Surgical simulators are crucial in early craniofacial and plastic surgical training, necessitating synthetic materials that accurately replicate tissue properties. Recent critiques of our lab’s currently deployed silicone surrogate have highlighted numerous areas for improvement. To further refine our models, our group's objective is to find a composition of materials that is closest in fidelity to native oral mucosa during surgical rehearsal by expert craniofacial surgeons. Fifteen platinum silicone-based surrogate samples were constructed with variable hardness and slacker percentages. These samples underwent evaluation of tactile sensation, hardness, needle puncture, cut resistance, suture retention, defect repair, and tensile elasticity. Expert craniofacial surgeon evaluators provided focused qualitative feedback on selected top-performing samples for further assessment and statistical comparisons. Evaluation revealed surrogate characteristics with satisfactory to good performance. Sample 977 exhibited the highest performance, and comparison with the original surrogate (sample 810) demonstrated significant improvements in critical areas, emphasizing the efficacy of the refined composition. The study identified a silicone composition that directly addresses the feedback received by our team’s original silicone surrogate. The study underscores the delicate balance between biofidelity and practicality in surgical simulation. The need for ongoing refinement in surrogate materials is evident to optimize training experiences for early surgical learners.

Surgical simulators are crucial in early craniofacial and plastic surgical training, necessitating synthetic materials that accurately replicate tissue properties. Recent critiques of our lab’s currently deployed silicone surrogate have highlighted numerous areas for improvement. To further refine our models, our group's objective is to find a composition of materials that is closest in fidelity to native oral mucosa during surgical rehearsal by expert craniofacial surgeons. Fifteen platinum silicone-based surrogate samples were constructed with variable hardness and slacker percentages. These samples underwent evaluation of tactile sensation, hardness, needle puncture, cut resistance, suture retention, defect repair, and tensile elasticity. Expert craniofacial surgeon evaluators provided focused qualitative feedback on selected top-performing samples for further assessment and statistical comparisons. Evaluation revealed surrogate characteristics with satisfactory to good performance. Sample 977 exhibited the highest performance, and comparison with the original surrogate (sample 810) demonstrated significant improvements in critical areas, emphasizing the efficacy of the refined composition. The study identified a silicone composition that directly addresses the feedback received by our team’s original silicone surrogate. The study underscores the delicate balance between biofidelity and practicality in surgical simulation. The need for ongoing refinement in surrogate materials is evident to optimize training experiences for early surgical learners.

The authors attempt to addresses the importance of timely detection and management of cervical intraepithelial neoplasia (CIN) to prevent cervical cancer. The study focuses on the potential of electrical impedance spectroscopy (EIS) as an adjunct to colposcopy, aiming to enhance the accuracy of identifying high-grade cervical lesions. Colposcopy, a widely used technique, exhibits variable sensitivity in detecting high-grade lesions, which relies on the expertise of the operator. The study's primary objective is to evaluate the effectiveness of combining colposcopy with EIS in detecting high-grade cervical lesions among patients initially diagnosed with low-grade CIN based on cytology. We employ a cross-sectional observational design, recruiting 101 women with abnormal cervical cytology results. The participants undergo colposcopy with acetic acid and subsequent EIS using the ZedScan device. The ZedScan results are categorized into color-coded probability levels, with red indicating the highest likelihood of high-grade squamous intraepithelial lesions (HSIL) occurrence. Results reveal that ZedScan exhibits a sensitivity rate of 89.5% and a specificity rate of 84% for detecting high-grade lesions. Colposcopy, on the other hand, records a sensitivity rate of 85.5% and a specificity rate of 92%. The agreement rate between ZedScan and biopsy is 79.2%, as indicated by a kappa coefficient of 0.71, while the agreement rate between colposcopy and biopsy is 74.3%, with a kappa coefficient of 0.71.

Aneuploidy describes the gain or loss of entire chromosomes or chromosome arms. Already more than 100 years ago, aneuploidy was described to be featured in cancer and it is known today to be present in 68-90 % of cancers, depending on tumour entity. Aneuploidy is implicated to affect cancer growth, therapy response and frequently affects prognosis. Chromosomal instability (CIN) is recognized as the main cause of aneuploidy and is characterised as the fluent process of gaining or losing chromosomes. Chromosomally instable cells need to be kept in check, or cleared, to prohibit the sampling of aneuploid karyotypes able to drive tumorigenesis. Of note, even aneuploid cancer cells often show CIN, a feature that promotes therapy related drug-resistance. Here, we review how CIN can be prevented or limited to spread by the induction of cell death and the relevance of different p53 responses triggered in response to mitotic perturbations to prohibit the formation of cancer driving aneuploidies.

