The Cosmic Ray Extremely Distributed Observatory (CREDO) is a newly formed, global collaboration dedicated to observing and studying cosmic rays (CR) and cosmic ray ensembles (CRE): groups of a minimum of two CR with a common primary interaction vertex or the same parent particle. The CREDO program embraces testing known CR and CRE scenarios, and preparing to observe unexpected physics, it is also suitable for multi-messenger and multi-mission applications. Perfectly matched to CREDO capabilities, CRE could be formed both within classical models (e.g. as products of photon-photon interactions), and exotic scenarios (e.g. as results of decay of Super Heavy Dark Matter particles), their fronts might be significantly extended in space and time, and they might include cosmic rays of energies spanning the whole cosmic ray energy spectrum. CRE are expected to be partially observable on Earth even if the initiating interaction or process occurs as far as ~1 Gpc away. They would have a footprint composed of at least two extensive air showers with correlated arrival directions and arrival times. Since CRE are mostly expected to be spread over large areas and, because of the expected wide energy range of the contributing particles, CRE detection might only be feasible when using available cosmic ray infrastructure collectively, i.e. as a globally extended network of detectors. Thus, with this review article, the CREDO Collaboration invites the astroparticle physics community to actively join or to contribute to the research dedicated to CRE, and in particular to share any cosmic ray data useful for the specific CRE detection strategies.

The Cosmic-Ray Extremely Distributed Observatory (CREDO) is a project dedicated to global studies of extremely extended cosmic-ray phenomena, the cosmic-ray ensembles (CRE), beyond the capabilities of existing detectors and observatories. Up to date cosmic-ray research has been focused on detecting single air showers, while the search for ensembles of cosmic-rays, which may overspread a significant fraction of the Earth, is a scientific terra incognita. Instead of developing and commissioning a completely new global detector infrastructure, CREDO proposes approaching the global cosmic-ray analysis objectives with all types of available detectors, from professional to pocket size, merged into a worldwide network. With such a network it is possible to search for evidences of correlated cosmic-ray ensembles. One of the observables that can be investigated in CREDO is a number of spatially isolated events collected in a small time window which could shed light on fundamental physics issues. The CREDO mission and strategy requires active engagement of a large number of participants, also non-experts, who will contribute to the project by using common electronic devices (e.g. smartphones). In this note the status and perspectives of the project is presented.

Low-energy cosmic rays (LECRs) play a crucial role in the formation of planetary systems, and detecting and reconstructing the properties of early LECRs is essential for understanding the mechanisms of planetary system formation. Given that LECRs interact with the surrounding medium to produce nuclear de-excitation line emissions with energy mainly within 0.1–10 MeV, which are unaffected by stellar wind modulation, these gamma-ray emissions can accurately reflect the properties of LECRs. This study introduces an innovative method for using gamma-ray emissions to infer LECR properties. We employed the Parker transport equation to simulate the propagation and spectral evolution of LECRs in a protoplanetary disk and calculated the characteristic gamma-ray emissions resulting from interactions between LECRs and disk material. These gamma-ray emissions encapsulate the spectral information of LECRs, providing a powerful tool to reconstruct the cosmic ray environment at that time. This method, supported by further theoretical developments and observations, will fundamentally enhance our understanding of the impact of CRs on the origin and evolution of planetary systems and address significant scientific questions regarding the cosmic ray environment at the origin of life.

The latest experimental measurements of cosmic rays (CRs) have discovered a series of anomalies, including the hardening of the nuclear spectra at R ∼200 GV followed by softening at R ∼10 TV and complicated energy dependence of anisotropy from GeV to PeV. Recent works have demonstrated nearby sources are crucial for these anomalies of spectra and anisotropy. In this work, we analyze the contributions of five nearby sources within 1 kpc around solar system to the spectra and anisotropy, finally find out which source is the best candidate source. In the calculation process, we also introduce the anisotropic diffusion of CRs induced by the local interstellar magnetic field (LIMF) nearby the solar system based on spatial-dependent propagation (SDP) model. As a result, we find Geminga SNR source can simultaneously account for CR spectra and anisotropy, whereas the other sources can not . Measurements of CR anisotropy and spectra by experiments such as LHAASO and HAWC are expected to test this scenario in the near future.

In relativity, the Newtonian concepts of velocity and acceleration are observer-dependent quantities that vary with the chosen frame of reference. It is well established that in the comoving frame, cosmic expansion is currently accelerating; however, in the rest frame, this expansion is actually decelerating. In this paper, we explore the implications of this distinction. The traditional measure of cosmic acceleration, denoted by q, is derived from the comoving frame and describes the acceleration of the scale factor a for a 3D space-like homogeneous sphere. We introduce a new parameter q_E representing the acceleration experienced between observers within the light cone. By comparing q_E to the traditional q using observational data from Type Ia supernovae (SN) and the radial clustering of galaxies and quasars (BAO)—including the latest results from DESI2024—our analysis demonstrates that q_E aligns more closely with these data. The core argument of the paper is that Λ—regardless of its origin—creates an event horizon that divides the manifold into two causally disconnected regions analogous to conditions inside a black hole’s interior, thereby allowing for a rest-frame perspective q_E in which cosmic expansion appears to be decelerating and the horizon acts like a friction term. Such a horizon suggests that the universe cannot maintain homogeneity outside. The observed cosmological constant Λ can then be interpreted not as a driver of new dark energy or a modification of gravity but as a boundary term exerting an attractive force, akin to a rubber band, resisting further expansion and preventing event horizon crossings. This interpretation calls for a reconsideration of current cosmological models and the assumptions underlying them.

This research explores the intricate relationship between gravitational and cosmic redshift phenomena, unveiling a profound understanding of how light behaves as it traverses the cosmos. The study begins with an examination of gravitational redshift, a well-established concept occurring when photons move away from massive gravitational sources, such as stars within galaxies. Gravitational redshift, expressed as λ/λ₀, manifests within the gravitational influence and extends to the boundary of the observed "zero-gravity sphere" enveloping galaxies. Within this remarkable zero-gravity sphere, gravitational effects persist, while the antigravity influence of dark energy remains negligible. As a result, gravitational redshift dominates, and cosmic redshift is notably absent within the sphere. Photons within this sphere maintain their constant speed 'c' and undergo gravitational redshift exclusively. However, as photons exit the zero-gravity sphere at a distance 'r' equivalent to the source star's radius, they encounter the onset of cosmic redshift, quantified as {(λ_obs - λ_emit)/ λ_emit}. Cosmic redshift blends with gravitational redshift, forming the effective redshift of the photon. Critically, the effective cosmic redshift surpasses gravitational redshift, illuminating a profound revelation: photons traverse a greater "light-traveled distance" than their proper distance from the source. In essence, cosmic redshift signifies that photons move across their intended distances at their intrinsic speed c, while the expanding universe introduces a relative distance expansion, influenced by antigravity. This research delves into the intricate dance between gravitational and cosmic redshift, shedding light on their remarkable implications for our comprehension of the expanding universe.

In developing his cosmological model of 1917, de Sitter theoretically predicted the phenomenon of cosmological redshift (the de Sitter effect), which he did long before the discovery of this phenomenon in observations. The de Sitter effect is gravitational by its nature, as it is due to differences between the coordinate systems of the observer and the distant source. However, the relationship between the redshift and distance derived from the de Sitter metric is at odds with observations, since this relationship is nonlinear (quadratic) for small redshifts, while the observed relationship between the same quantities is strictly linear. This paper discusses the possibility that cosmological redshift is gravitational by its nature, as in de Sitter’s 1917 model. At the same time, here, as in de Sitter’s model, an elliptical space is used, the main characteristic of which is the identification of its antipodal points. But, unlike de Sitter’s model, here, in order to ensure a strict linear dependence of the redshift on distance, the origin of the reference system is transferred to the observer’s antipodal point. The Schwarzschild-de Sitter metric used in this model allows you to estimate the curvature of space from observational data. To do this, a theoretical Hubble diagram is built within the framework of the model with the Schwarzschild-de Sitter metric, which is compared with observations from the Pantheon+ catalogue of type Ia supernovae and the Amati catalogue of gamma-ray bursts in the redshift range of 0<z<8. As a results of the comparison, the lower estimate of the radius of curvature of space turned out to be quite large: 2.3·1015 Mpc. This means that the observational data indicate a negligible curvature of space.

Background: Aging is commonly accepted as a time period of declining heath. Aims: This review aimed to examine the research base concerning the use of term ‘successful aging’, a process and outcome deemed desirable, but challenging to attain. A second was to provide related information to demonstrate how health professionals as well as individuals can aim for a ‘successful aging’ process and outcome, despite the presence of disabling osteoarthritis. Methods: Information specifically focusing on ‘successful aging’ and the concept of improving opportunities for advancing ‘successful aging’ despite osteoarthritis was sought. Results: Among the many articles on ‘successful aging’, several authors highlight the need to include, a broader array of older adults into the conceptual framework. Moreover, conditions such as osteoarthritis should not necessarily preclude the individual from attaining a personally valued successful aging outcome. Conclusion: Pursuing more inclusive research and research designs, and not neglecting to include people with chronic osteoarthritis can potentially heighten the life quality of all aging individuals, while reducing pain and depression, among other adverse aging and disability correlates among those with osteoarthritis

In the realm of computer vision, semantic segmentation is the task of recognizing objects in images at the pixel level. This is done by performing a classification of each pixel. The task is complex and requires sophisticated skills and knowledge about the context to identify objects’ boundaries. The importance of semantic segmentation in many domains is undisputed. In medical diagnostics, it simplifies the early detection of pathologies, thus mitigating the possible consequences. In this work, we provide a review of the literature on deep ensemble learning models for polyp segmentation and we develop new ensembles based on convolutional neural networks and transformers. The development of an effective ensemble entails ensuring diversity between its components. To this end, we combine different models (HarDNet-MSEG, Polyp-PVT, and HSNet) trained with different data augmentation techniques, optimization methods, and learning rates, which we experimentally demonstrate to be useful to form a better ensemble. Most importantly, we introduce a new method to obtain the segmentation mask which is more suitable for combining transformers in an ensemble. In our extensive experimental evaluation, the proposed ensembles exhibit state-of-the-art performance.

In the realm of Lithium-ion batteries, issues like material aging and capacity decline contribute to performance degradation or potential safety hazards. Predicting Remaining Useful Life (RUL) serves as a crucial method to assess the health of batteries, thereby enhancing reliability and safety. Currently hybrid approaches for batteries RUL estimation are prevalence and gained fruitful development. In this paper, a hybrid voting ensembles combining Gradient Boosting, Random Forest and K-Nearest Neighbors is proposed to predict the capacity fade trend and knee point. Finally, extensive experiments are conducted using CALCE CS2 datasets. According to the experimental results, the proposed approach supersedes the single deep learning approach for RUL prediction and the knee point is predicted accurately. Besides prediction purpose, this innovated approach can be also proposed to be integrated into the real-world application for wider usage.

Biofortification refers to the increase in the amount of essential vitamins or provitamins or minerals in crops to improve the nutritional status of the people, which is largely intended to alleviate the problem of micronutrient malnutrition. I argue that biofortification may not be an effective weapon to fight against the hidden hunger since it demonstrates limited capacity on nutritional enhancement and can negatively impact the socio-economic fabric of the society in many different ways. Finally, I suggest a couple of alternatives that might meet the challenge more efficiently than biofortified crops.

The atomic nucleus contains protons and neutrons surrounded by a structured electron cloud. Some combinations of protons and neutrons induce the nucleus to behave like a microscopic magnet, possessing a unique magnitude and orientation known as the nuclear magnetic moment (µ). When the numbers of protons and neutrons are both even then µ=0, but otherwise each nu-clide’s nuclear magnetic moment is unique. A second unique nuclear physical property relates to the nucleon binding energy (BE), which can be thought of as the energy between protons and neu-trons bound within the nucleus. The sequence of stable nuclides increases one nucleon at a time through 36Ar. The binding energy associated with the addition of each successive nucleon (∆BE) through this progression is unique. The hypothesis here is that the unique non-zero magnetic mo-ment and ∆ binding energy of each nuclide derive from its respective microscopic nuclear struc-ture, analogous to the way that the atomic physical properties of an element ultimately derive from its unique electron orbital structure. By extension, the identification of nuclear periodic pat-terns might eventually inform a theory of nuclear structure. The light, stable nuclides through 36Ar were arranged in ascending order according to atomic mass, and their nuclear magnetic mo-ments and binding energies were evaluated for periodic patterns. Fixed-period lengths from 4 through 18 nuclides per period were considered. These fixed periods, each of equal length, were stacked one upon the other and analyzed for vertical trends. The best evidence of periodicity in both µ and ∆BE converges precisely at the fixed 12-nuclide period. Implications for nuclear structure are discussed.

Semantic segmentation is a very popular topic in modern computer vision and it has applications to many fields. Researchers proposed a variety of architectures over time, but the most common ones exploit an encoder-decoder structure that aims to capture the semantics of the image and it low level features. The encoder uses convolutional layers, in general with a stride larger than one, to extract the features, while the decoder recreates the image by upsampling an using skip connections with the first layers. In this work, we use DeepLab as architecture to test the effectiveness of creating an ensemble of networks by randomly changing the activation functions inside the network multiple times. We also use different backbone networks in our DeepLab to validate our findings. We manage to reach a dice coefficient of 0.888, and a mean Intersection over Union (mIoU) of 0.825, in the competitive Kvasir-SEG dataset. Results in skin detection also confirm the performance of the proposed ensemble, which is ranked first with respect to other state-of-the-art approaches (including HardNet) in a large set of testing datasets. The developed code will be available at https://github.com/LorisNanni.

