare standards and best practices among organizations and supply chains.

The mechanism of brain information processing unfolds within spatial and temporal domains inherently linked to the concept of symmetry. Biological evolution, beginning with the prevalent molecular chirality, results in the handedness of cognitive and psychological functions (the phenomena known as biochirality). The key element in the chain of chirality transfer from the downstream to upstream processes is the pyramidal neuron (PyrN) morphology-function paradigm (archetype). The most apparent landmark of PyrN is the geometry of the cell soma. However, “why/how PyrN soma gains the shape of quasi-tetrahedral symmetry” has never been explicitly articulated. Resolving the above inquiry is only possible based on the broad-view assumption that encoding 3D-space requires specific 3D-geometry of the neuronal detector and corresponding network. Accordingly, our hypothesis states that if the primary function of PyrNs, at the organism level, is sensory space perception, then the pyramidal shape of soma is the best evolutionary-selected geometry to support sensory-motor coupling.

Autistic spectrum disease (ASD) is an increasingly common diagnosis nowadays with a prevalence of 1-2% in most countries. Its complex causality – a combination of genetic, immune, metabolic and environmental factors - is translated into pleiomorphic developmental disorders of various severity, which have in common two main aspects: repetitive, restrictive behaviors, and difficulties in social interaction varying from awkward habits and verbalization to complete lack of interest from the ASD child for the outside world. The wide variety of ASD causes also makes it very difficult to find a common denominator – a disease biomarker and medication – and currently there is no commonly used diagnostic and therapeutic strategy besides clinical evaluation and psychotherapy.It is known that inflammation is present in a majority of ASD children, and blood inflammatory markers, together with metabolic, electrophysiological markers and imagistics are useful for ASD diagnostic validation and treatment; however, they tend to leave out a sizeable proportion of ASD kids who do not have such modifications. Genetic testing – whole exome sequencing or targeted profiling on about 500 ASD-linked genes- may also provide good insight into pathophysiology, however many times its results are more restrictive rather than offering additional therapeutic options.Here we describe a new biomarker for ASD - the neuron-specific enolase (NSE) - which was elevated above the normal clinical range (less than 16.3 ng/mL) in the vast majority of ASD kids tested in our study (40 of 41, or 97.5%). This finding opens up a new direction for diagnostic confirmation, dynamic evaluation and therapeutic intervention for ASD kids.

Activation Functions are crucial parts of the Deep Learning Artificial Neural Networks. From the Biological point of view, a neuron is just a node with many inputs and one output. A neural network consists of many interconnected neurons. It is a “simple” device that receives data at the input and provides a response. The function of neurons is to process and transmit information; the neuron is the basic unit in the nervous system. Carly Vandergriendt (2018) stated the human brain at birth consists of an estimated 100 billion Neurons. The ability of a machine to mimic human intelligence is called Machine Learning. Deep Learning Artificial Neural Networks was designed to work like a human brain with the aid of arbitrary choice of Non-linear Activation Functions. Currently, there is no rule of thumb on the choice of Activation Functions, “Try out different things and see what combinations lead to the best performance”, however, sincerely; the choice of Activation Functions should not be Trial and error. Jamilu (2019) proposed that Activation Functions shall be emanated from AI-ML-Purified Data Set and its choice shall satisfy Jameel’s ANNAF Stochastic and or Deterministic Criterion. The objectives of this paper are to propose instances where Deep Learning Artificial Neural Networks are SUPERINTELLIGENT. Using Jameel’s ANNAF Stochastic and or Deterministic Criterion, the paper proposed four classes where Deep Learning Artificial Neural Networks are Superintelligent namely; Stochastic Superintelligent, Deterministic Superintelligent, and Stochastic-Deterministic 1^st and 2^nd Levels Superintelligence. Also, a Normal Probabilistic-Deterministic case was proposed.

This paper is about to estimate the suspended sediment transport amount in the streams flowing into the Sapanca Lake Basin. There are 12 subsidiary streams flowing into the Sapanca Lake Basin. With the aim of estimating the suspended sediment transport in 2012-204 in these subsidiary streams, measurements belonging the parameters such as level, cross sectioning, flow rate, temperature and suspended sediment were made monthly. Along the measurement period, weather conditions were above seasonal normal and precipitations decreased. In order to estimate the suspended sediment amount by using results of the measurement obtained, Artificial Neuron Network (ANN), Sediment Rating Curve (SRC) and Multiple Linear Regression (MLR) models were used for different scenarios. It was seen that artificial neuron networks yielded the most accurate results among the models.