Particles in classical physics are distinguishable objects, which can be picked out individually on the basis of their unique physical properties. By contrast, in quantum mechanics the standard view is that particles of the same kind (``identical particles'') are completely indistinguishable from each other. This standard view is problematic: Particle indistinguishability is irreconcilable not only with the very meaning of ``particle'' in ordinary language and in classical physical theory, but also with how this term is used in the practice of present-day physics. Moreover, the indistinguishability doctrine prevents a smooth transition from quantum particles to what we normally understand by ``particles'' in the classical limit of quantum mechanics. Elaborating on earlier work, we here discuss an alternative to the standard view that avoids these and similar problems. As it turns out, this alternative approach connects to recent discussions in quantum information theory concerning the question of when identical particles can be considered to be entangled.

This qualitative research explores the dynamics of collaborative marketing and supply chain strategies for enhanced product lifecycle management. Through in-depth interviews with industry stakeholders, key themes, challenges, and implications of collaboration emerge. Trust, communication, technology, strategic alignment, and sustainability are identified as critical factors driving successful collaboration. The study highlights the transformative potential of collaboration in driving innovation, efficiency, and customer satisfaction. Despite challenges such as aligning objectives and ensuring data security, collaborative strategies offer significant opportunities for value creation and differentiation. The findings underscore the importance of building trust, leveraging technology, and integrating sustainability considerations in collaborative efforts. Strategic alignment and cultural fit among partners are essential for overcoming differences and achieving common goals. The implications of the research extend to practitioners seeking to enhance collaboration in their organizations and researchers exploring collaborative practices in different industries and contexts. Future research could further explore the impact of collaboration on stakeholder perspectives and outcomes. By addressing challenges and leveraging opportunities, organizations can maximize the benefits of collaborative marketing and supply chain strategies to drive sustainable growth and competitive advantage in today's dynamic business landscape.

Ontological premises have profound theoretical implications. This analysis posits a single, universal structure composed of two ontic entities: discrete, quantized units of space ("Planck Spheres") and a State of Absolute Nothingness (the "SOAN"). Planck Spheres and the SOAN form a physical, ultra-high (3 x N) dimensional space ("Planck Space") and a discrete 3D space (or "4D spacetime"). Together, Planck Space and 4D spacetime form a tightly integrated ((3 x N) + 3) hyperspace (the "Dual Ontology"). Critically, a one-to-one mapping and identity exists between the Planck Spheres comprising 4D spacetime and Planck Space. The Dual Ontology conjecture supports radically simplified physical explanations for three distinct areas of theoretical physics: First, the conjecture reconciles fundamental issues in Special Relativity and quantum mechanics by explaining why single and N-body quantum states (a) dynamically evolve in 4D spacetime subject to the speed of light and (b) instantaneously collapse in a physical Planck Space that is not subject to Special Relativity. Second, the temporal and physical asymmetry between the dynamic evolution of quantum states in 4D spacetime subject to Special Relativity and the instantaneous collapse of quantum states in a Planck Space where Special Relativity is inapplicable explains quantum path irreversibility and the arrow of time. Third, at or near the heat death of 4D spacetime, the instantaneous collapse of the energy content of Planck Space and the simultaneous transition of 4D spacetime's extremely widely dispersed energy content to a non-singular, generally localized volume at t = 0 explains 4D spacetime's isotropy, homogeneity, extremely high energy, pressure, and temperature, flatness, and low gravitational entropy. It also explains the horizon and fine-tuning problems.

Objective: This study aimed to validate the use of liquid phenol-based chemical peeling therapy for cervico-vaginal intraepithelial neoplasia (CIN and VaIN), with the goal of circumventing obstetric complications associated with surgical treatment. Methods: A total of 483 eligible women diagnosed with CIN and/or VaIN participated in this study. Participants underwent phenol-based chemical peeling therapy every 4 weeks until disease clearance. Disease clearance was determined by negative Pap tests for four consecutive weeks. HPV genotyping was conducted at the onset of the study and after disease clearance in select cases. Results: Among the 476 participants (excluding those with cancer), the number of treatment sessions until CIN/VaIN clearance ranged from 2 to 49 (median = 7 sessions). Forty-five participants (9.4%) underwent surgical treatments. Seven participants (1.5%) experienced recurrence, presenting with CIN2/VaIN2 or worse lesions; of these, three underwent LEEP, while four repeated the chemical peeling therapy. No obstetrical complications were noted among the 98 pregnancies following this therapy. The findings suggest that phenol-based therapy is safe and effective for CIN, although it requires numerous and lengthy treatments. Factors associated with resistance to this therapy include immune suppression, high-grade lesions, multiple HPV type infection, and direct or passive smoking.