Abstract: The recently described perivascular unit (PVU) resides immediately adjacent to the true capillary neurovascular unit (NVU) in the postcapillary venule and contains the normal-benign perivascular spaces (PVS) and pathological enlarged perivascular spaces (EPVS). The PVS are important, in that, they also have recently been identified to be the construct and the conduit responsible for the delivery of metabolic waste from the interstitial fluid to the ventricular cerebrospinal fluid for disposal into the systemic circulation and has been termed the glymphatic system. Importantly, the outermost boundary of the PVS is lined by protoplasmic perivascular astrocyte endfeet (pvACef) that communicate with regional neurons. As compared to the well-recognized and described neurovascular unit (NVU) and NVU coupling, the PVU is less well understood and remains an emerging concept. The primary focus of this narrative review is to compare the similarities and differences between these two units and discuss each of their structural and functional relationships and how they relate not only to brain homeostasis but also how they may relate to the development of multiple clinical neurological disease states and specifically how they may relate to obesity, metabolic syndrome, and type 2 diabetes mellitus. Additionally, the concept and importance of a perisynaptic astrocyte coupling to the neuronal synapses with pre- and postsynaptic neurons will also be considered as a perisynaptic unit to provide for the creation of the information transfer in the brain via synaptic transmission and brain homeostasis. Multiple electron microscopic images and illustrations will be utilized in order to help explain these complex units.

The advent of modern satellite technology has transformed observational astronomy and astrophysics, offering unprecedented insights into the large-scale behavior of gravitation and challenging established cosmological models. This technological progress has reinvigorated the study of relativistic cosmology, leading to a critical reassessment of foundational assumptions, particularly the cosmological principle, which posits that the universe is homogeneous and isotropic on large scales. While this principle underpins the Standard Cosmological Model and the Friedmann-Lemaitre-Robertson-Walker metric, emerging data has increasingly been challenging its validity. Central to this investigation are the redshift-distance and light intensity-distance relations, essential for testing cosmological models. The integration of both parametric and nonparametric redshift models provides a more comprehensive analysis, addressing discrepancies in our understanding of the universe's structure and evolution. However, unresolved mysteries, particularly concerning dark matter and dark energy, complicate these models. This research critically examines the cosmological principle using the latest observational data and scrutinizes the Friedmann model's assumptions. The study shows that galaxy formation was most rapid in the early universe, especially within the redshift range of , with notable peaks around at and These two characteristic redshift values, predicted by our standard Friedmann redshift model used in this work, are confirmed by the observational data utilized in this research. The research also highlights that dark matter plays a significantly more critical role than dark energy in the process of galaxy formation. While dark energy primarily affects the large-scale expansion of the universe, dark matter seems to go beyond the domination of local galaxy formation and evolution of cosmic structures. These findings underscore the limitations of current models and contribute to the ongoing refinement of cosmological theories, offering a clearer understanding of the universe’s evolution.

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

Recently, much attention has been devoted to finding highly efficient and powerful activation functions for CNN layers. Because activation functions inject different nonlinearities between layers that affect performance, varying them is one method for building robust ensembles of CNNs. The objective of this study is to examine the performance of CNN ensembles made with different activation functions, including six new ones presented here: 2D Mexican ReLU, TanELU, MeLU+GaLU, Symmetric MeLU, Symmetric GaLU, and Flexible MeLU. The highest performing ensemble was built with CNNs having different activation layers that randomly replaced the standard ReLU. A comprehensive evaluation of the proposed approach was conducted across fifteen biomedical data sets representing various classification tasks. The proposed method was tested on two basic CNN architectures: Vgg16 and ResNet50. Results demonstrate the superiority in performance of this approach. The MATLAB source code for this study will be available at https://github.com/LorisNanni.

The fundamental divergence in foundation of modern physics lies in the incompatibility between quantum theory and relativity. This study created a relative continuum, found a mathematical tool for the cosmic continuum; proposed dark particle hypothesis, filled gap on minimum existence quantity particle; discovered new equivalence principle, bridged differences in foundation of physics; and established an ideal model, revealed deep essence of cosmic and material structure. In this model, any cosmic system is a continuum composed of existence continuum relative to the wavelength of bosons energy waves and its dimension continuum. This model provides new perspectives on the fundamental problems of physics and cosmology. Firstly, it elucidated the physical mechanism of bosons in fundamental interactions. Secondly, it reconstructed the understanding of the basic unit of the cosmic and material structure. Thirdly, it updated the inherent concepts about the existence form and existence dimension. Fourthly, it restored the causality truth of wave function collapse in quantum mechanics.

Air pollution is a serious global issue, responsible for approximately one in every nine deaths each year, ranking it among the greatest environmental hazards to human health. It is of particular concern in urban areas, where elevated pollutant concentrations and potential sufferers converge. Over one half of the world’s population presently lives in urban areas, and the urban population ratio is expected to reach 68% by 2050. Common air pollutants include particulate matter (PM), sulphur dioxide (SO2), ground-level ozone (O3), nitrogen oxide (NOx) and carbon monoxide (CO). While elevated rates of air pollution pose serious health risks for humans, outdoor plants can help reduce the harmful effects of air pollution by filtering and purifying the air around us.In this project Common Ivy, Aster and Miniature Andromeda plants were evaluated for air pollutant mitigation. In this study we developed a vegetation barrier model with the plant located in the middle of the greenhouse box, and air pollutant was sprayed on one side of the plant. Dispersion patterns of sprayed pollutants were tested with and without vegetation barrier. Measurements of carbon dioxide (CO2), Formaldehyde (HCHO), Total Volatile Organic Compounds (TVOC), and Particulate Matter (PM2.5/PM10) were taken before spraying, then at 0 and 30 minutes after spraying, using both monitors.The results show mitigation rates (in 177 ft3 of air after 30 min): for TVOC the minimum reduction is 5 mg/m3; for HCHO, 1 mg/m3; for CO2, 2000 ppm; for PM2.5, 2000 ug/m3; and for PM10 it was 1000 ug/m3.

Abstract Cerebral microbleed(s) (CMBs) are increasingly being viewed not only as a marker for cerebral small vessel disease (SVD) but also as having an increased risk for the development of stroke (hemorrhagic/ischemic) and aging-related dementia. Recently, brain endothelial cell activation and dysfunction and blood-brain barrier dysfunction and/or disruption have been shown to be associated with SVD, enlarged perivascular spaces, and the development and evolution of CMBs. CMBs are a known disorder of cerebral microvessels that are visualized as 3-5mm, smooth, round or oval, and hypointense (black) lesions seen only on T2*-weighted gradient recall echo or susceptibility-weighted sequences on MRI images. CMBs (a global problem) are known to occur with high prevalence in community-dwelling older individuals. Since our current global population is the oldest recorded in history and only expected to continue to grow, we can only expect the health care burdens associated with CMBs to also grow. CMBs should raise a red flag regarding the increased risk of large symptomatic neurologic intracerebral hemorrhages. Importantly, CMBs are also currently regarded as markers of diffuse vascular and neurodegenerative brain damage. Thus, it is essential that we try to learn as much as we can about their development, evolution, and their relation to impaired cognition, dementia, and neurodegeneration.

In computer vision and image analysis, Convolutional Neural Networks (CNNs) and other deep learning models are at the forefront of research and development. These advanced models have proven to be highly effective in tasks related to computer vision. One technique that has gained prominence in recent years is the construction of ensembles using Deep CNNs. These ensembles typically involve combining multiple pre-trained CNNs to create a more powerful and robust network. The purpose of this study is to evaluate the effectiveness of building CNN ensembles by combining several advanced techniques. Tested here are CNN ensembles constructed by replacing ReLU layers with different activation functions, employing various data augmentation techniques, and utilizing several algorithms, including some novel ones, that perturb network weights. Experimental results performed across many data sets representing different tasks demonstrate that our proposed methods for building deep ensembles produces superior results. All the resources required to replicate our experiments are available at https://github.com/LorisNanni.

Recent analyses of cosmic microwave background (CMB) maps have been interpreted as demonstrating that the Universe was born without an initial rotation. However, these analyses are based on unrealistic models and do not contain essential ingredients such as quantum effects, the strong, weak and gravitational interactions between the components, their intrinsic spins and magnetic moments, as well as primordial black holes. If the Universe was born spinning these effects would distribute the initial spin angular momentum among its components long before the CMB forms at recombination. A primordial spin would now appear as a nonzero total angular momentum of its components along the direction of the original spin, and a primordial large-scale rotation would no longer be apparent. The existence of a special axis or direction would break a fundamental symmetry assumed in general relativity, cosmic isotropy, and a net angular momentum implies a cosmic parity violation.

For applications in sensing and cavity-based quantum computing and metrology, open-access Fabry-Perot cavities – with an air or vacuum gap between a pair of high reflectance mirrors – offer important advantages compared to other types of microcavities. For example, they are inherently tunable using MEMS-based actuation strategies, and they enable atomic emitters or target analytes to be located at high field regions of the optical mode. Integration of curved-mirror Fabry-Perot cavities on chips containing electronic, optoelectronic, and optomechanical elements is a topic of emerging importance. Micro-fabrication techniques can be used to create mirrors with small radius-of-curvature, which is a prerequisite for cavities to support stable, small-volume modes. We review recent progress towards chip-based implementation of such cavities, and highlight their potential to address applications in sensing and cavity quantum electrodynamics.

The microvessel neurovascular unit with its brain endothelial cell (BEC) and blood-brain barrier remodeling is important in the development of impaired cognition in sporadic or late-onset Alzheimer’s disease (LOAD) and vascular dementia or vascular cognitive impairment and dementia including cerebral amyloid angiopathy in neurodegeneration. LOAD is considered to be the number one cause of dementia globally; however, when one considers the role of mixed dementia (MD) (the combination of both the amyloid cascade hypothesis and the vascular hypothesis of LOAD), it becomes apparent that MD is the number one cause. The microvessel BECs are the first cells in the brain to be exposed to the peripheral neurotoxins of the systemic circulation and are therefore the brain cells at the highest risk for early and chronic injury. Therefore, it is not surprising that microvessel BECs are the first cells to undergo injury and the response to injury wound healing mechanism and remodeling that is excessive and recurrent in the aging process plus other age-related diseases such as cerebro-cardiovascular disease, hypertension, type 2 diabetes mellitus, Parkinson’s disease, plus others. This narrative review explores the intricate relationship between microvessel remodeling, cerebral small vessel disease (SVD), and neurodegeneration as occurs in LOAD. Further, it discusses the current understanding of how microvessel dysfunction, disruption, and pathology contribute to the pathogenesis of LOAD and thus, highlights potential avenues for therapeutic interventions.

Introduction: Subtalar Arthroereisis (STA) is a surgical intervention for pediatric flexible flatfoot (PFF), primarily targeting hindfoot alignment by limiting excessive subtalar eversion. However, its effects on forefoot parameters remain underexplored. This study aims to investigate radiological changes following STA in pediatric patients. Materials and Methods: A retrospective analysis was conducted on consecutive patients treated with STA for PFF. First ray-related angles, including Hallux Valgus Angle (HVA) and Inter-Metatarsal Angle (IMA), alongside hindfoot radiological parameters such as Meary, Calcaneal Pitch, and Costa Bartani angles, were assessed. Subgroup analysis by gender was performed, and correlations between demographic and pre-operative radiological parameters were examined. Results: Forty-one patients (81 feet) with a mean age of 11.6 years were included, with a mean follow-up duration of 6.4 months. No significant differences were observed in first ray-related an-gles pre- and post-operatively, with mean IMA changing from 7.97° to 7.18° and mean HV angles from 9.51° to 8.66°. Noteworthy improvements were seen in flat foot angles, including Meary, Calcaneal Pitch, and Costa Bartani angles, postoperatively. Age subgroup analysis revealed similar trends in IMA and HVA changes between Group A (operated before peak growth) and Group B (operated later). Higher preoperative angles tended to improve, while lower preoperative IMA and HVA tended to worsen postoperatively, all remaining within normal ranges. Conclusion: STA showed positive radiological outcomes for PFF treatment, while negligible changes in first ray-related angles were observed. Age subgroup analysis indicated similar trends regardless of operation timing. Higher preoperative angles tended to improve, while lower preoperative angles tended to worsen postoperatively, despite all falling within non-pathological ranges. Further re-search is warranted to confirm this correlation.

We used an ultrasensitive, broadband optomechanical ultrasound sensor to study the acoustic signals produced by pressurized nitrogen escaping from a variety of small syringes. Harmonically related jet tones extending into the MHz region were observed for a certain range of flow (i.e., Reynolds number), in qualitative agreement with historical studies on gas jets emitted from pipes/orifices of much larger dimensions. For higher turbulent flow rates, we observed broadband ultrasonic emission in the ~ 0 – 5 MHz range, likely limited on the upper end by attenuation in air. These observations are made possible by the broadband, ultrasensitive response (for air-coupled ultrasound) of our optomechanical devices. Aside from their theoretical interest, our results could have practical implications for the non-contact monitoring and detection of early-stage leaks in pressured fluid systems.