Amyotrophic lateral sclerosis (ALS) is also called "motor neuron disease”. In this review, we propose that ALS is not just a neuromotor disorder, but begins as a disorder of P53-modulated skeletal muscle metabolism, leading to failures at the energy state of the cells, incorrect redox states, motor denervation, and a loss of muscle fibers. Motoneurons die as a consequence of the lack of muscular feedback, and the oligomeric TDP43 aggregates progressively and relentlessly lead to mistakes in peripheral immune self-tolerance sustained over time. An effective treatment has not been found for this devastating pathology, as for 152 years the target has not been accurately defined. Scientists and doctors should consider new knowledge regarding ALS and consider immunomodulatory therapies that, based on genetic analysis and symptoms, can be combined with compounds that regulate metabolism and promote the elimination of useless organelles and cells. What if ALS could be cured as a result of seeing motor neuron disease differently? This review aims to develop that goal and change the paradigm of our understanding of ALS.

Wingless-type MMTV integration site (Wnt) signaling is one of the most critical pathways in developing and adult tissues. In the brain, Wnt signaling contributes to different neurodevelopmental aspects ranging from differentiation, axonal extension, synapse formation, neurogenesis and neuroprotection. Canonical Wnt signaling is mediated mainly by the multifunctional β-catenin protein which is a potent co-activator of transcription factors such as Lymphoid Enhancer Factor (LEF) and T Cell Factor (TCF). Accumulating evidence points to dysregulation of Wnt/β-catenin signaling in major neurodegenerative disorders. Here I focus on a “Wnt/β-catenin-glial connection” in Parkinson’s disease (PD), the most common movement disorder characterized by the selective death of midbrain dopaminergic (mDAergic) neuronal cell bodies in the subtantia nigra pars compacta (SNpc) and gliosis. I will summarize the work of the last decade documenting that Wnt/β-catenin signaling in partnership with glial cells is critically involved in each step and at every levels in the regulation of nigrostriatal DAergic neuronal health, protection and regeneration in the MPTP mouse model of PD, focusing on Wnt/β-catenin signaling to boost a full neurorestorative program in PD.

We aim to investigate if serum levels of microRNAs: miR-126, mir-197 and mir-223, previously implicated in cardiometabolic disease, are reproducibly associated with incident-diabetes (inc-DM), incident-cardiovascular disease (inc-CVD) and with carotid atherosclerosis (measured for the maximum thickness of the intima-media of the carotid bulb (IMT)). The microRNAs were measured, one: in serum of 553 subjects from the baseline exam of the Swedish prospective cohort, Malmö Diet and Cancer Study (MDC-CC), with 169 subjects who developed CVD and 140 DM (16 years follow-up) and, two: in 1221 subjects from the Malmö Offspring Study (MOS), with 14 de-veloped CVD and 12 DM (3.7 years follow-up). Multivariate logistic and linear regression models were used to investigate the relationship of serum-concentrations of the microRNAs and inc-DM, inc-CVD, IMT-bulb respectively. In MDC-CC, miR-126 showed significant positive association with inc-DM (p= 0.01) whereas in fully adjusted model, the association was borderline significant (p= 0.05). The results were not replicated in MOS. There was no consistent significant association between the microRNAs with IMT or inc-CVD in any cohort. Our results do not support previous reports on significant associations between these microRNAs and the risk of CMD, as they were not reproducible in our cohorts. In addition, the directionality of any associations found were not consistent with those previously reported.

The Performance Assessment for California Teachers (PACT) is a high stakes summative assessment that was designed to measure pre-service teacher readiness. We examined the inter-rater reliability (IRR) of trained PACT evaluators who rated 19 candidates. As measured by Cohen’s weighted kappa, the overall IRR estimate was .17 (poor strength of agreement). IRR estimates ranged from -.29 (worse than expected by chance) to .54 (moderate strength of agreement); all were below the standard of .70 for consensus agreement. Follow up interviews of 10 evaluators revealed possible reasons we observed low IRR, such as departures from established PACT scoring protocol, and lack of, or inconsistent, use of a scoring aid document. Evaluators reported difficulties scoring the materials that candidates submitted, particularly the use of Academic Language. Cognitive Task Analysis (CTA) is suggested as a method to improve IRR in the PACT and other teacher performance assessments such as the edTPA.

As a combination of both concepts of innovation and environmental development, green innovation is of great significance to the sustainable development of the country and industry. Previous literatures have found the separate roles of green entrepreneurial orientation and inter-organizational learning in understanding green innovation issues. However, few studies have done a comprehensive analysis of integrating three streams of research: green entrepreneurial orientation, green innovation and supply chain learning capability. Based on the resource-based view and dynamic capability theory, we examine the direct of green entrepreneurial orientation on green innovation as well as indirect effect through the mediation of supply chain learning capability. Meanwhile, an empirical data set of 228 manufacturing companies in China (Shaanxi, Guangdong, Hebei, Jiangsu, and Shandong) was used to test our hypotheses. Findings from our empirical study suggest that supply chain learning capability partially mediates the positive relationships between green entrepreneurial orientation and its two consequences—green incremental innovation and green radical innovation. In addition, this research implies that when enterprise has a strong green entrepreneurial orientation, the enterprise should make an effort to enhance the level of supply chain learning capability so as to fully develop their green innovation.