Purpose: This research investigates the influence of supplier relationship management methods on the operational efficiency and customer satisfaction of Italian restaurants.Design/Methodology/Approach: Employing a qualitative research methodology, data was gathered via interviews and questionnaires from a sample of 200 individuals across many Italian restaurants throughout Italy.Findings: The investigation uncovered robust relationships between supplier relationship management approaches and other operational factors, highlighting the interdependence of management tactics. Efficient management of supplier relationships not only improves the efficiency of the supply chain, but also has an impact on the procurement of ingredients, the variety of menu options, and the integration of technology.Research Limitations/Implications: Although technology developments were shown to enhance operational efficiency, their influence on customer satisfaction was minimal. The research highlights the complex nature of factors that influence customer happiness, indicating the need of adopting a well-rounded strategy that combines technology with personalised care. Identified continuous improvement opportunities provide valuable insights for restaurant owners to enhance strategy and better meet consumer expectations.Practical Implications: This research provides useful insights on the management of Italian restaurants, but it has limitations due to its qualitative approach and dependence on self-reported data.Social Implications: However, the results add to the current knowledge and provide practical consequences for restaurant owners who want to improve their operational efficiency and customer pleasure.Originality/Value: Italian restaurants may achieve long-term success in a highly competitive culinary industry by acknowledging the interdependence of management strategies and using customer-focused techniques.

The inability to delineate a unified physical ontology that accounts simultaneously for the laws of special relativity and the results of quantum experiments has been a defining problem in physics for more than 100 years. This analysis addresses the problem by positing an ontic, mixed ontology composed of a “discrete” 4D spacetime and a physical, ultra-high dimensional (3 x N) “Planck Space.” Together, Planck Space and the three spatial dimensions of 4D spacetime form a tightly integrated ((3 x N) + 3) hyperspace (the “Dual Ontology”). Critically, the Dual Ontology’s structure replaces 1) the continuous, differentiable manifold of 4D spacetime with a discrete 4D spacetime and 2) mathematical 3N configuration spaces with a physical (3 x N) Planck Space. Moreover, the Dual Ontology is structurally and dynamically predicated on the one-to-one mapping and identity between the discrete spatial units that simultaneously form 4D spacetime and Planck Space. The one-to-one mapping and identity of the discrete spatial units support an integrated quantum dynamics based upon the dynamic evolution of single and N-body quantum states in 4D spacetime in full compliance with the laws of special relativity and the instantaneous collapse of all quantum states in an ontic Planck Space, where special and general relativity and more generally, 4D spacetime’s laws of physics, do not apply.

Time can be a difficult concept to understand. Albert Einstein, who viewed time as an illusion, explained the passage of time is relative to the observer’s frame of reference in the space-time continuum. However, the state of consciousness of the observer also influences the passage of time. This paper examines the relationship between the experience of time and different states of consciousness including near-death experiences, mystical states of consciousness, and psychedelic medicine-induced states of consciousness. Two different experiences of time are described. These are Chronos and Kairos. Chronos is described as 4th dimensional time whereas Kairos is 5th dimension time. Methods for facilitating the experience of Kairos are discussed and the potential benefits of experiencing Kairos are reviewed.

Accurate inundation maps for flooded wetlands and rivers are a critical resource for their management and conservation. In this paper we automate a method (thresholding of the short-wave infrared band) for classifying inundation, using Landsat imagery and Google Earth Engine. We demonstrate the method in the Okavango Delta, northern Botswana, a complex case study due to the spectral overlap between inundated areas covered with aquatic vegetation and dryland vegetation classes on satellite imagery. Inundation classifications in the Okavango Delta have predominately been implemented on broad spatial resolution images. We present the longest time series to date (1990-2019) of inundation maps at high spatial resolution (30m) for the Okavango Delta. We validated the maps using image-based and in situ data accuracy assessments, with accuracy ranging from 91.5 - 98.1%. Use of Landsat imagery resulted in consistently lower estimates of inundation extent than previous studies, likely due to the increased number of mixed pixels that occur when using broad spatial resolution imagery, which can lead to overestimations of the size of inundated areas. We provide the inundation maps and Google Earth Engine code for public use.