The atomic structures of Zn and Na borophosphate glasses were studied by X-ray and neutron diffraction. Peaks assigned to the B−O, P−O, and O−O distances confirm that only BO4 units co-exist with the PO4 tetrahedra. The Zn−O and Na−O coordination numbers are found to be a little larger than four. The narrowest peaks of the Zn−O first-neighbor distances exist for the glasses along a line connecting the Zn(PO3)2 and BPO4 compositions (50 mol% P2O5) which is explained by networks of ZnO4, BO4, and PO4 tetrahedra with twofold coordinated oxygens. Calculated amounts of the available oxygen support this interpretation. Broadened peaks occur for glasses with lower P2O5 contents, consistent with the presence of threefold coordinated oxygens. The two distinct P−O peak components of the Zn and Na borophosphate glasses differ in their relative abundances which is interpreted by Na+ cations that coordinate oxygens in some P−O−B bridges, something not seen for the Zn2+ ions.

To identify objects in images, a complex set of skills is needed that includes understanding the context and being able to determine the borders of objects. In computer vision, this task is known as semantic segmentation and it involves categorizing each pixel in an image. It is crucial in many real-world situations: for autonomous vehicles, it enables the identification of objects in the surrounding area; in medical diagnosis, it enhances the ability to detect dangerous pathologies early, thereby reducing the risk of serious consequences. In this study, we compare the performance of various ensembles of convolutional and transformer neural networks. Ensembles can be created, e.g, by varying the loss function, data augmentation method or the learning rate strategy. Our proposed ensemble, which is based on the simple average rule, demonstrates exceptional performance on several datasets. All the resources used in this study are available online at the following GitHub repository: https://github.com/LorisNanni.

The recent Planck Legacy release confirmed the existence of an enhanced lensing amplitude in the cosmic microwave background (CMB) power spectra, which endorses the positive curvature of the early Universe with a confidence level exceeding 99%. In this study, the pre-existing curvature is incorporated to extend the field equations where the derived wave function of the Universe is utilized to model Universe evolution with reference to the scale factor of the early Universe and its radius of curvature upon the emission of the CMB. The wave function reveals both positive and negative solutions, implying that matter and antimatter of early Universe plasma evolve in opposite directions as distinct Universe sides. The wave function indicates that a nascent hyperbolic expansion is followed by a first phase of decelerating expansion away from early plasma during the first 10 Gyr, and then, a second phase of accelerating expansion in reverse directions, whereby both Universe sides free-fall towards each other under gravitational acceleration. Simulations of the predicted conformal curvature evolution demonstrate the fast orbital speed of outer stars owing to the external fields exerted on galaxies as they travel through conformally curved space-time. Finally, the wave function predicts an eventual time-reversal phase comprising rapid spatial contraction that culminates in a Big Crunch, signalling a cyclic Universe. These findings reveal that early plasma could have separated and evolved into distinct sides that collectively and geometrically influencing the Universe evolution, physically explanting the effects attributed to dark matter and energy.

Households and businesses are generating unprecedented levels of electrical and electronic wastes (e-waste), fueled by modernisation and rapid obsolescence. While the challenges imposed by e-waste are similar everywhere in the world, disparities in progress to deal with it exists; with developing nations such as South Africa lagging. The increase in e-waste generation increases the need to formulate strategies to manage it. This paper presents an overview of e-waste management on a global and South African scenarios with a specific case for Cathode Ray Tube (CRT) waste management practices in South Africa. CRTs present the biggest problem for recyclers and policy makers because they contain hazardous elements such as lead and antimony. Common disposal practices have been either landfilling or incineration. The research into the South African practices with regards to CRT waste management showed that there is still more to be done to effectively manage this waste stream. This is despite clear waste regulatory frameworks in the country. However, recent developments have placed e-waste as a priority waste stream, which should lead to intensified efforts in dealing with it. Overall, these efforts should aim to maximise diversion from landfilling and to create value-addition opportunities, leading to social and environmental benefits.

This short communication makes use of the principle of singular perturbation to approximate the ordinary differential equation (ODE) of prompt neutron (in the point kinetics model) as an algebraic equation. This approximation is shown to yield a large gain in computational efficiency without compromising any significant accuracy in the numerical simulation of primary coolant system dynamics in a PWR nuclear power plant. The approximate (i.e., singularly perturbed) model has been validated with a numerical solution of the original set of neutron point-kinetic and thermal–hydraulic equations. Both models use variable-step Runge–Kutta numerical integration.

The spin-torsion theory is a gauge theory approach to gravity that expands upon Einstein's general relativity (GR) by incorporating the spin of microparticles. In this study, we further develop the spin-torsion theory to examine spherically symmetric and static gravitational systems that involve free-falling macroscopic particles. We posit that the quantum spin of macroscopic matter becomes noteworthy on cosmic scales. We further assume that the Dirac spinor and Dirac equation adequately capture all essential physical characteristics of the particles and their associated processes. A crucial aspect of our approach involves substituting the constant mass in the Dirac equation with a scale function, allowing us to establish a connection between quantum effects and the scale of gravitational systems. This mechanism ensures that the quantum effect of macroscopic matter is scale-dependent and diminishes locally, a phenomenon not observed in microparticles. For any given matter density distribution, our theory predicts an additional quantum term, the quantum potential energy (QPE), within the mass expression. QPE induces time dilation, distance contraction, and thus mimics a gravitational well. When applied to cosmology, our theory yields a static cosmological model. The QPE serves as a counterpart to the cosmological constant introduced by Einstein to balance gravity in his static cosmological model. The QPE also offers a plausible explanation for the origin of the Hubble redshift (traditionally attributed to the universe's expansion). The predicted luminosity distance-redshift relation aligns remarkably well with SNe Ia data from the cosmological sample of SNe Ia. In the context of galaxies, QPE functions as the equivalent of dark matter. The predicted circular velocities align well with the rotation curve data from the SPARC (Spitzer Photometry and Accurate Rotation Curves database) sample. Importantly, our conclusions in this paper are reached through a conventional approach, with the sole assumption of the quantum effects of macroscopic matter on large scales, without the need for additional modifications or assumptions.

In this article, we introduce the concept of soft intervals, soft ordering and sequences of soft real numbers, and some of their structural properties are studied. The notion of soft Lebesgue measure on the soft real numbers has been introduced. Also, a correspondence relationship has been established between the soft Lebesgue measure and the classical Lebesgue measure. Furthermore, we have studied some exciting results and relations between the soft Lebesgue measure and the Lebesgue measure of soft real sets.

Building a widely distributed hotspot network is a very tedious task due to its complexity. Providing security, fully distributed network services, and cost-conscious impact are the major challenges behind this goal. To overcome these issues, we have presented a novel distributed hotspot network architecture with five layers that can provide large-scale hotspot coverage as an assimilated result. Our contributions to this new architecture highlight important aspects. First, scalability can be increased by including many Internet-of-Things (IoT) devices with sensors and Wi-Fi and/or LoraWAN connectivity modules. Second, hotspot owners can rent out their hotspots to create a distributed hotspot network in which the hotspots can act as an ordinary data gateway, a full-fledged hotspot miner, and a lightweight hotspot miner to earn crypto tokens as rewards for certain activities. Third, the advantages of Wi-Fi and LoraWAN can be seamlessly leveraged to achieve optimal coverage, higher network security, and suitable data transmission rate for transferring sensor data from IoT devices to remote application servers and users. Fourth, blockchain is used to enhance the decentralized behavior of the architecture presented here by providing immutability and independence from a centralized regulator and making the network architecture more reliable and transparent. The main feature of our paper is the use of the tau-computing paradigm along with hotspots to improve availability, Internet backhaul-agnostic network coverage, and synchronous update capability, and tau-aware leasing to strengthen and improve coverage. We also discuss the key challenges and future roadmap that require further investment and deployment.

Hydraulic conductivity is the key and one of the most uncertain parameters in groundwater modeling. The grid based numerical simulation require spatial distribution of sampled hydraulic conductivity at un-sampled locations in the study area. This spatial interpolation has been routinely performed using variogram based models (two-point geostatistics methods). These traditional techniques fail to capture the complex geological structures, provides smoothing effects and ignore the higher order moments of subsurface heterogeneities. In this work, a multiple-point geostatistics (MPS) method is applied to interpolate hydraulic conductivity data which will be further used in WASH123D numerical groundwater simulation model for regional smart groundwater management. To do this, MPS need ‘training images (TIs) as a key input. TI is a conceptual model of subsurface geological heterogeneity which was developed by using concept of ages, topographic slope as an index criteria and knowledge of geologist. After considerations of full physics of study area, an example shows the advantages of using multiple-point geostatistics compared with the traditional two-point geostatistics methods (such as Kriging) for the interpolation of hydraulic conductivity data in a complex geological formation.

The spectra and global distributions of the X-ray emissions generated by the solar wind charge-exchange (SWCX) process in the terrestrial magnetosheath are investigated based on a global hybrid model and a global geocoronal hydrogen model. The solar wind O6+ ions which are the primary charge state for oxygen ions in solar wind are considered. The line emissivity of the charge-exchange born O5+ ions are calculated by Spectral Analysis System for Astrophysical and Lab oratory (SASAL). It is found that the emission lines from the O5+ ranges from 105.607 to 118.291 eV with the strong line at 107.047 eV. We then simulated the magnetosheath X-ray emission intensity distributions with a virtual camera at two positions of north pole and dusk at six stages during the passing of a perpendicular interplanetary shock combined with a tangential discontinuity structure through the Earth’s magnetosphere. During this process, the X-ray emission intensity increases with time, and the maximum value is 27.11 keV cm-2 s-1 sr-1 on the dayside, which is 4.5 times that before the solar wind structure reaches the Earth. A clear shock structure can be seen in the magnetosheath and moves earthward. The maximum emission intensity seen at dusk is always higher than that seen at north pole.

Samarinda City is one of the most attractive cities in Borneo Island (Indonesia) and also as a capital city of EastBorneo Province. The expansion of urban areas becomes essential due to rapid population and housing demand. Base on the statistical report, the annual population growth rate is 0.018% from the year 2016-2017 with a total population of 843446 inhabitants. Many natural disasters occur in some areas in this city, especially flooding. This natural disaster occurs almost every year, many people suffered and forced to evacuate. In 2018 there is 3 flood event with 28311 people was suffered and evacuated, and 5170 houses were flooded [1]. During the flood event, it was very possible to gain damages to their property and make traffic stuck. One common way to reducing the damages is using Early Warning Systems (EWS). Early warning is a major element for disaster risk reduction, including damages. To prevent and mitigate the impact of a disaster, many countries had taken action to build various methods of a public warning system. An effective early warning system focused on people-centered and comprises the following element, such as risk knowledge, technical monitoring and service, communication and dissemination of warnings, and community response capability [2]. Related to the existing condition which Samarinda is a Muslim-dominated city and obviously has a lot of a number of mosques. This is a good potency to develop an early warning system because every mosque has a loudspeaker for echoing Adzan (Muslim prayer-calling). With this existing condition, the loudspeaker can be utilized as a flood outdoor-voice warning announcer. The aim of this study is to briefly introduce the strategy of dissemination early warning by utilizing mosques. The hope of early warning dissemination is giving enough time to the people to evacuate their property to reduce damages and possibly to giving information to avoiding traffic stuck (in a certain location)due to flooding. The results of this study can be used as input for decision-makers to develop effective flood management strategies and policies, especially in the case of an early warning system where not well-developed in Samarinda.

The main objective of this study is to find out the influence of cooperation and intra-specific competition in escaping predation through refuge of the prey population and the effect of the two intra-specific interactions on the dynamics of prey-predator systems. For this purposes, two mathematical models with Holling type-II functional response function have been proposed and analyzed. The first model includes cooperation among prey populations whereas the second one incorporates intra-specific competition. Existence conditions and stability of different equilibrium points of both models have been carried out for the qualitative behaviour of the systems. Refuge through intra-specific competition has a stabilizing role, whereas cooperation has a destabilizing role on the system dynamics. Periodic oscillations are observed in both the systems through Hopf bifurcation. From the analytical and numerical findings, we conclude that intra-specific competition affects the prey population and continuously checks the refuge class under a critical value, and thus it never becomes too large to cause predator extinction due to food scarcity. Conversely, cooperation leads maximum individuals to escape predation through the refuge so that predators will suffer from low predation success.

It is generally assumed that the universe expands only on large scales. For some time now, there has also been a well-founded assumption in the literature that cosmic expansion also exists in gravitationally bound systems. In this article we attempt to establish whether cosmic expansion also takes place on scales such as the Earth's sphere of influence. In the examples presented, we find the expansion rate of the size required by the "constant" found by Hubble and Lemaître. This is supported by other examples that also contradict the general assumption mentioned at the beginning. However, this leads to conclusions that also call other cosmological assumptions into question.

Abstract: A new method for constructing exact solutions of the General Relativity equations for a dusty matter with fractal property is proposed. This method allows to find the solution of the GR-equations in terms of matter velocities : the connection coefficients and the Ricci tensor of space-time are expressed in terms of matter velocities; the metric tensor and the matter density are found as functions of velocity from the GR-equations. The connection coefficients and the Ricci tensor are invariant with respect to the discrete scaling transformation of velocity , where is constant. Therefore, the found solution can be used to simulate the fractal properties of the cosmic web in terms of matter velocities. This solution includes isotropic and anisotropic distributions of matter density. In an isotropic case, there is a class of exact solutions including both the well-known Friedmann’s solution and a solution with a periodic distribution of the matter density in space. This last solution may be used to simulate the quasi-periodic distribution of matter in the cosmic web. It is possible that, the cosmic web and its fractal properties are the space-time primary properties. These properties are described with a deformation tensor of the space-time.