Children’s beneficial relationships with animals are well known. Companion animals, particularly dogs have become an integral part of family life and children’s material culture. Aside the proven physiological benefits there is little research about what children say about their relationships with animals and how they describe them. In this paper we bring together both horse-human and dog-human interactions, finding common ground for understanding the complexity of human development, well-being and flourishing. Dogs in schools are fast becoming a trend in helping support and enhance children’s learning as well as their social and emotional well-being. Studies have shown that the very presence of a dog can increase children’s concentration, executive function and behavior. Also, equine therapy is gaining momentum and empirical studies are showing noteworthy benefits to children and young people. However, the lack of children’s voices means that the mechanisms for these benefits are somewhat unknown and unclear. In seeking to explore this, the authors utilize a visual, sensory and diffractive ethnographic approach to illuminate and illustrate, experiment and re-enact, how the children relate, share spaces and multiple subjectivities with their classroom canine, “Ted” and companion horse “Henry”. ”Henry” is part of a programme in which youngsters care for and engage in activities with horses.

Abstract The relationship between cancer and neurodegeneration has spurred extensive scientific discourse, challenging their historical classification as distinct disorders. While cancer signifies uncontrolled cellular proliferation and neurodegeneration marks progressive neuronal loss, recent insights highlight intriguing interconnections between these seemingly disparate conditions. Cancer entails perpetual signaling for growth, evasion of growth inhibitors, resistance to cell death, acquisition of replicative immortality, stimulation of blood vessel growth (angiogenesis), and initiation of invasion and metastasis. Conversely, investigations emphasize disrupted cellular energy regulation and evasion of immune surveillance as key traits arising from genome instability, mutations, and inflammation driving tumorigenesis. Neurodegeneration involves neuronal malfunction and depletion, synaptic impairment, and protein abnormalities aggregations contributing to muscle atrophy and cognitive deficits. Varied clinical studies underscore contrasting correlations between cancer and neurodegeneration, hinting at mirrored molecular pathways that foster cell resilience or vulnerability. Research explores cellular signaling in tumorigenesis, shared with neurodegenerative disorders. Aberrant expression or mutations in crucial genes implicated in neurodegeneration also surface in cancer contexts. Debates persist on the nature of the relationship between cancer and neurodegeneration, contemplating inverse associations or shared pathways. Understanding their complex interplay, encompassing genetics, cellular mechanisms, and environmental influences, remains pivotal in unraveling their connections. This review explores the intriguing perspective that neurodegeneration and cancer might share fundamental genetic links, delving into potential implications for their onset and progression.

Intelligent transportation systems (ITS) have recently evolved rapidly, which requires development of highly trustworthy and effective communication technologies for uses, including vehicle-to-vehicle (V2V) and vehicle-to-everything (V2X) communication; where Orthogonal Frequency Division Multiplexing (OFDM) is regarded as a strong candidate and highly popular option technique among these methods. However, the movement of vehicles introduces Doppler frequencies which produce inter-carrier interference (ICI), that is frequently occurs in V2X channels. This interference has the potential to compromise the integrity of subcarrier orthogonality within OFDM, leading to lower-quality communication and an increased likelihood of data transmission errors. When employing channels with doubly dispersive fading, OFDM necessitates the usage of a complex equalization based on the minimum mean-square error (MMSE) equalizer, which requires channel matrix inversion. Several low-complexity equalizers for OFDM have been developed and are based on band factorization, time domain LSQR (Least-Square QR) iterative computing, and banded minimum mean squared error (BMMSE). This paper proposes Conjugate Gradient Least Squares (CGLS), which is a novel iterative computation algorithm integrated with nonlinear equalizers. The suggested nonlinear equalization technique determines the trade-off between computations and performance. According to simulation data, the suggested nonlinear equalizer performs better than the current BMMSE and linear CGLS algorithms across doubly dispersive fading channels.

Malaria is one of the leading causes of illnesses and deaths in Africa at large and Nigeria in particular, especially amongst pregnant women and children under the age of five years. Our research revealed that though the government has deployed so many intervention systems to contend with this death-causing vector—the mosquitoes, malaria related deaths (MRDs) have continued to increase. This is because people have not sufficiently adopted those intervention systems to protect themselves. Further enquiries into the ineffective compliance of the people to the intervention systems revealed that the interventions are passive in nature. Based on these, we set up three measurable research outcomes to enable us to determine the appropriateness of persuasive technology in solving the malaria problem. We technically avoided a one-size-fits-all design approach and adopted Participatory System Design (PSD) and User-Centered Design (UCD) approaches in our system design methodologies. Well-structured questionnaires were used to extract information from the participants. The data obtained from the research survey was used in modeling the intervention system. The research was conducted in three phases: baseline, development and deployment of an intervention system—the Malaria Prevention and Control Support System (MPCSS), and an evaluation study to determine the performance of the intervention system. The research led to the following achievements: (1) encouraged an increase in the number of people who participated in malaria prevention and control activities by lowering the rate of malaria cases from 96.9% to 68.5% and increasing ownership of mosquito nets from 54% to 85.5%; (2) demonstrated that persuasive technology could be used to increase public awareness and knowledge of a given subject as noted in our evaluation result; and (3) demonstrated that persuasive technology is a veritable active intervention to combat malaria.