The Leguminosae (legume family) is divided into three sub-families, the Caesalpiniodeae, Mimosoideae and Papilionoideae. Here, the literature on legume-rhizobia symbioses was reviewed, and genotypically characterised rhizobia related to the taxonomy of the legumes they were isolated from. Only data from field soils were considered. The objective of the work was to assess to what extent legume specificity for rhizobial symbiont is related to legume taxonomy. Bradyrhizobium spp. were the exclusive rhizobial symbionts of species in the Caesalpinioideae but data are limited. Where tested, species within the two Mimosoideae tribes, Ingeae and Mimoseae were nodulated by different rhizobial genera. Generally, Papilionoideae species with indeterminate nodules were promiscuous in relation to rhizobial symbionts but high specificity for rhizobial partners appears to hold at tribe level for the Fabeae (Rhizobium spp.), genus level for Medicago (Ensifer spp.), Cytisus (Bradyrhizobium spp.) and Lupinus (Bradyrhizobium spp.), and species level for Galega spp. (Neorhizobium galegeae), Hedysarum coronarium (Rhizobium sullae), Cicer arietinum (Mesorhizobium spp.) and New Zealand native Sophora spp. (Mesorhizobium spp.). High legume specificity for rhizobial symbionts was linked to specific rhizobial symbiosis genes. For Papilionoideae species with determinate nodules, the Dalbergieae were primarily nodulated by Bradyrhizobium but were promiscuous with respect to Bradyrhizobium spp. while those in the Desmodieae, Phaseoleae, Psoraleae and Loteae were promiscuous across different rhizobial genera. Possible advantages and disadvantages of high specificity or promiscuity are discussed.

This study investigates the impact of integrated marketing strategies on supply chain efficiency in retail businesses. Through qualitative research methods including in-depth interviews and case studies, the study explores how aligning marketing activities with supply chain operations influences various aspects of retail performance. The findings reveal that integrated marketing strategies lead to enhanced demand forecasting accuracy, improved customer satisfaction, and greater operational efficiency. By leveraging technology, such as artificial intelligence and data analytics, retailers can optimize inventory management, personalize offerings, and anticipate consumer preferences in real-time. Cross-functional collaboration and effective leadership emerge as crucial factors in fostering integration and overcoming challenges such as data management and cultural resistance. Additionally, the study highlights the significance of sustainability and entrepreneurship in driving integrated strategies, with implications for long-term competitiveness and brand reputation. The findings underscore the importance of viewing marketing and supply chain functions as interconnected elements of a holistic business strategy, rather than operating in silos. The study offers valuable insights for theory, practice, and future research, emphasizing the need for holistic and collaborative approaches to integration in the dynamic retail landscape. By embracing integrated marketing strategies, retailers can position themselves for success in an increasingly competitive market environment, driving innovation, efficiency, and customer satisfaction.

Organoid engineering promises to revolutionize medicine with wide ranging applications of scientific, engineering, and clinical interest, including precision and personalized medicine, gene editing, drug development, disease modeling, cellular therapy, and a basic understanding of human development. Organoids are a three-dimensional (3D), miniature, caricature of a target organ, are initiated with stem/progenitor cells, and are extremely promising tools to model organ function. The biological basis for organoids is that they foster stem cell-self renewal, differentiation, and self-organization, recapitulating tissue structure or function better than 2D systems. In this review, we first discuss the importance of epithelial organs and the general properties of epithelial cells to provide context for the liver, pancreas, and gall bladder and rationale for organoid cultures. Next, we develop a general framework to understand self-organization, tissue hierarchy, and organoid cultivation. For each of these areas, we provide historical context, and review both a wide range of biological and/or biophysical/mathematic perspectives that enhances understanding of organoids. Next, we review existing techniques and progress in hepatobiliary and pancreatic organoid engineering. To do this, we review organoids from both primary tissues, cell lines, and stem cells, and introduce engineering studies when applicable. Noninvasive assessment of 1 organoids can reveal underlying biology and enable improved assays for growth, metabolism, and function. Applications of organoid for cell therapy are also discussed. Taken together, we establish a broad strong scientific foundation for organoids and provide an in-depth review of hepatic, biliary and pancreatic organoids.

Climate change is rapidly exacerbating and adding to major-to-existential issues associated with fresh water availability and utilization. The massive thus far untapped saline/salt water - oceans/wastelands/deserts – Halophytes resources nexus can, at scale and profitably provide major climate change mitigation and greatly alleviate most extant fresh water issues. Approaches include ocean fertilization and saline/seawater agriculture on deserts and wastelands to sequester massive amounts of CO2 and methane and for food, freeing up the some 70% of the fresh water now utilized by current agriculture for direct human use. Also enables production of huge amounts of Bio/SAF fuels and bio mass based chemical feed stock employing the massive capacity of cheap saline/ seawater and cheap deserts, wastelands. Overall saline/ seawater can, uniquely, at the scale of the climate and fresh water issues, without desalinization, profitably, utilizing extant technologies and the some 44% of the land that is deserts/ wastelands, and the 97% of the water that is saline/ seawater rapidly, seriously, address land, fresh water, food, energy and climate.