High-quality and large-size single crystals of lead-free Na0.5Bi0.5TiO3 were grown using the Czo-chralski technique. The crystals had pure perovskite structure with rhombohedral symmetry and were translucent in the visible and near infrared spectral ranges recorded in the interval 350-1050 nm. The energy gaps determined from the X-ray photoelectron spectroscopy (XPS) and optical measurements were approximately 2.92 eV. The current-voltage characteristics, depolarization current, dc (σdc) and ac (σac) electrical conductivity, and Seebeck coefficient of the crystals were investigated. The frequency/temperature-dependent electrical properties were also measured and analyzed through complex impedance spectroscopy. An overlapping reversible insulator-metal transition (resistive switching) on nanoscales, caused by the electric field, was detected. This was the first time that most of these investigations were performed for this material. The following conductivity mechanisms of NBT single crystals were identified: (i) quasi-free electron and hole conduction and hopping-charges mechanism at low temperatures, (ii) small polaron conductivity in the middle temperature range, and (iii) a significant contribution of the oxygen vacancies to conductivity in the high temperature range. The activation energy values determined from the conductivity data, the imaginary part of the electric impedance and the modulus indicate that the relaxation process in the high-temperature range is attributable to both single and double ionized oxygen vacancies, in combination with the hopping of electrons between Ti4+ and Ti3+. P-type electrical conductivity was also found. These discoveries create new possibilities of reducing the electrical conductivity of NBT and improving the process of effectively poling this material. The density of the electronic states was investigated using an ab initio method. The energy gap cal-culated for NBT (R3c) was 2.8 eV, and is well comparable to those determined from XPS and optical measurements. Our results indicate the possibility of tuning material properties by inten-tionally creating non-stoichiometry/structural defects (oxygen vacancies, cation excess and cation deficiency).

We present a thermodynamic approach in modeling the evolution of the universe based on a theory that space consists of energy quanta, the spaceons. From wave-particle duality, they can be treated as an ideal gas. The model is similar to the Big Bang but without Inflation. It provides an insight into the nature of dark energy and dark matter, and an explanation for the accelerated expansion of the universe. The universe started from an atomic size volume of spaceons at very high temperature and pressure. Upon expansion and cooling, phase transitions occurred resulting in the formation of fundamental particles, and matter. These nucleate and grow into stars, galaxies, and clusters due to the action of gravity. From the cooling curve of the universe we constructed a thermodynamic phase diagram of cosmic composition, from which we obtained the correlation between dark energy and the energy of space. Using Friedmann’s equations, our model fits well the WMAP data on cosmic composition with an equation of state parameter, w= -0.7. The dominance of dark energy started at 7.25 x 10⁹ years, in good agreement with BOSS measurements. The expansion of space is attributed to a scalar quantum space field. Dark Matter is identified as a plasma form of matter similar to that which existed during the photon epoch, prior to recombination. The thermodynamics of expansion of the universe was adiabatic and decelerating during the first 7 billion years after the Big Bang; it accelerated thereafter. A negative pressure for Dark Energy is required to sustain the latter. This is consistent with the theory of General Relativity and the law of conservation of energy. We propose a mechanism for the acceleration as due to consolidation of matter forming Dark Energy Stars (DES) and other compact objects. The resulting reduction in gravitational potential energy feeds back energy for the expansion. Space will continue to expand and dark energy will undergo phase transition to a Bose-Einstein condensate, a superfluid form of matter. Self-gravitation can cause a bounce and start a new Big Bang. We show how the interplay of gravitational and space forces leads to a cyclic, maybe eternal, universe.

This paper presents a two-stage ADC based on pseudo-differential operational transconductance amplifier (OTA), which is designed for the readout circuit of X-ray linear array sensor. This hybrid ADC employs an incremental sigma-delta ADC and a cyclic ADC, achieving a good trade-off between accuracy and conversion speed. The two stages share the same hardware to reduce power consumption and die area. A common-mood feedback module is used to suppress the influence of charge injection, and the effectiveness is demonstrated by detailed theoretical analysis. A test chip of 14-bit ADC is fabricated in 0.35μm CMOS technology. The measured root mean square (RMS) value of DNL is 0.254 LSB, and the maximum value of INL is -0.776/+1.56 LSB. The measured effective number of bits (ENOB) is 13.43 bits.

X-ray Fluorescence Computed Tomography (XFCT) is an emerging non-invasive imaging technique providing molecular-level data, gaining attention for high-resolution imaging. However, increased sensitivity with benchtop X-ray sources raises radiation exposure. Artificial Intelligence (AI), particularly deep learning (DL), has revolutionized medical imaging by delivering high-quality images in the presence of noise. In XFCT, traditional methods rely on complex algorithms for noise reduction, but AI holds promise in addressing high-dose concerns. We present an optimized SCUNet model for noise reduction in low-concentration XRF images. Compared to higher-dose images, our method’s effectiveness is evaluated. While various denoising techniques exist for X-ray and CT, few address to XFCT. The DL model is trained and assessed using the augmented data, focusing on background noise reduction. Image quality is measured using PSNR and SSIM, comparing outcomes with 100% X-ray dose images. Results show the proposed algorithm achieves high-quality images from low-dose and low-contrast agents, with a maximum PSNR of 39.05 and SSIM of 0.86. The model outperforms BM3D, NLM, DnCNN, and SCUNet in both visual inspection and quantitative analysis, particularly in high-noise scenarios. This indicates the potential of AI, specifically the SCUNet model, in significantly improving XFCT imaging by mitigating the trade-off between sensitivity and radiation exposure.

Observations of the X-ray binary system Her X-1 by the AstroSat Soft X-ray Telescope 1 (SXT) were carried out in 2020 through 2023 with the goals of measuring X-ray spectrum changes with the 35-day disk rotation phase and measuring eclipses at different 35-day phases. The four multi-day long observations were scheduled during: turn-on to Main High (MH) and MH rise; MH state; Short High (SH) state; and Low State (LS). 35-day phase was determined using monitoring observations with the Swift Burst Alert Telescope (BAT). Nine eclipses were observed at a range of 35-day phases, with at least one eclipse during each observation. Data with dips were separated from data without dips. The variation of X-ray spectral parameters vs. 35-day phase shows the following: eclipse parameters are nearly constant, showing that the scattering corona does not change with 35-day phase; dips show an increase in covering fraction but not column density compared to non-dip data; the 1 keV line normalization indicates an origin in a small region near the continuum emission region, likely the magnetospheric accretion flow from the inner disk onto the neutron star; and the change in blackbody normalization (area) shows that the emission region is much larger than the 1 keV emission region, and consistent with the inner edge of the accretion disk.

Dengue virus (DENV), being one of the lethal pathogens in the hot climatic regions of the world, have been extensively studied to decipher its mechanism of pathogenesis and missing links of its life cycle. With respect to the entry of DENV, multiple receptors have been recognised in different cells of the human body. However, scientists still argue whether these identified receptors are the exclusive entry mediators for the virus. Adding to the complexity, DENV has been reported to be infecting multiple organ types in its human host. Also, more than one receptor in a particular cell has been discerned to take part in mediating the ingress of DENV. In this review, we aim to discuss about the different cells of the human immune system that support DENV infection and their corresponding receptors that DENV deploy to gain access to the cells.

In the digital age, Artificial Intelligence (AI) is emerging as a transformative force in various sectors, in-cluding medicine. This article explores the potential of AI, akin to the magical genie of Aladdin's lamp, particularly within thoracic surgery and lung cancer management. It examines AI applications like ma-chine learning and deep learning in achieving more precise diagnoses, preoperative risk assessment, and improved surgical outcomes. The challenges and advancements in AI integration, especially in computer vision and multi-modal models, are discussed alongside their impact on robotic surgery and operating room management. Despite its transformative potential, implementing AI in medicine faces challenges regarding data scarcity, interpretability issues, and ethical concerns. Collaboration between AI and medi-cal communities is essential to address these challenges and unlock the full potential of AI in revolution-izing clinical practice. This article underscores the importance of further research and interdisciplinary collaboration to ensure the safe and effective deployment of AI in real-world clinical settings.

MicroRNA (miRNA) is small non-coding RNAs that play vital roles in post-transcriptional gene regulation by inhibiting mRNA translation or promoting mRNA degradation. Dysregulation of miRNA has been implicated in numerous human diseases, including cancers. The family members of miR-34 (miR-34s), composed of miR-34a, miR-34b, and miR-34c, have emerged as the most extensively studied tumor-suppressive miRNAs. In this comprehensive review, we aim to provide an overview of the major signaling pathways and gene networks regulated by the miR-34s in various cancers and highlight the critical tumor suppressor role of miR-34s. Furthermore, we will discuss the potential of using miR-34 mimics as a novel therapeutic approach against cancer, while also addressing the challenges associated with their development and delivery. It is anticipated that gaining a deeper understanding of the functions and mechanisms of miR-34s in cancer will greatly contribute to the development of effective miR-34-based cancer therapeutics.

One of the solutions of the Einstein equations, called McVittie solution, signifying a black hole embedded by the dynamic spacetime is studied. In the stationary spacetime the Mcvittie metric becomes the Schwarzschild-de Sitter metric (SdS). The geodesic of a freely falling test particle towards the black hole is examined in the SdS spacetime. It is found that unlike Schwarzschild case the potential of such particle becomes maximum at a point where it eventually stops to follow an unstable circular motion and then resumes its motion towards black hole center. It is shown that an observer or system of particles is spaghettified near the black hole singularity in the SdS spacetime. The dynamic of the universe in the framework of McVittie metric, being a generalized time dependent SdS solution, is represented in terms of that point, called stationary or turning point. The motion of the stationary point is studied in various regimes of the expanding universe and the possible outcomes are discussed in brief.

Women of color (WoC) in the health professions encounter challenges in advancement to higher positions, disparities in wages, discrimination, lack of expectation to achieve leadership positions, and absence of extensive support networks. Articles in the literature have addressed race and/or gender in the context of professional development. However, applying an intersectionality lens or framework to better understand the contextual issues of professional development for WoC remains to be addressed. Thus, this scoping review aimed to (i) identify health professions literature that addresses disparities affecting WoC, and (ii) describe strategies and approaches to support WoC in the health professions. Methods: Literature searches were conducted in multiple databases. Three independent reviewers reviewed and screened articles for inclusion. Results: 31 articles were included - medicine(17), nursing(1), pharmacy(7), other(4), and multiple health professions(2). Key findings included underrepresentation of women and minority groups, inequities in professional advancement and leadership positions for WoC, and greater dissatisfaction and attrition among minority and women professionals. Conclusion: WoC face unique and distinct challenges and barriers in their professional careers resulting from the intersectionality of not only race and gender, but also lived experiences and opportunities. Strategies to improve diversity and representation should include an intersectionality framework or lens and be critically evaluated.

The Bacillus Calmette-Guerin vaccine (BCG vaccine) designed to prevent tuberculosis in children has been shown to induce a trained immune response in the body to fight against bacteria as well as other parasites and viruses. This knowledge has been reciprocated to generate the idea that this vaccine can also offer protection against severe acute respiratory syndrome coronavirus-2 (SARS-COV-2). Some recent pre-print articles have highlighted that countries with mass BCG immunizations seems to have a lower incidence of coronavirus disease 2019 (COVID-19) compared to those without BCG immunization. There are yet no experimental proof of any such association and the world health organisation (WHO) is currently testing the theory with clinical trials on selected cohorts. Epidemiologists and other scientific experts has expressed both their hope and concern simultaneously regarding the success theory of BCG vaccination to prevent COVID-19. Though its still not verified in any way whether the BCG vaccination can actually prevent COVID-19 or not but we believe a thorough analytical research in this regard is indeed worth a shot.

Monsoon winds drive upwelling along the eastern coast of India during the south-west (SW) monsoons. These winds also provide alongshore windstress (AWS) resulting in positive cross-shore Ekman transport (ET) from late May to the end of September. While instances of high ET and sea surface temperature (SST) based upwelling index (UI_SST) were observed along different parts of the coast, UI_SST was weaker in the northern section in the earlier part of monsoon. This was even in the presence of maximum AWS and ET during the 10 years analysis period spanning January-2009 to December-2018. Additionally, negative sea surface height anomalies (SSHAs), typically associated with coastal upwelling, were observed only along the southern-most coast. An empirical orthogonal function (EOF) analysis revealed two coherent modes of SSHA variation. The first principal component (PC) showed a SSHA signature coincident spatio-temporally with the first downwelling Kelvin wave, closely associated with the equatorial zonal winds that drive coastal Kelvin waves. The third PC with a coastal SSHA pattern similar to the second upwelling Kelvin wave was associated with offshore ET along the northern part of the Indian east coast. Time series of the two PCs exhibited suppression of coastal upwelling by downwelling Kelvin waves during May-July along the northeastern coast of India. Local AWS driven ET was the primary driver of coastal upwelling with the weakening of the remotely forced Kelvin waves in August. A coherent mode consisting of negative coastal SSHA signature was excited in response to local AWS driven ET during the upwelling period. This study examined the spatio-temporal variability of SW monsoon coastal upwelling along the east coast of India and illustrated the role of equatorial windstress forced first downwelling Kelvin wave in suppressing upwelling in the northern part of the coast during early SW monsoon season.