Ecologists use the net biotic interactions among plants to predict fundamental ecosystem features. Following this approach, ecologists have built a giant body of theory founded on observational evidence. However, due to the limitations that a phenomenological approach raises both in empirical and theoretical studies, an increasing number of scientists claim the need for a mechanistic understanding of plant interaction outcomes, and a few studies have taken such a mechanistic approach. In this synthesis, we propose a modeling framework to study the plant interaction mechanistically. We first establish a conceptual ground to frame plant-plant interactions, and then, we propose to formalize this research line theoretically developing a family of individual-based, spatially-explicit models in which biotic interactions are an emergent property mediated by the interaction between plants’ functional traits and the environment. These models allow researchers to evaluate the strength and sign of biotic interactions under different environmental scenarios and thus constitute a powerful tool to investigate the mechanisms underlying facilitation, species coexistence, or the formation of vegetation spatial patterns.

The demand of high data rate and ubiquitous coverage in heterogeneous cellular (HetNets) is increasing progressively. In order to meet this demand, sophisticated model having applied interference reduction scheme and cell association technique is needed. The small base station (sBS)are deployed inside the broadcasting area of macro base station (mBS), in heterogeneous cellular networks (HetNets). Since mBS has high transmission power therefore a large number of users get connected with mBS. This causes disproportion of load distribution across the HetNets. For load balancing users from high power mBS are migrated to low power sBS to increase network capacity and to decrease the load from mBS. This results in interference in the communication signal because of strong mBS Interference. Hence, we need interference management technique to mitigate interference and user association and to efficiently use sBSs’ resources. Inter-cell interference (ICI) limit the HetNets’ performance. Additionally, there exist deliberate jamming interference which depends on jammers transmission power and its proximity with the target, which notably degrades the network performance. In this paper, we employ reverse frequency allocation scheme (RFA) to reduce inter cell interference, deliberate jamming interference and to accomplish load balancing. The proposed setup is analyzed inquisitively and with the help of simulations. The result shows reduction in interferences as well as balance of load distribution in the network achieved by employing RFA scheme together with cell association.

The critical period (CP) phenomenon in language development ranks among the 125 conundrums facing scientists in the 21st century, according to Science. While the phenomenon itself has been noncontroversial in first language acquisition, it still warrants an adequate explanation. Predicated on language acquisition as a complex process, questions among the first to be raised include: How do children accomplish this remarkable feat in such a short amount of time? And how do nature and nurture come together to influence language learning? In second language acquisition, however, both the notion of CP, albeit popular, and its empirical evidence have remained contested to this date - among the questions, whether the observed evidence counts as CP-specific and/or whether or not it warrants an isomorphic attribution to maturational constraints. Entwined in this debate are two well-established facets of inter-learner differential attainment. The first is that there exists a stark difference in ultimate attainment between younger and older learners. A second facet is the vast differences in ultimate attainment among older learners. In this article, adopting a social physics approach, we mathematically establish both the relationship between nature and nurture contributions and the presence of a critical period, and, at once, tender a parsimonious and probable theory for the twin phenomena of inter-learner differential attainment.

Modular steel buildings (MSBs) interlocking inter-module connections (IMCs) have piqued researchers’ interest. However, the existing literature has not yet studied the optimisation of its plate thicknesses. This paper, therefore, focuses on optimising interlocking (IMCs) plate thickness in (MSBs), leveraging previous experimental and numerical simulation methodologies. Various numerical models for four MSBs interlocking (IMCs) with plate thicknesses (4 mm, 6 mm, 10 mm, and 12 mm) were developed under compression loading conditions. The study’s novelty lay in its comprehensive parametric analysis, which evaluated the slip phenomenon in (MSBs) connections and introduced a slip prediction model validated against empirical data. Further innovative machine learning approach was utilised to predict slip values based on applied force through a random forest regression model trained using the 'Treebagger' function. Sensitivity analysis and comparisons with alternative methods were utilised to underscore the reliability and applicability of the findings. The results showed that 11.03 mm was the optimal plate thickness for interlocking (IMCs) in modular steel buildings, with up to 8.08% reduced material costs. Increasing plate thickness boosts its deformation resistance by up to 50.75%. ‘TreeBagger’ random forest for anomaly detection and machine learning improves slip prediction up to 7% at higher force levels.