.In his groundbreaking 1905 paper on special relativity, Einstein distinguished between local and global time in inertial systems, introducing his famous definition of distant simultaneity to give physical content to the notion of global time. Over the following decade, Einstein attempted to generalize this analysis of relativistic time to include accelerated frames of reference, which, according to the principle of equivalence, should also account for time in the presence of gravity. Characteristically, Einstein's methodology during this period focused on simple, intuitively accessible physical situations, exhibiting a high degree of symmetry. However, in the final general theory of relativity, the a priori existence of such global symmetries cannot be assumed. Despite this, Einstein repeated some of his early reasoning patterns even in his 1916 review paper on general relativity and in later writings. Modern commentators have criticized these arguments as confused, invalid, and inconsistent. Here, we defend Einstein in the specific context of his use of global time and his derivations of the gravitational redshift formula. We argue that a detailed examination of Einstein's early work clarifies his later reasoning and demonstrates its consistency and validity.

Sea cucumbers (Holothuroidea; Echinodermata) are ecologically significant constituents of benthic marine habitats. We surveilled RNA viruses inhabiting 8 species (representing 4 families) of holothurian collected from four geographically distinct locations by viral metagenomics, including a single specimen of Apostichopus californicus affected by a hitherto undocumented wasting disease. The RNA virome comprised genome fragments of both single-stranded positive sense and double stranded RNA viruses, including those assigned to the Picornavirales, Ghabrivirales, and Amarillovirales. We discovered an unconventional flavivirus genome fragment which was most similar to a shark virus. Ghabivirales-like genome fragments were most similar to fungal totiviruses in both genome architecture and homology, and likely infected mycobiome constituents. Picornavirales, which are commonly retrieved in host-associated viral metagenomes, were similar to invertebrate transcriptome-derived picorna-like viruses. Sequence reads recruited from the grossly normal A. californicus metavirome to nearly all viral genome fragments recovered from the wasting-affected A. californicus. The greatest number of viral genome fragments was recovered from wasting A. californicus compared to any other surveyed holothurian, including the grossly normal A. californicus, which reflects a pattern observed in viral metagenomics study of sea star wasting. These results expand the known host range of flaviviruses, and suggest that fungi and their viruses may play roles in holothurian ecology.

Distributed fiber optic strain measurement techniques have become increasingly important in recent years, especially in the field of structural health monitoring of reinforced concrete structures. Numerous publications show the various monitoring possibilities from bridges to special heavy structures. The present study is intended to demonstrate the possibilities, but also the challenges, of distributed fiber optic strain measurement in reinforced concrete structures. For this purpose, concrete beams for 3-point bending tests were equipped with optical fibers on the reinforcement and concrete surface as well as in the concrete matrix in order to record the strains in the compression and tension zone. In parallel, an analytical approach based on the maximum strains in the uncracked and cracked states was performed using the Eurocode~2 interpolation coefficient. In principle, the structural design correlates with the measured values, but the strains are underestimated, especially in the cracked zone. During load increase, structural distortions in the compression zone affected the strain signal, making reliable evaluation in this zone difficult. The information content of distributed fiber optic strain measurement in reinforced concrete structures can offer tremendous opportunities. Future research should consider all aspects of the bond, sensor selection and positioning. In addition, there is a lack of information on the long-term stability of the joint and the fiber coating, as well as the effects of dynamic loading.

A case study is presented which demonstrates the value and validity of a novel approach to the use of consolidated amateur (‘ham’) radio reception reports as indicators of the presence of intense ionospheric sporadic E (Es). It is shown that the use of amateur data can provide an important supplement to other techniques, allowing the detection and tracking of Es where no suitable ionosonde or other measurements are available. The effectiveness of the approach is demonstrated by reference to ionosonde data, and the advantages and limitations of the technique are discussed.

Technologies around the world produce and interact with geospatial data instantaneously, from mobile web applications to satellite imagery that is collected and processed across the globe daily. Big raster data allows researchers to integrate and uncover new knowledge about geospatial patterns and processes. However, we are also at a critical moment, as we have an ever-growing number of big data platforms that are being co-opted to support spatial analysis. A gap in the literature is the lack of a robust framework to assess the capabilities of geospatial analysis on big data platforms. This research begins to address this issue by establishing a geospatial benchmark that employs freely accessible datasets to provide a comprehensive comparison across big data platforms. The benchmark is a critical for evaluating the performance of spatial operations on big data platforms. It provides a common framework to compare existing platforms as well as evaluate new platforms. The benchmark is applied to three big data platforms and reports computing times and performance bottlenecks so that GIScientists can make informed choices regarding the performance of each platform. Each platform is evaluated for five raster operations: pixel count, reclassification, raster add, focal averaging, and zonal statistics using three different datasets.

The identification of informal settlements in urban areas is an important step in developing and implementing pro-poor urban policies. Understanding when, where and who lives inside informal settlements is critical to efforts to improve their resilience. This study aims to analyse the capability of machine-learning (ML) methods to map informal areas in Jeddah, Saudi Arabia, using very-high-resolution (VHR) imagery and terrain data. Fourteen indicators of settlement characteristics were derived and mapped using an object-based ML approach and VHR imagery. These indicators were categorised according to three different spatial levels: environ, settlement and object. The most useful indicators for prediction were found to be density and texture measures, (with random forest (RF) relative importance measures of over 25% and 23% respectively). The success of this approach was evaluated using a small, fully independent validation dataset. Informal areas were mapped with an overall accuracy of 91%. Object-based ML as a hybrid approach performed better (8%) than object-based image analysis alone due to its ability to encompass all available geospatial levels.