A commercially reared domesticated turkey (Meleagris gallopavo) was purchased from a local market and sections of tissue representing leg, thigh, and breast were harvested and processed for analysis of the lipids and proteins present. Leg and thigh tissue was enriched in mitochondrial proteins whereas the breast tissue was enriched in glycolytic enzymes as well as the cytosolic and mitochondrial forms of glycerol-3-phosphate dehydrogenase. A potential marker for breast tissue muscle formation and/or function was also identified. The tissues could clearly be separated based upon their lipid profiles with little differences in cardiolipin levels suggesting that mitochondrial surface areas may be similar across the tissues. The most significant differences in the lipids were found to be higher levels of oxidized lipids in thigh meat. This work provides the first untargeted proteome and lipidome datasets for the domesticated turkey. The proteome dataset is accessible from ProteomeXchange Consortium via the PRIDE partner repository with the identifier PXD008207.

Monsoon winds drive upwelling along the eastern coast of India during the south-west (SW) monsoons. These winds also provide alongshore windstress (AWS) resulting in positive cross-shore Ekman transport (ET) from March to the end of September. While instances of high ET and sea surface temperature based upwelling index (UI_SST) were observed along two parts of the coast: between Kashinagara and Kakinada in the north, and between Kavali and Point Calimere in the south. The UI_SST illustrated a much poorer agreement with local ET in the northern section, where the onset of UI_SST preceded the rise of ET and the subsidence of UI_SST signals occurred during a period of rising ET. Additionally, negative sea surface height anomalies (SSHAs), typically associated with coastal upwelling, were also missing through most of the upwelling period. A complex empirical orthogonal function (CEOF) analysis revealed two coherent modes of SSHA variation. The first mode showed a SSHA signature spatio-temporally coincident with the first upwelling and downwelling Kelvin waves closely associated with the equatorial zonal winds that drive them. The second CEOF mode, with a coastal SSHA pattern similar to the SSHA signatures of coastal upwelling, was associated with local offshore ET along the Indian east coast. The CEOF analysis exhibited the triggering of coastal upwelling in April and its suppression from June by coastally trapped Kelvin waves along the northeastern coast of India, while local AWS driven ET was the primary driver of coastal upwelling along the southeastern coast. The second CEOF mode also exhibited a coherent negative coastal SSHA signature excited by local AWS driven ET during the upwelling period. This study examined the spatio-temporal variability of premonsoon and SW monsoon coastal upwelling along the western Bay of Bengal and its relation to remotely forced coastal Kelvin waves.

Lactoperoxidase (LP), which is a high-value minor whey protein, has recently drawn extensive attention from research scientists and industry due to its multi-function and potential therapeutic applications. In this study, the separation and optimization of two similar-sized proteins, LP and lactoferrin (LF) were investigated using strong cation exchange column chromatography. Optimization was started with central composite design based experiments to characterize the importance of different decision variables. The three variables used in the optimization were flow rate, length of gradient and final salt concentration in the linear elution gradient step. The obtained empiric functional model represented the effect of the significant factors on the yield as the objective function. Afterwards, the calibrated mechanistic model was employed to predict accurate optimal set of variables. The optimal operating points were found and the results were compared with validation experiments. Predictions respecting yield confirmed a very good agreement with experimental results while keeping purity, a product quality characteristic, equal or above to a predefined value.

Spike (S) protein of Coronaviruses help in receptor attachment and virus entry into the host cells. While S protein is required for virus entry, it is also important as an immunogen as it is the most accessible part of the virus architecture. S protein form knob like structures (viral spikes) protruding outwards in the form of homotrimers containing an S1 and S2 as monomers. Mutations in structural proteins of virus play crucial role in determining virulence and also in many instances influencing emergence of antibody escape variants and cellular tropism. In this paper we have performed in depth analyses of spike protein sequences from various parts of the world and tried to correlate the data with possible functional relevance of such mutations.

A lack of data reproducibility (“reproducibility crisis”) is debated across many scientific and medical disciplines. A systematic analysis of the available evidence on the reliability of scientific data revealed that, although the existence of a reproducibility crisis is widely perceived, conclusive data on the scale of the problem are lacking. Most importantly we found that, although the debate is largely focused on methodological issues, researcher conduct defines research standards and in turn data reliability. The availability of reliable methods itself does not guarantee good practice. Moreover, research is typically characterised by a lack of established methods due to its immanent novelty. Despite the crucial importance of researcher conduct, research and conclusive data on the determinants of researcher behaviour are missing. In conclusion, meta-research is urgently needed that establishes an understanding of the factors that determine researcher behaviour. This knowledge can then be used to implement and iteratively improve measures, which incentivise researchers to apply the highest standards resulting in high quality data.

A prominent class of reactions, reductive aminations are used extensively in research labs and industry to synthesize amines; which are applied in a variety of medicines, agrochemicals, and biomolecules. Amine compounds are essential in many aspects of life; amino groups exist in many natural and agricultural products. New 4-(benzylamino)benzoic acid derivatives with general formula of C14H12NO2R, where [R= (H), (4-Cl), (4-NMe), (4-Br), (3-NO2), (4-NO2), (2-OMe), (3-OMe), (4-OMe), (2,3-OMe), (3,4-OMe), (2-OH, 3-OMe), (3-OMe, 4-OH), (3,5-OMe, 4-OH), (2-OH, 5-Br), (3-OH), (4-SMe), (2,3-OH), (3-CF3)] (compounds 1-19) were obtained by reductive amination reaction via reacting p-amino benzoic acid with benzaldehyde derivatives and sodium borohydride. All prepared compounds has been characterized by a variety of spectroscopic techniques (HRMS, FT-IR, 1H, and 13C{1H} NMR) and elemental analysis. Furthermore, the structure of some of the synthesized derivatives were confirmed by single crystal X-ray diffraction (R = 4-Cl, 4-Br, 2-OMe, 3-OMe, 4-OMe, 2,3-OMe), compounds 2, 4, 7-9 and 11, respectively. Moreover, some of these new compounds have shown somehow moderate antibacterial activities against different strains of bacteria (gram-positive and gram-negative) with MIC values ranging from 64-256 µg/ mL. The anticancer activities of all compounds (IC50 values, µM) were evaluated against different cell lines, HGF (Fibroblasts; normal cell line), A549 (Non-Small Cell Lung Cancer cell line) and H69 (Small Cell Lung Cancer cell line). Compound 18 showed a considerable IC50 value of 90.69 against A549 and an excellent value of 32.22 and H69, respectively.

Integrated crop-livestock production (ILP) is an interesting alternative for more sustainable soil use. However, more studies are needed to analyze soil pore properties under ILP at the micrometer scale. Thus, this study proposes a detailed analysis of soil pore architecture at the micrometer scale in three dimensions. For this purpose, samples of an Oxisol under ILP subjected to minimum tillage (MT) and no-tillage (NT) with ryegrass as cover crop (C) and silage (S) were investigated. The soil micromorphological properties of the soil were analyzed using X-ray microtomography. The MT(C) system showed the highest values of porosity (c. 20.4%), connectivity (c. 32.8×103), volume (c. 26%), and number of pores (c. 32%) in a rod-like shape. On the other hand, the MT(S), NT(C), and NT(S) systems showed higher tortuosities (c. 2.2, c. 2.0, and c. 2.1) and lower pore connectivities (c. 8.3×103, c. 6.9×103, and c. 6.2×103), especially in S use. Ellipsoidal and rod-shaped pores predominated over spheroidal and disc-shaped pores in all treatments. The results of this study show that the use of ryegrass as a cover crop improves soil physical properties, especially in MT. For S use, the type of soil management (MT or NT) did not show any differences.

A Cu₂ZnSnS₄ (CZTS) film with a thickness of approximately 1.5 μm was fabricated on a Mo-coated glass substrate by annealing a CZTS precursor fabricated from nanoparticle ink. The chemical states of the elements in the CZTS thin film in the depth direction were studied to identify the presence of secondary phases, which are detrimental to the performance of solar cells containing CZTS. X-ray diffraction was unable to detect any secondary phases in CZTS because of their small relative amount. Instead, X-ray photoelectron spectroscopy (XPS), which is highly sensitive to chemical state, was conducted at different depths in the CZTS film to further check the presence of secondary phases. XPS analysis revealed peaks shift consistent with the presence of secondary phases. For the CZTS film annealed in a S atmosphere at 575 °C for 3 h, the film surface consisted of a secondary-phase layer composed of CuS, ZnS, and SnSx (x=1 or 2) originating from the decomposition of CZTS. At depths below 80 nm, the film was pure CZTS. Formation of MoS2 at the CZTS–Mo interface was confirmed by XPS analysis of Mo and S.

We obtain exact solutions to the field equations for 5 dimensional LRS Bianchi type-I spacetime in $f(R,T)$ theory of gravity where specifically the following three cases are considered: (i) $f(R,T)=\mu(R+T)$, (ii) $f(R,T)=R \mu + R T \mu^2$ and (iii) $f(R,T)=R+\mu R^2+\mu T$ where $R$ and $T$ respectively the Ricci scalar and trace of the energy-momentum tensor. It is found that the equation of state (EOS) parameter $w$ is governed by the parameter $\mu$ involved in the $f(R,T)$ expressions. We fine-tune the parameter $\mu$ to obtain effect of phantom energy in the model, however we also restrict this parameter to obtain a stable model of the universe. It is noted that the model isotropizes at finite cosmic time.

Samarinda’s flooding issue is threatening future city development. As the most populated city in Kalimantan, Samarinda (the municipality of East Borneo) plays a role-model in disaster management for a neighboring city. This paper introduces current flood disaster handling in this city. History of disaster management in Indonesia is started from the earlier of Indonesian independence. Year 2008, after hit by severe Tsunami in Aceh and its surrounding, Government of Republic of Indonesia form special agency to manage disaster specifically, namely National Board for Disaster Management (in Bahasa called: Badan Penanggulangan Bencana Nasional [BNPB]) and follows by the regional and local government to form similar agency in provincial and local scale (including Samarinda), called Regional Board for Disaster Management (in Bahasa: Badan Penanggulangan Bencana Daerah[BPBD]) which is formed in 2009 and 2011, respectively. The aim of this paper is to explain flood management in Samarinda where is flood hazard increase gradually and need to be a priority. Descriptive analysis is used in this study including secondary data and interviewed stakeholders. Finally, the finding of study obtains found five constraints related to Samarinda’s flood management including administrative and policy, social, economic, environment and technical and knowledge constraint. This study also promotes several schemes of non-structural approach to enlarge alternative perspective in flood management.

In the present work, the charged B1, B2 and B3 bastons with the condition of k(mm) = k >> k(dd) > k(dm) = k(lq) = 0 are explained as the good candidates of the dark matters. The proposed rest mass (26.12 eV/c²) of the B1 dark matter is indirectly confirmed from the supernova 1987A data. The missing neutrinos are newly explained by using the dark matters and lepton charge force. The neutrino excess anomaly of the MinibooNE data is explained by the B1 dark matter scattering within the Cherenkov detectors. And the rest masses of 1.4 TeV/c² and 42.7 GeV/c² are assigned to the Le particle and the B2 dark matter, respectively, from the cosmic ray observations. In the present work, the Q1 baryon decays are used to explain the anti-Helium cosmic ray events. Because of the graviton evaporation and photon confinement, the very small Coulomb’s constant (k(dd)) of 10^x-54k and gravitation constant (G_N(dd)) of 10^xG_N for the charged dark matters at the present time are proposed. The x value can have the positive, zero or negative value around zero. Therefore, F_c(mm) > F_g(dd) (?) F_g(mm) > F_g(dm) > F_c(dd) > F_c(dm) = F_c(lq) = 0 for the proton-like particle.

We measure the accelerated cosmic expansion rate of the late-time Universe and derive constraints on cosmological parameters from the final baryon acoustic oscillation (BAO) uncorrelated measurements of different surveys after two decades of dedicated spectroscopic observation combined with the Pantheon sample of Type Ia supernovae, the Hubble diagram of gamma-ray bursts & quasars data, the Cosmic Chronometers data, and the recent Hubble constant value measurement from the Hubble Space Telescope and the SH0ES Team as an additional prior. In Λ cold dark matter (ΛCDM) scenario, the model fit yields Ωm=0.313±0.034 and ΩΛ=0.672±0.025. Combining BAO with CC+Pantheon+QSR+GRB data sets we get H0=69.21±1.22 km s−1 Mpc−1, rd=133.46±2.49 Mpc. For the a flat wCDM model, we get w=−1.111±0.030. For a dynamical evolution of dark energy in a flat w0waCDM cosmology, we get wa=−0.292±0.167. We apply the Akaike information criteria probe to compare the three models, and see that all models are favored and cannot be discarded from the current data.

In this research, the other reasonable explanations for the cosmic microwave background radiation is revealed. Due to the microwave resolution, it very roughly shows the image of galaxies in the universe. Moreover, the intensity measurement on each pixel of the image is the sum of the incident microwaves from different directions, so the microwave image cannot represent the microwave sources clearly far away from the Earth. Hence, we propose a simulation after removing several strongest microwave sources, the remaining microwave radiation sources can establish a very uniform intensity distribution over a range of several ten light years. On the other hand, Sloan Digital Sky Survey reveals 200 million galaxies in the universe and, in fact, only to eliminate the contributions of all galaxies from the microwave image is impossible. The way to further obtain the fine-scale structure by only removing the few strongest microwave sources as the foreground effect will keep the other contributions from all the rest galaxies and stars. Therefore, the Cosmic Microwave Background cannot be uniquely explained the radiation which was left after the initial formation of the universe. Moreover, it is the mainly residual radiation from the un-calculated galaxies and inaccurate estimation of the microwave source strength.