The development of novel coherent and brilliant sources, such as soft X-ray Free Electron Laser (FEL) and High Harmonic Generation (HHG) enables new ultrafast analysis of the electronic and structural dynamics of a wide variety of materials. Soft X-ray FEL delivers high brilliance beams with short pulse duration, high spatial coherence and photon energy tunability. In com-parison with FELs, HHG X-ray sources are characterized by a wide spectral bandwidth and few to sub-femtosecond pulses. The approach will lead to time-resolved reconstruction of molecular dynamics, shedding light on different photochemical pathways. The high peak brilliance of soft X-ray FELs facilitates investigations in nonlinear regime, while the broader spectral bandwidth of the HHG sources may provide the simultaneous probing of multiple components. Significant technical breakthroughs in these novel sources are under way to improve brilliance, pulse dura-tion, and to control spectral bandwidth, spot size, and energy resolution. Therefore, in the next few years, the new generation of soft X-ray sources combined with novel experimental tech-niques, new detectors, and computing capabilities will allow the study of several extremely-fast dynamics, such as vibronic dynamics. In the present review, we shortly discuss recent devel-opments in experiments, performed with soft X-ray FELs and HHG sources, operating near car-bon K-absorption edge, being a key atomic component in biosystems and soft materials. Differ-ent spectroscopy methods such as time-resolved pump-probe techniques, nonlinear spectrosco-pies and photoelectron spectroscopy studies have been addressed in an attempt of a better un-derstanding of fundamental physico-chemical processes

Connected and Autonomous Vehicle (CAV) combines technologies of autonomous vehicle (AV) and connected vehicles (CV) to develop quicker, more reliable and safer traffic. Artificial Intelligence (AI) based CAV solutions play significant roles in sustainable city. The convergence imposes stringent security requirements for CAV safety and reliability. In practice, vehicles are developed with increased automation and connectivity. Increased automation increases the reliance on the sensor-based technologies and decreases the reliance on driver; increased connectivity increases the exposures of vehicles vulnerability and increases the risk for an adversary to implement a cyber-attack. Much work has been dedicated to identifying the security vulnerabilities and recommending mitigation techniques associated with different sensors, controllers, and connection mechanisms, respectively. However, there is an absence of comprehensive and in-depth studies to identify how the cyber-attacks exploit the vehicles vulnerabilities to negatively impact the performance and operations of CAV. In this survey, we set out to thoroughly review the security issues introduced by AV and CV technologies, analyze how the cyber-attacks impact the performance of CAV, and summarize the solutions correspondingly. The impact of cyber-attacks on the performance of CAV is elaborated from both viewpoints of intra-vehicle system and inter-vehicle system. We pointed out that securing the perception and operations of CAV would be the top requirement to enable CAV to be applied safely and reliably in practice. Also, we suggested to utilize cloud and new AI methods to defend against smart cyber-attacks on CAV.

Due to the rapid developments in aquaculture industry, Artemia franciscana, originally an American species, has been intentionally introduced to the Eurasia, Africa and Australia. In the present study, we used a partial sequence of the mitochondrial DNA Cytochrome Oxidase subunit I (mt-DNA COI) gene and genomic fingerprinting by Inter-Simple Sequence Repeats (ISSRs) to determine the genetic variability and population structure of Artemia populations (indigenous and introduced) from 14 different geographical locations in Western Asia. Based on the haplotype spanning network, Artemia urmiana has exhibited higher genetic variation than native parthenogenetic populations. Although A. urmiana represented a completely private haplotype distribution, no apparent genetic structure was recognized among the native parthenogenetic and invasive A. franciscana populations. Our ISSR findings have documented that despite invasive populations have lower variation than source population in Great Salt Lake (Utah, USA), they have significantly revealed higher genetic variability compare to the native populations in Western Asia. According to the ISSR results, the native populations were not fully differentiated by the PCoA analysis, but the exotic A. franciscana populations were geographically divided in four genetic groups. We believe that during the colonization, invasive populations have experienced substantial genetic divergences, under new ecological conditions in the non-indigenous regions.

Anterior-tooth (ANT) contacts induce short latency reflex inhibition of human jaw-closing muscles. The jaw is a rigid class 1 lever for pinpoint-targeting muscle force into a single bite-point, the pivoting food particle. See-saw reflex movements around the food particle fulcrum multiply the food-crushing force. Unpredictable jolts of reaction force caused by food-crushing are subjected to the rostral ANT and caudally to the two articulate ends of the jaw triangle. Compression/distraction strains of food-crushing must be monitored and inhibited by withdrawal reflexes. The mesencephalic ganglion (Vmes), neural myelin sheath, and muscle stretch receptors evolved subsequently to the advent of jaws to improve the velocity of proprioceptive and withdrawal reflexes. In mammalians, the spindles of the taut motor units, stretched by the food-fulcrum send excitatory monosynaptic feedback for the efferent neurons of the respective ipsilateral muscle units, via Vmes. In the Vmes, the spindle-input-mediating afferent neurons are coupled with another source of afferent feedback, which is also excitatory, from the back-tooth (BAT) mechanoreceptors. The two sources of excitatory pulses are summated and targeted for the efferent neurons to boost the stretched and taut motor units. Likewise, the afferent feedback from ANT mechanoreceptors is also coupled in the Vmes with concomitant feedback from spindles. The ANT output, however, is inhibitory to negate the excitatory feedback from the stretched jaw-muscle units. The inhibitory feed from ANT temporarily blocks the excitatory potential of masticatory motor efferent neurons to protect the ANT and jaw-joints from inadvertent strains. The inhibitory inputs from ANT alternate with the excitatory inputs from BAT to determine which jaw-closing muscle units are activated or inhibited at any given instant of food-crushing. The Vmes exists in all jawed vertebrates, and its’ evolution was probably motivated by demands for the control of bite force. The monosynaptic unilateral food-crushing excitatory and inhibitory reflexes (UFCR) override the coexisting bilaterally executed feed for jaw muscles from the central nervous system. Hypothesis: The Vmes-mediated UFCR combine neural inputs from tooth contacts with concomitant feedback from muscle stretch receptors for the control of mammalian food-crushing bite force.