The direct detection of dark matter constituents, in particular the weakly interacting massive particles (WIMPs), is central to particle physics and cosmology. In this paper we develop the formalism for WIMP-Nucleus induced transitions from isomeric nuclear states. We specialize it in the case of the experimentally interesting target 180 Ta

Reinforced concrete (RC) columns are often placed under confinement to increase their strength and ductility. Carbon fiber reinforced polymer (CFRP) materials have recently been recognized as favorable confinement systems. At present, a number of national standards and codes dedicated to the design of concrete components strengthened with CFRP in general and CFRP confinement in particular are available. These sets of rules provide design equations for confined reinforced concrete columns with circular and rectangular cross sections. Most of the standards and codes exhibit significant differences, including the used predictive models limitations, observed effects, and covered loading conditions. In this paper, five international standards and design guidelines are introduced and discussed. The purpose is to present a constructive and critical assessment of the state-of-the-art design methodologies available for CFRP confined RC columns and to discuss effects not previously considered properly. Therefore, some recent research efforts and findings from the Leipzig University of Applied Sciences are also introduced. The obtained data is used for a comparative study of the guideline predictive equations. Furthermore, it is shown that some new findings concerning the rupture strength and the maximum strength plus accompanying axial strain of a CFRP confined column are suitable to improve the current guidelines.

The purpose of this study is to estimate the mean transitioning probabilities from a Healthy state to malaria positive uncomplicated state or to malaria positive severe state. It also classifies the various transitioning probabilities of moving through the various states based on some baseline characteristics. Malaria test results for 2019 over a 12-month period were collected from the University of Ghana school clinic. An H-U model for the study was developed and the transition rates from the cross-sectional data are indicated. With two states Healthy (H) and Uncomplicated (U) forming a state space, there were four possible transitions. The results show that the probability of transitioning from a Healthy state to a malaria positive state is 0.03% while the probability that an individual will remain at Healthy state (H) after the test is 99.73%. It was found that if an individual is already positive and has taken medication the probability that its second test came out negative is 6.45% while the chances that it will remain positive but uncomplicated is 93.55%. The study also showed that in the long run, about 95.98% of persons who visited the student clinic with malaria symptoms recorded negative tests for malaria parasite while about 4% recorded positive for malaria. In terms of disaggregation by gender, it was realized that the number of reported negative test results were higher for females (97.08%) than for males (96.13%). However, the infection rate is higher for males (3.87%) than females (2.92%). It is recommended that in as much as the University of Ghana has two health centers (a clinic and hospital), there should be a centralized system to track students’ health so research done would not be biased.

Lithium titanates are used in various applications, such as anode materials for lithium intercalation (Li4Ti5O12) or breeding materials in fusion reactors (Li2TiO3). Here, we report the formation of nano-crystalline lithium titanates by a mechanochemical approach and present a deeper insight into their structural characteristics by PXRD and solid-state NMR spectroscopy. The compounds were synthesized in a high energy planetary ball mill with varying milling parameters and different grinding tools. NaCl type Li2TiO3 (α-Li2TiO3) was formed by dry milling of lithium hydroxide with titania (rutile or anatase) and by a milling induced structure transformation of monoclinic β Li2TiO3 or spinel type Li4Ti5O12. Heating of mechanochemical prepared α Li2TiO3 induces a phase transformation to the monoclinic phase similar to hydrothermal reaction products, but a higher thermal stability was observed for the mechanochemical formed product. Microstructure and crystallographic structure were characterized by PXRD via Rietveld analysis. Detailed phase analysis shows the formation of the cubic phase from the various educts. A set of two lattice parameters for α Li2TiO3 was refined, depending on the presence of OH- during the milling process. An average crystallite size of less than 15 nm was observed for the mechanochemical generated products. The local Li environment detected by 6Li SPE MAS NMR revealed Li defects in the form of tetrahedral instead of octahedral site occupation. Subsequent adjustment of the structural model for Rietveld refinement leads to better fits, supporting this interpretation.