The Universe, rather than being homogeneous, displays an almost infinite topological genus, because it is punctured with a countless number of gravitational vortexes, i.e., black holes. Starting from this view, we aim to show that the occurrence of black holes is constrained by geometric random walks taking place during cosmic inflationary expansion. At first, we introduce a visual model, based on the Pascal’s triangle and linear and nonlinear arithmetic octahedrons, which describes three-dimensional cosmic random walks. In case of nonlinear 3D paths, trajectories in an expanding Universe can be depicted as the operation of filling the numbers of the octahedrons in the form of “islands of numbers”: this leads to separate cosmic structures (standing for matter/energy), spaced out by empty areas (constituted by black holes and dark matter). These procedures allow us to describe the topology of an universe of infinite genus, to assess black hole formation in terms of infinite Betti numbers, to highlight how non-linear random walks might provoke gravitational effects also in absence of mass/energy, and to propose a novel interpretation of Beckenstein-Hawking entropy: it is proportional to the surface, rather than the volume, of a black hole, because the latter does not contain information.

Despite numerous studies in statistical downscaling methodology, there remains a lack of methods that can downscale from precipitation modeled in global climate models to regional level high resolution gridded precipitation. This paper reports a novel downscaling method using a Generative Adversarial Network (GAN), CliGAN, which can downscale large-scale annual maximum precipitation given by simulation of multiple atmosphere-ocean global climate models (AOGCM) from Coupled Model Inter-comparison Project 6 (CMIP6) to regional-level gridded annual maximum precipitation data. This framework utilizes a convolution encoder-dense decoder network to create a generative network and a similar network to create a critic network. The model is trained using an adversarial training approach. The critic uses the Wasserstein distance loss function and the generator is trained using a combination of adversarial loss Wasserstein distance, structural loss with the multi-scale structural similarity index (MSSIM), and content loss with the Nash-Sutcliff Model Efficiency (NS). The MSSIM index allowed us to gain insight into the model’s regional characteristics and shows that relying exclusively on point-based error functions, widely used in statistical downscaling, may not be enough to reliably simulate regional precipitation characteristics. Further use of structural loss functions within CNN-based downscaling methods may lead to higher quality downscaled climate model products.

In this study, we introduce the concept and construction of an innovative Digital Miniature Cathode Ray Magnetometer designed for the precise detection of magnetic fields. This device addresses several limitations inherent to magnetic probes such as D.C. offset, nonlinearity, temperature drift, sensor aging, and the need for frequent recalibration, while capable of oper-ating in a wide range of magnetic fields. The core principle of this device involves the utilization of a charged particle beam as the sensitivity medium. The system leverages the interaction of an electron beam with a scintillator material, which, then, emits visible light that is captured by an imager. The emitted scintillation light is captured by a CMOS sensor. This sensor not only rec-ords the scintillation light but also accurately determines the position of the electron beam, providing invaluable spatial information crucial for magnetic field mapping. The key innova-tion lies in the combination of electron beam projection, CMOS imager scintillation-based de-tection and digital image signal processing. By employing this synergy, the magnetometer achieves remarkable accuracy, sensitivity and dynamic range. The precise position registration enabled by the CMOS sensor further enhances the device's utility in capturing complex magnetic field patterns, allowing for 2D field mapping. In this work, the optimization of the probe's per-formance is tailored for applications related to the characterization of insertion devices in light sources, including undulators.

We investigate the behavior of the solutions of the ray equation in isotropic media. We discuss local and global transversals and wavefronts and give examples of rays without wavefronts.

A multiscale model that enables quantitative understanding and prediction of the size effect on scattering properties of micro- and nanostructures is crucial for the design of LED surface textures optimized for high light extraction efficiency (LEE). In this paper, a hybrid process for combining full-wave finite-difference time-domain simulation and a ray-tracing technique based on a bidirectional scattering distribution function model is proposed. We apply this method to study the influence of different pattern sizes of a patterned sapphire substrate on GaN-based LED light extraction from the microscale to the nanoscale. The results show that near-wavelength–scaled patterns with strong diffraction are not expected to enhance LEE. By contrast, microscaled patterns with optical diffusion behavior have the highest LEE at a specific aspect ratio, and subwavelength-scaled patterns that have antireflection properties show marked enhancement of LEE for a wide range of aspect ratios.

With the development of sensor and communication technologies, Internet of Things (IoT) subsystem is gradually becoming a crucial part in vehicles. It can effectively enhance functionalities of vehicles. However, new attack types are also emerged. For example, a driver with the smart key in the pocket can push the start button to start a car when. At the same time, security issues in the push-to-start scenario are alerted, such as smart key forgery. In this paper, we propose a vehicle Passive Entry Passive Start (PEPS) system that uses deep learning algorithms to recognize the driver by the Electrocardiogram (ECG) signals measured by his or her smart watch. ECG signals are used for verification. Smart watches, as a new smart key of PEPS system, can replace traditional smart keys to improve security. Experiment results show that Long Short-Term Memory (LSTM) models have achieved the best accuracy score for identity recognition (91%) when single ECG cycle is used. However, it takes at least 30 minutes for training. The training time of Auto Encoder successfully reduces to 5 minutes. When 15 continuous ECG cycles are used, it can achieve 100% identity accuracy.

The detection performance of small objects in remote sensing images has not been satisfactory compared to large objects, especially in low-resolution and noisy images. A generative adversarial network (GAN)-based model called enhanced super-resolution GAN (ESRGAN) showed remarkable image enhancement performance, but reconstructed images usually miss high-frequency edge information. Therefore, object detection performance showed degradation for small objects on recovered noisy and low-resolution remote sensing images. Inspired by the success of edge enhanced GAN (EEGAN) and ESRGAN, we applied a new edge-enhanced super-resolution GAN (EESRGAN) to improve the quality of remote sensing images and used different detector networks in an end-to-end manner where detector loss was backpropagated into the EESRGAN to improve the detection performance. We proposed an architecture with three components: ESRGAN, EEN, and Detection network. We used residual-in-residual dense blocks (RRDB) for both the ESRGAN and EEN, and for the detector network, we used a faster region-based convolutional network (FRCNN) (two-stage detector) and a single-shot multibox detector (SSD) (one stage detector). Extensive experiments on a public (car overhead with context) dataset and another self-assembled (oil and gas storage tank) satellite dataset showed superior performance of our method compared to the standalone state-of-the-art object detectors.

To solve a series of major problems, such as the singularity before the Big Bang, the inflation of the early universe and the accelerating expansion of the present universe, this series of studies start with super gravity, dark energy and dark matter, go beyond the surface of a lot of observation data, and systematically reveal the arche-internal mechanism of all things, to establish the arche-unity of physics, and give a natural and reasonable explanation. At present, there are at least three basic pathways that are leading our research field to repulsion against gravitation, quantum repulsion against quantum gravitation and high-dimensional superrepulsion against high-dimensional supergravity, that is, the research on the accelerating expansion mechanism of the current universe, the research on the dynamic mechanism of the early cosmic inflation, and the research on the rebound mechanism near the singularity before the Big Bang. In this series of studies, the arche problem of everything is always placed under the extreme environmental conditions of the initial universe, the starting point of scientific logic is closely combined with the starting point of the universe history, the pseudo vacuum energy considered by the inflationary universe model, the Higgs field predicted by the standard physical model and the dark energy speculated by the observational cosmology are reduced to the positive energy system with strong negative pressure, and they are reduced to the repulsion (all the resistance to gravity) that forms a conjugate relation with gravity. In our opinion, dark energy and dark matter are essentially at the level of quantum gravity and quantum repulsion. Therefore, we not only consider the conventional quantum effect and non commutative quantum effect, but also further consider the arche-conjugate effect and the cluster resonance-at-cofrenquence effect. For noncommutative space-time, we put forth the ultimate supersymmetry, the arche-conjugation and the cluster resonance-at-cofrenquence. A relatively complete natural mechanism forms such an important inference: the closer they get to Planck scale, the stronger the conventional quantum effect, non commutative quantum effect, arche-conjugate effect and co-frequency resonance effect are. In the high-dimensional space-time (the 11 dimensional hyperspace compactly reduced to M 4 × N r ), corresponding to the introduction of supergravity with the supersymmetry between the graviton and the gravitino, we put forth the superrepulsion with the supersymmetry between the repulsion and the repulsitino, and establish the arche-conjugate relationship between the high-dimensional supergravity and the high-dimensional superrepulsion. Therefrom, we propose a basic inference that can be promoted to the principle of hyperholography of high-dimensional universe (or multiuniverse): in a parallel universe formed by mutual coupling and holographic correspondence between the P universe dominated by negative pressure (high-dimensional superrepulsion and quantum repulsion of accumulating positive energy, mainly composed of dark energy) and the N universe dominated by positive pressure (high-dimensional supergravity and quantum gravity of accumulating negative energy, mainly composed of dark matter), there is a correspondence between the small-scale physics (ultraviolet cutoff) of the P universe and the large-scale physics (infrared cutoff) of the N universe, while there is a correspondence between the large-scale physics (ultraviolet cutoff) of the P universe and the small-scale physics (infrared cutoff) of the N universe. In the new research paradigms set in this series, the arche-conjugation between the high-dimensional supergravity and the high-dimensional super repulsion, as well as between the quantum gravity and the quantum repulsion, is higher than the supersymmetry, so it becomes the core concept of the new theory. The arhce-unity of physics is a super unity that transcends the grand unification of four basic interaction, which is formed between high-dimensional supergravity (related to dark matter) and high-dimensional superrepulsion (related to dark energy), between quantum gravity (related to dark matter) and quantum repulsion (related to dark energy). From the basic component point of view, before or after the big bang, the gravitons and repulsons are coupled together, the negative energy contraction dominated by the positive pressure and the positive energy expansion dominated by the negative pressure work alternately, forming the arche-conjugate pulsaton of neither the point particle nor the linear superstring. Under the big unified framework of quantum gravitational field and quantum repulsive field, this series of work comprehensively expands the general relativity and loop quantum ring gravitation theory, sets up the quantum repulsive field equation corresponding to the quantum gravitational field equation, and then establishes the quantum hedge-unified field equation describing the interaction of quantum gravitational field and quantum repulsive field; On this basis, the quantum repulsive universe equation corresponding to the quantum gravitational universe equation is established, thus a set of new equations describing the expansive universe with quantum hedge-unified field are established. On the one hand, scalar disturbance is considered as the exhibition of repulsive effect, on the other hand, tensor disturbance is considered as the exhibition of gravitational effect. In the initial stage of the big ripping, due to the mutual restraint of quantum repulsion and quantum gravity, the scalar and tensor perturbations are not obvious. However, at the end of the big ripping, the scalar and tensor perturbations are very significant, and there is a large power spectral exponential run. Between particle physics and cosmology, we improve and expand the path integral of quantum gravity, create the path integral of quantum hedge-unified field, and set up the basic equation of quantum cosmic-synergetic dynamics, and then establish the basic equation of quantum-cosmic paradigm dynamics. Thus we put up the operator distribution function and its dynamic equation of the quantum arche- pulsaton, and finally use the Wigner-Ville distribution as a non-linear time-frequency distribution to establish the Wigner joint-distribution of quantum-conjuagted pulsation function, so as to analyze the arche of all things with three evolutionary forms: quantum chaotic-pulsaton, quantum quasi-spherical pulsaton and quantum spherical-pulsaton. In this series of work, the mechanism to avoid the singularity of the universe is put forward fundamentally, and the dark energy and dark matter are explained through new mechanisms and effects at the level of quantum gravity. Between particle physics and cosmology, we improve and expand the path integral of quantum gravity, establish the path integral of quantum hedge-unified field, thus establish the basic equation of quantum cosmic-synergy dynamics, and then establish the basic equation of quantum cosmic-paradigm dynamics. Thus the covariant gravitational mass and the covariant inertial mass formed by the ultra-synergy between particles and the universe are presented, and the equivalence hypothesis on the covariant non-inertial system which can be elevated to the basic principle, is presented. Based on this hypothesis, a systematic calculation and analysis of binary stars composed of neutron stars and black holes are made. The master equation, variance and Fokker-Planck equation for the birth-death and migration of a large number of particles are established between binary stars composed of neutron stars and black holes.

In the United States, the Federal Aviation Administration has officially classified flight crew (FC) consisting of commercial pilots, cabin crew or flight attendants as “radiation workers” since 1994 due to the potential for cosmic ionizing radiation (CIR) exposure at cruising altitudes originating from solar activity and galactic sources. Several epidemiological studies have documented elevated incidence and mortality for several cancers in FC, but it has not yet been possible to establish whether this is attributable to CIR. CIR and its constituents are known to cause a myriad of DNA lesions, which can lead to carcinogenesis unless DNA repair mechanisms remove them. But critical knowledge gaps exist with regard to CIR dosimetry, the role of other genotoxic exposures among FC, and possible biological mechanisms underlying higher cancer rates observed in FC exist. This review summarizes our understanding of the role of DNA damage and repair responses relevant to CIR exposure in FC. We aim to stimulate new research directions and provide information that will be useful for guiding regulatory, public health, and medical decision-making to protect and mitigate risks for those who travel by air.