Microglial cells, the resident macrophages of the CNS, exist in a process-bearing, ramified/surveying phenotype under resting conditions. Upon activation by cell damaging factors they get transformed to an amoeboid phenotype releasing various cell products including pro-inflammatory cytokines, chemokines, proteases, reactive oxygen/nitrogen species and the excytotoxic ATP and glutamate. In addition, they engulf pathogenic bacteria or cell debris and phagocytose them. However, already resting/surveying microglia has a number of important physiological functions in the CNS; they e.g. shield small disruptions of the blood-brain barrier by their processes, dynamically interact with synaptic structures and clear surplus synapses during development. In neurodegenerative illnesses they aggravate the original disease by a microglia-based compulsory neuroinflammatory reaction. Therefore, the blockade of this reaction improves the outcome of Alzheimer’s disease, Parkinson’s disease, multiple sclerosis, amyotrophic lateral sclerosis, etc. The function of microglia is regulated by a whole array of purinergic receptors classified as P2Y12, P2Y6, P2Y4, P2X4, P2X7, A2A, A3, and being targets for endogenous ATP, ADP, or adenosine. ATP is sequentially degraded by the ecto-nucleotidases and 5’-nucleotidase enzymes to the weak adenosine agonist inosine as an end-product. The appropriate selective agonists/antagonists for purinergic receptors as well as the respective enzyme inhibitors may profoundly interfere with microglial functions and reconstitute the homeostasis of the CNS disturbed by neuroinflammation.

Through an investigation of recently discovered Incantation of Wish-Fulfillment amulets from the Silla kingdom, this paper reveals that early Korea had more diverse forms of dhāraṇī practices than previously assumed. This paper’s analysis of these amulets from Korea contributes toward filling the gap in our current understanding of the material practice pertaining to the Incantation of Wish-Fulfillment widely practiced in medieval East Asia. Based on an interdisciplinary analysis of the two amulet sheets of the Incantation of Wish-Fulfillment from Silla, this paper explored hitherto unknown aspects of early Korean dhāraṇī practice. Previously, the only material dhāraṇī practice in early Korea was thought to be the enshrinement of textual relics in pagodas based on the Pure Light Incantation, which has little connection to contemporaneous Chinese dhāraṇī practice. However, the newly discovered Incantation of Wish-Fulfillment amulets, whose date this paper inferred to be between the eighth and ninth century, show that the Unified Silla also had a dhāraṇī practice closely linked to the Chinese practice. However, unlike the Chinese Incantation of Wish-Fulfillment amulets that were buried in tombs, the Silla amulets were likely enshrined in one of the pagodas erected on Mount Nam, Gyeongju. At the same time, the Silla epigraph from Myogilsang Pagoda at Haeinsa shows that the Incantation of Wish-Fulfillment was placed in the pagoda so as to wish for good afterlives of the soldiers who died at the battle, suggesting that placing the Incantation of Wish-Fulfillment in a pagoda had a function similar to that of burying the Chinese amulet in the tomb.

Bayesian nonlinear mixed effects models for data in the form of continuous, repeated measurements from a population, also known as Bayesian hierarchical nonlinear models, are a popular platform for analysis when interest focuses on individual specific characteristics and relevant uncertainty quantification. Due to the limitation of computational power, this framework was relatively dormant until the late 1980s, but in recent years, the statistical research community saw vigorous development of new methodological and computational techniques for these models, the emergence of software, and wide application of the models in numerous industrial and academic fields. This article presents an overview of the formulation, interpretation, and implementation of Bayesian nonlinear mixed effects models and surveys recent advances and applications.