The current surge in the deployment of web applications underscores the need to consider users' individual preferences in order to enhance their experience. In response to this, an innovative approach is emerging that focuses on the detailed analysis of interaction data captured by web browsers. This data, which includes metrics such as the number of mouse clicks, keystrokes, and navigation patterns, offers insights into user behaviour and preferences. By leveraging this information, developers can achieve a higher degree of personalization in web applications, particularly in the context of interactive elements such as online games. This paper presents the WebTraceSense project, which aims to pioneer this approach by developing a framework that encompasses a backend and frontend, advanced visualization modules, a DevOps cycle, and the integration of AI and statistical methods. The backend of this framework will be responsible for securely collecting, storing, and processing vast amounts of interaction data from various websites. The frontend will provide a user-friendly interface that allows developers to easily access and utilize the platform’s capabilities. One of the key components of this framework is the visualization modules, which will enable developers to monitor, analyse, and interpret user interactions in real-time, facilitating more informed decisions about user interface design and functionality. Furthermore, the WebTraceSense framework incorporates a DevOps cycle to ensure continuous integration and delivery, thereby promoting agile development practices and enhancing the overall efficiency of the development process. Moreover, the integration of AI methods and statistical techniques will be a cornerstone of this framework. By applying machine learning algorithms and statistical analysis, the platform will not only personalize user experiences based on historical interaction data but also infer new user behaviours and predict future preferences. In order to validate the proposed components, a case study was conducted which demonstrated the usefulness of the WebTraceSense framework in the creation of visualizations based on an existing dataset.

Grid modernization has been ushered in by rising electricity consumption, deteriorating infrastructure, and increasing reliability concerns for electric utilities. New advances, collectively referred to as the smart grid, include modern electronics, technology, telecommunications, and computing capabilities. Smart grid telecommunication frameworks provide two-way communication to support grid operations. Software-defined networking (SDN) has been proposed as a method of monitoring and controlling telecommunication networks, enabling increased smart grid visibility, control, and security. However, being connected to telecommunications infrastructure means that smart grid networks are exposed to cyber-attacks. Attackers may use unauthorized access to intercept messages, inject false data into system measurements, flood communication channels with false data packets, or target centralized controllers to cripple network control. Defense and security techniques against these threats are constantly evolving, necessitating an up-to-date, comprehensive study analyzing cyber attacks and defense methods for smart grid networks. Previous smart grid security surveys do not contain recent techniques and to our knowledge most, if not all, address only one type of attack type and/or one type of defense. This survey considers the latest security techniques, simultaneous multi-pronged cyber attacks and defensutilityes to meet the challenges of the next-generation SDN smart grid research with the goal of identifying future research needs, describing the open security challenges, and exposing both emerging threats and their potential impact on SD-SG deployment.

The global trend towards increased demand for organic food, greener environments, and the integration of biological control agents into pest management strategies has greatly enhanced the need for biological pesticides (biopesticides). Biopesticides are generally environmentally friendly and are made from micro-organisms or other natural substances. Despite their great potential, relatively few have been registered and commercialised in Nigeria compared to other African countries such as South Africa and Kenya. Biological active agents are so diverse such that ap-plying the same safety standards or environmental conditions to all of them is almost impossible. A review of risk assessment processes and comparative assessments of Nigeria's biopesticide regulations with other developing African countries and developed regions was conducted. Prolonged field testing, lack of bridged risk assessments and technical checklists have been identified as key factors hampering the timely development and commercialisation of biopesti-cides in Nigeria. Recommendations on necessary changes to the existing Nigeria biopesticide regulations have been made. Risk assessment matrices for microbial and biochemical biopesti-cides and a scientific/technical checklist have also been developed. Harmonisation and data ex-change among other countries in the region will also enhance the advancement of scientific and technical knowledge for sustainable regulation and cross-border trade.

The conventional well placement was done manually by using a numerical reservoir simulator, and it required a lengthy trial-and-error process. It required great experience and expertise to manipulate the variables and uncertainties that lie on the reservoir to determine the best placement of the well. In addition, the traditional gradient-based methods such as Line-search and Trust-region were not viable in terms of maximum results obtained. Gradient-based methods were too dependent on the surface gradient of the solution and may only converge to local optima instead of global optima. Complex reservoirs have rough surfaces with high uncertainties, which hinders the traditional gradient-based method from converging to global optima. Thus, genetic algorithms were utilized to automate the manual trial-and-error process and to overcome the limitations of the traditional gradient-based method. The objectives of this study were to analyse the effect of different initial well placement distributions, the number of random solution sizes, and the crossover rate on cumulative oil production. A synthetic reservoir model built using CMG Builder was used as the testing platform for the optimization problems. Well-placement parameterization and optimization set-up were carried out using the CMG CMOST optimization tool. The integration of CMG IMEX and CMOST optimized cumulative oil production based on the objectives of the study. The results obtained showed that the higher number of random solutions used resulted in higher cumulative oil production, with more generations needed to reach the optimum solution. It can be concluded that the larger number of random solutions used increased the probability of reaching the optimum solution, but will take more generations.