Traditional photodynamic therapy (PDT) is often limited in its efficacy by insufficient light penetration, inefficient photosensitizer energy transfer, and inadequate target tissue oxygenation. X-ray activated PDT (XPDT), using nanoparticle (NPs) photosensitizers comprised of europium-doped yttrium oxide cores encased within silica shells (Y₂O₃:Eu@SiO₂), offers the potential of overcoming most of these limitations. Aimed at maximizing the generation of reactive oxygen species (ROS), this study reports methodologies for investigation of the effects of synthesis conditions on the characteristics of Y₂O₃:Eu@SiO₂ NP. Transmission electronic microscope (TEM) revealed that the NP core diameter was linearly, positively correlated with condensation time (R2 = 0.7357, p < 0.05) and linearly, negatively correlated with urea concentration (R2 = 0.958, p < 0.05). The addition of cetyltrimethylammonium bromide (CTAB) during core synthesis demonstrated enhanced particle dispersion. Silica coating via APTES-1 and TEOS-3 conditions resulted in Y₂O₃:Eu@SiO₂ NPs that generated the highest ROS, with 8.7-fold and 8.9-fold increase respectively in relative fluorescence intensity at 8 Gy irradiation compared to a 5.2-fold increase in PBS under the same condition. In vivo evaluation using 18F-fluorothymidine positron emission tomography (18F-FLT PET) of mouse xenografts of a human prototypical cancer (ovarian) revealed a 55% reduction in tumor proliferation of radiation-sensitive CAOV3 tumors treated with Y₂O₃:Eu@SiO₂ NPs compared to a 19% reduction in tumor proliferation of radiation-resistant SKOV3 tumors on the fourth day post-treatment. Taken together, these findings suggest Y₂O₃:Eu@SiO₂ NPs can serve as effective photosensitizers for XPDT and their performance characteristics can be optimized by selecting synthesis conditions and parameters to deliver the desirable therapeutic effects, offering novel approaches to circumventing many of the limitations of conventional PDT in the treatment of cancer.

Communicating about sex is important in generating positive perceptions about one’s sexual and romantic life. The last decade has provided insight into the theoretical applications on sex communication research. While the focus on extant research focuses on the psychological processes’ individuals employ to talk about sex, no theoretical framework exists that identifies key constructs that provides a parsimonious understanding about the communicative processes of sex and sexuality. This review sought to identified key constructs that are suitable to develop a sex talk theory. In the current project, we reviewed 24 studies including 8,698 participants (Mage = 24.98) that applied a theoretical framework to sex research. This review identified three salient constructs (e.g., disclosure, cognitive, and relational and behavioral) that are important for a sex talk theory. Last, this review indicated that scholarship should explain the relationships between the key constructs. We provided several recommendations that scholars should take when developing a theory in sex communication research.

The present article describes the synthesis of an isonicotinate-derived meso-arylporphyrin, that has been fully characterized by spectroscopic methods (including fluorescence spectroscopy), as well as by elemental analysis and by HR-MS. The structure of a n-hexane monosolvate has been determined by single crystal X-ray diffraction analysis. The radical scavenging activity of this new porphyrin against the 2,2-diphenyl-1-picrylhydrazyl (DDPH) radical has been measured. Its antifungal activity against three yeast strains (C. albicans ATCC 90028, C. glabrata ATCC 64677 and C. tropicalis ATCC 64677) has been tested, using the disk diffusion and the microdilution methods. Whereas the measured antioxidant activity was low, the porphyrin showed moderate but encouraging antifungal activity. Finally, a study of its effect on the germination of lentil seeds revealed interesting allelopathic properties.

In this work, we explore new constraints on phantom scalar field cosmologies with a scalar field employing early times catalogues related to CMB measurements, along with the local standard observables, like Supernovae Type Ia (SNIa), H(z) measurements (Cosmic Clocks), and Baryon Acoustic Oscillations (BAO) baselines. In particular, we studied a tracker phantom field with hyperbolic polar coordinates that have been proposed in the literature. The main goal is to obtain precise cosmological constraints for H0 and σ8, in comparison to other constructions that present tension in early cosmological parameters. Our results show that phantom scalar field cosmologies have a reduced statistical tension on H0 that it is less than 3σ using model-independent CMB catalogues as SPT-3G+WMAP9 and ACTPol DR-4+WMAP9 baselines. This suggests these models using a different phantom potential might address the Hubble constant problem and reduce the systematics involved.

Two anisotropic exact Bianchi type I solutions of Einstein’s field equations that generalize the isotropic ΛCDM universe model, are used to investigate the Hubble tension. It is shown that the cosmic anisotropy as deduced from the Planck measurements of the fluctuations in the temperature of the cosmic microwave background radiation, is ten billion times too small to solve the Hubble tension.

The question of whether some neutrinos are tachyons remains unresolved although various evidence from cosmic ray and other data exists that the electron neutrino has an effective $m_\nu^2\approx -0.25 eV^2,$ which would require that one or more mass states is also tachyonic. In 2013 the $3+3$ model of the neutrino masses, which includes one tachyonic mass state, was proposed based on supernova SN 1987A neutrino data. Here we update evidence for tachyonic electron neutrinos and the $3+3$ model and discuss one test which could prove conclusive. The update of earlier evidence includes many new elements, including new data which makes the earlier cosmic ray evidence more robust, new results on cosmic ray composition, the ankle of the spectrum, leptonic cosmic ray data, and the statistical significance of finding the three large neutrino masses stipulated in the $3+3$ model. Barring a galactic supernova, which occur only around twice a century, a decisive test of the $3+3$ model could involve observing an extragalactic supernova neutrino burst, that is a cluster of neutrinos in a specific time window well beyond what chance would predict. Even though existing searches for such bursts have yielded only upper limits on the extragalactic supernova frequency within a certain distance, it is shown that the choice of a one-day window for possible neutrino clusters in time might be far more sensitive. A search using a one day time window could be done using existing data, and if a signal is found it would confirm the $3+3$ model. Of course, the absence of any day-long neutrino burst would not disprove the model, since it could mean only that the nearest supernova during the period when detectors were active was simply too far to be detected. Finally, apart from testing the 3 + 3 model, an alternative type of search is suggested using existing hadronic cosmic ray data (from the IceCube Collaboration) that might verify the tachyonic neutrino hypothesis.

1) Background: the budget of non-thermal energy in galaxy clusters is not well constrained, owing to the observational and theoretical difficulties in studying these diluted plasmas on large scales. 2) Method: we use recent cosmological simulations with complex physics in order to connect the emergence of non-thermal energy to the underlying evolution of gas and dark matter. 3) Results: the impact of non-thermal energy (e.g. cosmic rays, magnetic fields and turbulent motions) is found to increase in the outer region of galaxy clusters. Within numerical and theoretical uncertainties, turbulent motions dominate the budget of non-thermal energy in most of the cosmic volume. 4) Conclusion: assessing the distribution non-thermal energy in galaxy clusters is crucial to perform high-precision cosmology in the future. Constraining the level of non-thermal energy in cluster outskirts will improve our understanding of the acceleration of relativistic particles by cosmic shocks and of the origin of extragalactic magnetic fields.

Rapidly rotating neutron stars with very strong surface magnetic fields are observed to emit pulsed emission in the whole range of electromagnetic spectrum from radio to high energy gamma-rays. These so called pulsars are known for their exceptional rotational stability. The radio emission from pulsars is generally believed to be powered by the rotational energy of neutron stars. More than 3000 pulsars have been currently known from radio observations, however, it is observed that a large population of pulsars is also bright in optical, X-rays and gamma-rays. The Fermi-LAT observations in the energy range above 100 MeV have discovered about 300 pulsars. However, origin of high energy non-thermal radiation from pulsars is not completely understood and remains an active area of research. In this contribution, we report a summary of observational features of the gamma-ray pulsars and perform pulsar population study to predict their detectability for the MACE gamma-ray telescope, which has just started its regular science operation at Hanle in India.

Oxidative stress (OS) occurs from excessive reactive oxygen species or a deficiency of antioxidants – primarily endogenous glutathione (GSH). There are many illnesses, from acute and post-COVID-19, diabetes, myocardial infarction, to Alzheimer’s disease, that are associated with OS. These dissimilar illnesses are in order, a viral infection, a metabolic disorder, an ischemic event, and a neurodegenerative disorder. OS may be an early initiator or a significant promotor of their progressive pathophysiologic processes. Consequently, addressing initial OS-related pathology may avoid subsequent severe and irreversible complications. Early intervention would modulate multiple factors, including cytokine stimulation, complement dysregulation, immuno-thrombosis, fibrosis, and autoimmunity. Past clinical studies that addressed OS have had equivocal results. It may be due to the use of ineffective antioxidants, an untimely delay in their use, or an inefficient delivery system. Experimental studies have used antioxidants that are not available for clinical trials. Although GSH can significantly reduce OS, its exogenous use is hampered by the lack of an effective delivery system. By incorporating GSH into cyclodextrin (CD) through nanotechnology, there is recent evidence that exogenous GSH can be delivered more effectively to prevent or mitigate injury from OS [1]. Future studies using the GSH/cyclodextrin (GC) complex will be needed to confirm its effectiveness and, hopefully, offer a path to treat many sub-optimally managed or currently untreatable illnesses.

The stellar winds of the central stars of planetary nebulae play an essential role in planetary nebulae shaping. In the interacting stellar winds model, the fast stellar wind injects energy and momentum which are transfered to the nebular envelope through an X-ray-emitting hot bubble. Together with other physical processes, such as the ionization of the nebular envelope, the asymmetrical mass-loss in the AGB, and the action of collimated outflows and magnetic fields, the presurized hot gas determines the expansion and evolution of planetary nebulae. \emph{Chandra} and \emph{XMM-Newton} have provided us with detailed information of this hot gas. Here in this talk I will review our current understanding of the effects of the fast stellar wind in the shaping and evolution of planetary nebulae and give some hints of the promissing future of this research.

This paper offers a comprehensive examination of the process involved in developing and automating supervised end-to-end machine learning workflows for forecasting and classification purposes. It offers a complete overview of the components (i.e. feature engineering, model selection, etc), principles (i.e. bias-variance decomposition, model complexity, overfitting, model sensitivity to feature assumptions and scaling, output interpretability, etc), models (i.e. neural networks, regression models, etc), methods (i.e. Cross-Validation, data augmentation, etc), metrics (i.e. Mean Squared Error, F1-score, etc) and tools that rule most supervised learning applications with numerical and categorical data, as well as their integration, automation, and deployment. The end goal and contribution of this paper is the education and guidance of the non-AI expert academic community over complete and rigorous machine learning pipelines and data science practices, from problem scoping to design and state-of-the-art automation tools, including basic principles and reasoning in the choice of methods. The paper delves into the critical stages of supervised machine learning workflow development, many of which are often omitted by researchers due to brevity, and covers foundational concepts essential for understanding and optimizing a functional machine learning workflow, thereby offering a holistic view of task-specific application development for applied researchers who are not AI experts.

Fundamental science and applied research and technology development (RTD) are facing significant challenges that particularly compound to the notorious credibility, reproducibility, funding and sustainability crises. The underlying, serious shortcomings are substantially amplified by a metrics-obsessed publication culture, and a growing cohort of academics fishing for fairly stagnant (public) funding budgets. This work presents, for the first time, a groundbreaking strategy to successfully address these severe issues; the novel strategy proposed here leverages the distributed ledger technology (DLT) “blockchain” to capitalize on cryptoeconomic mechanisms, such as tokenization, consensus, crowdsourcing, smart contracts, reputation systems as well as staking, reward and slashing mechanisms. This powerful toolbox, which is so far widely unfamiliar to traditional scientific and RTD communities (“TradSci”), is synergistically combined with the exponentially growing computing capabilities for virtualizing experiments through digital twin methods in a future scientific “metaverse”. Project contributions, such as hypotheses, methods, experimental data, modelling, simulation, assessment, predictions and directions are crowdsourced using blockchain, and captured by so-called non-fungible tokens (“NFTs”). The so enabled, highly integrative approach, termed decentralized science (“DeSci”), is destined to move research out of its present silos, and to markedly enhance quality, credibility, efficiency, transparency, inclusiveness, sustainability, impact, and sustainability of a wide spectrum of academic and commercial research initiatives.

Natural circulation loop (NCL) systems are buoyancy-driven heat exchangers that are used in various industrial applications. The concept of passive heat exchange in NCL systems is attractive, because there is no need for an externally driven equipment (e.g., a pump) to maintain the fluid circulation. However, relying on buoyancy as the sole driving force may lead to several potential difficulties, one of which is generation of (possibly) time-varying nonlinearities in the dynamical system, where a difference in the time scales of heat transfer and fluid flow causes the flow to change from a steady-state regime to either an oscillatory regime or a flow-reversal regime, both of which are undesirable. In this paper, tools of symbolic time series analysis (e.g., probabilistic finite state automata (PFSA)) are proposed to identify selected regimes of operation in NCL systems, where the underlying principle is built upon the concept of pattern classification from measurements of fluid-flow dynamics. The proposed method is shown to be capable of identifying the current regime of operation from the initial time response under a given set of operational parameters. The efficacy of regime classification is demonstrated by testing on two data sets, generated from numerical simulation of a MATLAB SimuLink model that has previously been validated with experimental data. The results of the proposed PFSA-based classification are compared with those of a hidden Markov model (HMM) that serves as the baseline.