Although floods, as well as other natural disasters, can be considered relevant causes of intra-generational inequalities, the frequent catastrophes and the resulting damages to territory reflect the generalized indifference about inter-generational justice. Societal concerns, such as land protection, typically involve the administrative system performing proactive policies in the perspective of inter-generational solidarity, but subsidiarity has made more and more independent the local communities. As a consequence, the attention toward the long run effects – typically concerning the territorial system, as a whole, at the geographical scale – has been dispersed, and the proactive policies coming from the central government has became more ineffective. Regarding the case of the flood happened in 2009 in the Fiumedinisi-Capo Peloro hydraulic basin, in the northeastern part of Sicily, Italy, we propose an economic valuation – carried out by performing the method of the imputed preferences – in order to compare the expenses incurred by the public authorities responsible for protecting the territory to the costs of the rehabilitation of the damaged areas. Some considerations about the economic significance of the proactive policies for the arrangement of territory are addressed according to the role played by the social discount rate in the inter-temporal economic calculation.

Antisense oligonucleotides (ASOs) are short oligodeoxynucleotides designed to bind to specific regions of target mRNA. ASOs can modulate pre-mRNA splicing, increase levels of functional proteins and decrease levels of toxic proteins. ASOs are being developed for the treatment of several diseases, including motor neuron diseases (MNDs), a group of neurodegenerative disorders characterised by the loss of motor neurons, including spinal muscular atrophy (SMA), amyotrophic lateral sclerosis (ALS) and spinal and bulbar muscular atrophy (SBMA). The biggest success has been the ASO known as nusinersen, the first effective therapy for SMA, able to improve symptoms and slow disease progression. Another success is tofersen, an ASO designed to treat ALS patients with SOD1 gene mutations. Both ASOs have been approved by the FDA and EMA. On the other hand, ASO treatment in ALS patients with the C9orf72 gene mutation did not show any improvement in disease progression. The aim of this review is to provide an up-to-date overview of ASO research in MND, from preclinical studies to clinical trials and, where available, regulatory approval. We highlight the successes and failures, underline the strengths and limitations of the current ASO research, and suggest possible approaches that could lead to more effective treatments.

Traumatic spinal cord injury (SCI) elicits an acute inflammatory response which comprises numerous cell populations. It is driven by the immediate response of macro-phages and reactive M1 microglia, which triggers activation of genes responsible for the dysregulated microenvironment within the lesion site and in the spinal cord parenchyma immediately adjacent to the lesion. Recently published data indicate that microglia induces astrocyte activation and determines the fate of astrocytes. Conversely, astrocytes have the potency to trigger microglial activation and control their cellular functions. Here we review current information about the release of diverse signaling molecules (pro-inflammatory vs anti-inflammatory) in individual cell phenotypes (microglia, astrocytes, blood inflammatory cells) in acute and subacute SCI stages, and how they contribute to delayed neuronal death in a the surrounding spinal cord tissue which is spared and functional but reactive. In addition, temporal correlation in progressive degeneration of neurons and astrocytes and their functional interactions after SCI are discussed. Finally, the review highlight the time-dependent transformation of reactive mi-croglia (M1) and astrocytes (A1) into their neuroprotective phenotypes (M2a, M2c and A2) which are crucial for spontaneous post-SCI locomotor recovery. We also provide sug-gestions on how to increase functional outcome after SCI and discuss key therapeutic approaches.

This study presents the interaction with human host metabolism of SARS-CoV-2 ORF7b protein (43 aa), using a Protein-Protein-Interaction Networks analysis. After pruning, we selected from BioGRID the 51 most significant proteins among 2,753 proven interactions and 1,708 interactors, specific to ORF7b. We used these proteins as functional seeds and we got a significant network of 551 nodes via STRING. We performed topological analysis and calculated topological distributions by Cytoscape. Seven high ranked proteins as hub and seven as bottleneck following a hub-and-spoke network-architectural-model were found. Through this interaction model, we identified significant GO-processes (5,057 terms in 15 categories) induced in human metabolism by ORF7b. High statistical significance processes of dysregulated molecular cell mechanisms by the action of ORF7b were discovered. We detected disease-related human proteins and their involvement in metabolic roles, how they relate in a distorted way to signaling and/or functional systems, in particular intra- and inter-cellular signaling systems and the molecular mechanisms that supervise to programmed cell death, with mechanisms similar to that of cancer metastasis diffusion. A cluster analysis showed 10 compact and significant functional clusters, where two of them overlap in a Giant-Connected-Components core of 206 total nodes. These two clusters contain most of the high-rank nodes. ORF7b mainly acts through these two clusters, inducing most of the metabolic dysregulation. We conducted a co-regulation, transcriptional analysis by hub and bottleneck proteins. This analysis allowed us to define the transcription factors and miRNAs that control the high-ranking proteins and the dysregulated processes, within the limits of the poor knowledge that these sectors still impose.