With the emergence of blockchain and smart contracts, traditional digital applications 1 such as identity management, supply chain management, banking and finance etc. are expected 2 to be transformed into Decentralized Applications (DApps). Blockchain interoperability is a new 3 and exciting aspect of blockchain technology that is quickly gaining popularity in many industries. 4 However, the widespread use of blockchains has not yet been achieved because DApps running on the 5 blockchain using smart contracts require access to authentic off-chain data. Users are more conscious 6 of their personal data privacy and consequently are more reluctant to share their data, posing a 7 challenge in the adoption of DApps. To solve this challenge, we present a novel quantum-resistant, 8 data authentication and zero-knowledge proof scheme named zk-DASTARK. Based on our proposed 9 scheme, we present a novel framework which can be used to feed authenticated off-chain data to 10 DApps without compromising user data privacy. Our proposed framework is quite efficient against 11 well-known off-chain data authentication frameworks. The proposed framework is implemented on 12 state-of-the-art quantum-resistant IOTA Blockchain and is highly efficient as it takes approximately 13 60 ms to generate a proof and approximately 10 ms to verify a proof.

The presence of harmful algal blooms (HABs) and cyanotoxins in drinking water sources poses a great threat to human health. The current study employed molecular techniques to determine the occurrence of non-toxic and toxic cyanobacteria species in the Limpopo River basin based on the phylogenetic analyses of 16S rRNA gene. The bottom sediments samples were collected from selected rivers: Limpopo, Crocodile, Mokolo, Mogalakwena, Nzhelele, Lephalale, Sand Rivers (South Africa); Notwane (Botswana), Shashe River and Mzingwane River (Zimbabwe). The physical-chemical analysis of the bottom sediments showed the availability of nutrients, nitrates and phosphates, in excess of 0.5 mg/l for most of river sediments, alkaline pH and salinity in excess of 500 mg/l. The FlowCam showed the dominant cyanobacteria species identified from the samples were Microcystis species, followed by Cylindrospermopsis raciborskii, Phormidium and Planktothrix species and this was confirmed by molecular techniques. Nevertheless, two samples showed the amplification of cylindrospermopsin polyketide synthetase gene (S3 and S9) while two samples showed amplification for microcystin/nodularin synthetase gene (S8 and S13). Thus these findings may imply the presence of toxic cyanobacteria species in the river sediments. The presence of cyanobacteria may be hazardous to human because rural communities and farmers who abstract water from Limpopo river catchment for human consumption, livestock and wildlife watering and irrigation.

In this study, we investigate Quantum Entanglement Asymmetry (QEA) as a potential explanation for the matter-antimatter imbalance observed in the universe. By integrating quantum mechanics with cosmological phenomena, the study proposes a model in which quantum entanglement among particle-antiparticle pairs in the early universe leads to an asymmetry favoring matter. Through theoretical development and numerical simulations, we explore how this model predicts unique patterns in Cosmic Microwave Background (CMB) anisotropies and the distribution of matter, setting a foundation for empirical verification. The study aims to enhance the understanding of cosmological asymmetries and highlight the significance of quantum entanglement in the universe's evolution.

This article investigates on the radial and non-radial geodesic structures of the generalized K-essence Vaidya spacetime. Within the framework of K-essence geometry, it is important to note that the metric does not possess conformal equivalence to the conventional gravitational metric. This study employs a non-canonical action of the Dirac-Born-Infeld kind. In this work, we categorize the generalized K-essence Vaidya mass function into two distinct forms. Both the forms of the mass functions have been extensively utilized to analyze the radial and non-radial time-like or null geodesics in great details inside the comoving plane. Indications of the existence of wormhole can be noted during the extreme phases of spacetime, particularly in relation to black holes and white holes, which resemble the Einstein-Rosen bridge. In addition, we have also detected the distinctive indication of the quantum tunneling phenomenon around the central singularity.

Bistatic radar experiments have been used to study surface characteristics of extra-terrestrial bodies in the Solar System, including the Moon, Venus, Mars, and Titan. This paper proposes a 3D model to characterize the scattered field of a Gaussian rough surface on an extra-terrestrial body for an orbital bistatic radar configuration. Specifically, this model will investigate how the variability of surface roughness impacts the spectral broadening of the received signal using physical optics approximations and ray tracing on a surface model using a facet approach with Gaussian properties. A linear relationship between spectral broadening of the signal and surface roughness was found. This relationship is in line with results obtained by commonly used analytical models for bistatic radar on planetary surfaces.

We present a Quantum Space Model (QSM) of the evolution of the universe based on the theory that space consists of energy quanta from which it began. We used the Friedmann equations to trace its history and show that Dark Energy is the energy of space which caused its accelerating expansion.The universe started from a quanta of space which was triggered by quantum fluctuations that caused the Big Bang. It then expanded and cooled undergoing phase transitions to radiation, fundamental particles, and matter. Matter grew into galaxies, and was consolidated by gravity into Black Holes, ending in a Big Crunch and Deep Freeze inside a Black hole at 1.380 trillion years. Fluctuations caused a new Bang to start another cycle in its life. If the Law of Conservation of Energy is universal, then the cosmos is eternal. Our results support the theoretical predictions of a cyclic universe by Steinhardt and associates, as well as Penrose. Space and energy are equivalent as embodied in the Planck energy equation. They are the two most fundamental quantities that govern cosmic evolution. The two principal long range forces are the gravitational force and the space force,which maybe the fifth force in the universe. They provide the clockwork mechanism operating our cyclic universe.

Background: Bioelectrical impedance (BIA) and ultrasound (US) have become popular for estimating body fat percentage (BF%) due to their low cost and clinical convenience. However, agreement of these devices with gold standard method still require investigation. The aim was to analyze the agreement between a gold standard %BF assessment method with BIA and US devices. Methods: Twenty-three men (age 30.1 ± 7.7 years, 82.5 ± 14.9 kg, 1.77 ± 0.05 m) underwent Dual Energy X-Ray Absorptiometry (DXA), BIA (tetrapolar) and US (three-site method) %BF assessment. Pearson and concordance correlations were analyzed. T-test compared means between methods, and Bland Altman plots analyzed agreement and proportional bias. Alpha was set at &lt; .05. Results: Pearson coefficients between BIA and US with DXA were high (BIA = 0.94; US = 0.89; both p &lt; .001). Concordance coefficient was high for BIA (0.80) and moderate for US (0.49). BF% measured by BIA (24.5 ± 7.5) and US (19.4 ± 7.0) were on average 4.4% and 9.6% lower than DXA (29.0 + 8.5%), respectively (p &lt; .001). Lower and upper agreement limits between DXA and BIA were -1.45 and 10.31, while between DXA and US were 2.01 and 17.14, respectively. There was a tendency of both BIA (p = .09) and US (p = .057) to present proportional bias and underestimate BF%. Conclusions: Despite the correlation, the mean difference between the methods were significant, and the agreement limits are very wide. This indicate that BIA and US, as measured in this study, have limited potential to accurately measure %BF compared to DXA, especially in individuals with higher body fat.

We propose a toy model of a spherical universe made up of an exotic dark gas with temperature $T$ in thermal equilibrium with a black-body. Each particle of this exotic gas mimics a kind of particle of dark energy. So, each dark particle occupies a very small area of space so-called Planck area $L_p^{2}$, which represents the minimum area of the whole space-time given by the spherical surface with area $4\pi R_H^2$, where $R_H$ is the Hubble radius. We realize that such spherical surface is the surface of the black-body for representing the dark universe as if it were the surface of an expanding balloon. Thus, we are able to derive the law of universal gravitation, thus leading us to understand the cosmological anti-gravity. We estimate the tiny order of magnitude of the cosmological constant and the acceleration of expansion of the dark sphere. In this toy model, as the dark universe can be thought of as a large black body, when we obtain its power and frequency of emission of radiation, we find very low values. We conclude that such radiation and frequency of the black body made up of dark energy is a background gravitational wave with very low frequency in the order of $\sim 10^{-17}$Hz due to the slight stretching of the fabric of space-time.

Inflationary model provides a conceptual explanation of the horizon problem, the flatness problem and may also suppress the over abundant magnetic monopoles predicted by Grand Unified Theories. Although various inflationary models have been proposed since 1981, difficulties like fine tuning is not only unsolved but also becomes severer in confrontation with data of Planck Satellite. This paper proposes an alternative model of inflation: the spontaneous symmetry breaking phase transition at early universe is only responsible for the production of magnetic monopoles expected by Grand Unified Theories; it is the subsequent energy release of monopole annihilation that drives the inflation. As a result, the early universe underwent a free expansion with a heat source originating in the annihilation, which expects a smooth, plateau-like potential consistent with the observational data. Beside interpreting a number of long standing inflationary problems, the new scenario predicts a significant increase of entropy during the inflation, and tends to produce large scale structures exceed scale of 300 million light-years correlated with a CMB smoothen and flatten by a simple dynamical mechanism.

The technique of Faraday tomography is a key tool for the study of magnetised plasmas in the new era of broadband radio polarisation observations. In particular, observations at metre-wavelengths provide significantly better Faraday depth accuracies compared to traditional cm-wavelength observations. However, the effect of Faraday depolarisation makes the polarised signal very challenging to detect at metre wavelengths (MHz frequencies). In this work, Faraday tomography is used to characterise the Faraday rotation properties of polarised sources found in data from the LOFAR Two-Metre Sky Survey (LoTSS). Of the 76 extragalactic polarised sources analysed here, we find that all host a radio-loud AGN. The majority of the sources (∼64%) are large FRII radio galaxies with a median projected linear size of 710 kpc and median radio luminosity at 144 MHz of 4 × 10^26 W/Hz. In several cases, both hotspots are detected in polarisation at an angular resolution of ∼20". One such case allowed a study of intergalactic magnetic fields on scales of 3.4 Mpc. Other detected source types include an FRI radio galaxy and at least 8 blazars. Most sources display simple Faraday spectra, however, we highlight one blazar that displays a complex Faraday spectrum, with two close peaks in the Faraday dispersion function.

The high mutation rate of human immunodeficiency virus type 1 (HIV-1) plays a major role in treatment resistance from the development of vaccines to long-lasting drugs. In addressing the crux of the issue, various attempts to estimate the mutation rate of HIV-1 resulted in a large range of 10-5 - 10-3 errors/bp/cycle due to the use of different types of investigation methods. In this review, we discuss the different assay methods, their findings on the mutation rates of HIV-1 and how the location of these mutations can be further analyzed for their potential allosteric effects to reveal potentially new inhibitors with different pharmacodynamics that can be used to circumvent fast occurring HIV drug resistance. Given that HIV is one of the fastest mutating viruses, it is a good model for comprehensive study of its mutations that can give rise to much horizontal understanding towards overall viral drug resistance as well as emerging viral diseases.

Agronomic traits such as biomass yield and abiotic stress tolerance are genetically complex and challenging to improve by conventional breeding strategies. Genomic selection (GS) is an alternative approach in which genome-wide markers are used to determine the genomic estimated breeding value (GEBV) of individuals in a population. In alfalfa, previous results indicated that low to moderate prediction accuracy values (<70%) were obtained in complex traits such as yield and abiotic stress resistance. There is a need to increase the prediction value in order to employ GS in breeding programs. In this paper we reviewed different statistic models and their applications in polyploid crops including alfalfa. Specifically, we used empirical data affiliated with alfalfa yield under salt stress to investigate approaches which use DNA marker importance values derived from machine learning models, and genome-wide association studies (GWAS) of marker-trait association scores based on different GWASpoly models, in weighted GBLUP analyses. This approach increased prediction accuracies from 50% to more than 80% for alfalfa yield under salt stress. This is the first report in alfalfa to use variable importance and GWAS-assisted approaches to increase the prediction accuracy of GS, thus helping to select superior alfalfa lines based on their GEBVs.

Radio Occultation (RO) is pivotal for profiling the neutral and ionized atmosphere, with the PlanetiQ mission, via its GNOMES satellites, striving to establish an advanced atmospheric observing system. However, an assessment of the spatiotemporal distributions of PlanetiQ observations and comparisons with reliable datasets are lacking. This study addresses this gap by examining the temporal and spatial distribution of RO observations from PlanetiQ during its initial 198 operational days in 2023, alongside comparisons with COSMIC and Numerical Weather Prediction (NWP) models. Data from GN02, GN03, and GN04 satellites, yielding 1099, 1313, and 1843 RO events per day respectively, were analyzed. The satellite constellation's observations demonstrate a generally well-distributed pattern, albeit minor deficiencies in equatorial and polar regions. Single-profile comparisons with COSMIC data reveal strong correlations for pressure, temperature, Water Vapor Pressure (WVP), and refractivity profiles, with temperature exhibiting larger variations (RMSE = 1.24°C). Statistical analyses confirm statistically insignificant differences between PlanetiQ and COSMIC profiles at the same spatio-temporal coordinates. Comparisons with NWP models show slight differences with GFS, with overall RMSE values of 0.23 mb (WVP), 0.6 mb (pressure), 1.3 (refractivity), and 1.5°C (temperature). However, assessments against GFS/ECMWF models indicate overall compatibility, with insignificant differences between PlanetiQ profiles and models observations.