Satellite altimetry is successfully developing during the past three decades for the sea level, ocean dynamics, coastal oceanography, planetary waves, ocean tides, wind and wave, ice cover, Earth’s gravity field, and climatology research. We propose a new essential add-on of satellite altimetry related to the peculiarities of the orbits of the Topex/Poseidon and Jasons’ satellite missions which were not mentioned before in the scientific publications. Derived subsets of “self-crossover” and “inter-crossover” points in sub-polar latitudes are discussed in detail in the context of water exchange, and wind-wave dynamics, and potential challenges to be solved. The relatively short time lags between measurements at these crossovers provide additional information on anomalies of magnitudes and directions of ocean currents, and characteristics of wind-driven waves. Resulting data snapshots with constant space and time intervals can be regarded as time series of virtual buoys, an analog of continuous buoy measurements of the sea level, wind speed, and wave height. Areas of the World Ocean where these specific crossovers occur are described in the context of water exchange, wind wave studies, and potential challenges to be solved. The value of these special crossovers for studies and monitoring of the sub-polar seas is illustrated by a case study.

The intensive care units in North West London are part of one of the oldest critical carenetworks in the UK, forming a mature and established strategic alliance to shareresources, experience and knowledge for the benefit of its patients. North WestLondon saw an early surge in COVID-19 admissions, which urgently threatened thecapacity of some of its intensive care units even before the UK government announcedlockdown. The pre-existing relationships and culture within the network allowed itsmembers to unite and work rapidly to develop agile and innovative solutions, protectingany individual unit from becoming overwhelmed, and ultimately protecting its patients.Within a short 50-day period 223 patients were transferred within the network todistribute pressures. This unprecedented number of critical care transfers, combinedwith the creation of extra capacity and new pathways, allowed the region to continue tooffer timely and unrationed access to critical care for all patients who would benefitfrom admission. This extraordinary response is a testament to the power and benefitsof a regionally networked approach to critical care, and the lessons learned maybenefit other healthcare providers, managers and policy makers, especially in regionscurrently facing new outbreaks of COVID-19.

The Science-Sustainability poses an interdisciplinary paradox. On the one hand, the science for sustainability has increased in OECD economies in and in China as well as in the US in particular; on the other hand; the sustainability situation has worsened (Co2 emission has risen). On the face value, the adverse correlation shows a paradox. However, without explicating the science-sustainability relationship, it leads to a premature conclusion. In this study, we have drawn on three concrete questions for concrete answers. First, whether and how interdisciplinary sciences—energy science and environmental science—contribute to the sustainability. Second, whether and how the Sino-US inter-institutional analysis varies in the science-sustainability paradox. The empirical analysis from a panel data in the interdisciplinary and inter-institutional context show mixed patterns in three ways. First, the increase in the environmental science shows an improvement in the sustainability; the energy science shows a decline in the sustainability. Second, the Chinese environmental science has a comparative advantage to American environment science for the sustainability development, and the Chinese energy science has a comparative disadvantage to the US in the sustainability development. Third, the environmental science mediates the energy science in the science-sustainability relationships. Standing alone, the increase in the energy science harms sustainability; mediated by environmental science, it benefits sustainability. The study explains the adverse role of energy science in Jevons Paradox. The study also offers some policy paths for further research how capitalisms differently innovate, form strategies, and implement the practice.

Consciousness is a special type of interaction between subjects exchanging by lingua quanta (phonemes). A set of lingua quanta composes a thesaurus placed on the edge of chaos. Its library is a memory, modification of which is due to tuning of memristive neural elements scattered in the brain volume. The memristive neural model takes into consideration two types of neurons - excitatory and inhibitory and the current leakage, all at the body temperature, T = 309 K. At such temperatures only heavy ions like hydrogen ions - protons can pass robustly through the water medium of the brain. The robust ion transport is proton water wires supported by the Grotthuss mechanism. Final aims of the ions are the gap junctions (electric synapses) linking nearest neurons. Following these observations, a model of excitable nervous tissue is constructed. Namely, a difference mapping on the basis of sigmoid curves can reproduce chaotic modes of neural activity proved by positive values of the Lyapunov exponent. The edge of chaos is placed near the bifurcation boundary dividing the chaos and the periodic convulsive activity typical at the epileptic discharges. In this region the self-sustained spiral waves occur. An intermittent activity of the competing excitatory and inhibitory neurons is observed on the edge of chaos. The intermittent electrical activity of neural tissues is demonstrated by records both from different literature issues and records made by the author together with DR. A. Dudkin on slices of CA1 field of the hippocampus.

To keep the global navigation satellite system functional during extreme conditions, it is a trend to employ autonomous navigation technology with inter-satellite link. As in the newly built BeiDou system (BDS-3) equipped with Ka-band inter-satellite links, every individual satellite has the ability of communicating and measuring distances among each other. The system also has less dependence on the ground stations and improved navigation performance. Because of the huge amount of measurement data, centralized data processing algorithm for orbit determination is suggested to be replaced by a distributed one in which each satellite in the constellation is required to finish a partial computation task. In current paper, the balanced extended Kalman filter algorithm for distributed orbit determination is proposed and compared with whole-constellation centralized extended Kalman filter, iterative cascade extended Kalman filter, and increasing measurement covariance extended Kalman filter. The proposed method demands a lower computation power however yields results with a relatively good accuracy.