The genetic heterogeneity of autism has stymied the search for causes and cures. Whole-genomic studies on large numbers of families have helped identify combinations of inherited and de novo signal. In the present work, we re-analyze DNA microarrays using a novel strategy that takes prior knowledge of genetic relationships into account and that was designed to boost signal important to our understanding of the molecular basis of autism. Our strategy was designed to identify significant genomic variation within a priori defined biological concepts and improves signal detection while lessening the severity of multiple test correction seen in standard analysis of genome-wide association data. Upon application of our approach using 3,244 biological concepts, we detected genomic variation in 68 biological concepts with significant association to autism in comparison to family-based controls. These concepts clustered naturally into a total of 19 classes, principally including cell adhesion, cancer, and immune response. The top-ranking concepts contained high percentages of genes already suspected to play roles in autism or in a related neurological disorder. In addition, many of the sets associated with autism at the DNA level also proved to be predictive of changes in gene expression within a separate population of autistic cases, suggesting that the signature of genomic variation may also be detectable in blood-based transcriptional profiles. This cross-validation with gene expression data from individuals with autism coupled with the enrichment within autism-related neurological disorders supported the possibility that the mutations play important roles in the onset of autism and should be given priority for further study. Our work provides new leads into the genetic underpinnings of autism and highlights the importance of reanalysis of genomic studies of complex disease using prior knowledge of genetic organization.

The goal of germplasm enhancement is to introgress traits from wild crop relatives into cultivated material and eventually cultivars. It seeks to restore genetic diversity that has been lost over time or to augment cultivated material with novel alleles that improve parents in breeding programs. This paper discusses potato germplasm enhancement efforts in the past, focusing on effective examples such as disease resistance and processing quality. In addition, it outlines new strategies for enhancement efforts, shifting the focus from evaluating phenotypes to tracking and manipulating specific DNA sequences. In the genomics era, germplasm enhancement will increasingly be focused on identifying and introgressing alleles rather than traits. Alleles will come from a broad pool of genetic resources that includes wild species relatives of potato, landraces, cultivated potato itself, and distantly related species. Genomics tools will greatly increase the efficiency of introgressing multigenic traits, and will make it possible to identify rare alleles and utilize recessive alleles.

The major global pressures of rapid urbanization and urban growth are compounded by climate impacts resulting in increased vulnerability for urban dwellers, with these vulnerabilities exacerbated during COVID-19. Much of this is concentrated in urban and peri-urban areas where urban development spreads into hazard-prone areas. Often this development is dominated by poor quality homes in informal settlements or slums with poor tenure security. Lessons from a current resilience-building project shows that the fit-for-purpose (FFP) approach to land administration can provide a solution to increase the number of households with security of tenure and improve resilience outcomes as informal settlements grow. This paper discusses the influence of FFP land administration on vulnerabilities to multiple shocks related to climate change and COVID-19. This paper proposes ways the growth of human settlements can be better managed through responsible governance of land tenure rights, and effective land-use planning to improve resilience to different shocks and stresses and provide adequate access to safe land and shelter. Land administration systems can support improved resilience to the multiple stressors of climate and pandemics through improving tenure security and enhancing land use planning controls. Climate change adaptation and risk management need to be better mainstreamed into two major elements of land governance: (i) securing and safeguarding of land rights, and (ii) planning and control of land-use.

Given the broad and intense use of plastic, society is being increasingly affected by its degradation and by-products, particularly by microplastics (MPs) -fragments smaller than 5 mm in size-, and nanoplastics (NPs) -with sizes less than 1 µm. MPs and NPs may enter the body primarily through inhalation, consumption, and skin contact. Once ingested, MPs can penetrate tissues, deviating to other parts of the body, and hence potentially affecting important cellular pathways such as nonconforming chemokine receptors that control the communication between the fetus and the mother. Consequently, the potential health harm induced by MP internalization is a major issue, evidenced by multiple studies demonstrating harmful consequences in diverse animal models and human cells. Here, an overview of the various modes of exposure to MPs and NPs is presented, including inhalation, placental transfer, ingestion, breastmilk consumption, and skin absorption, as well as placental and fetal toxicity due to plastic particles based on animal and in vitro studies. Though MPs in our environment are becoming more recognized, their developmental toxicity is still scarcely known. Besides negatively affecting pregnancy, MPs and NPs have been shown to potentially harm the developing fetus, given their ability to cross the placental barrier. Still, considerable gaps remain in our understanding of the dispersion and toxicity of these particles in the environment, as well as the precise types of NPs and MPs bearing the greatest dangers. As a result, we advocate for larger-scale epidemiological investigations, the development of novel approaches for measuring NP and MP exposures, and the necessity of understanding the toxicity of various kinds of NPs to guide future research efforts.

Hemodialysis (HD) patients experience significant psychological stress related HD. Coping strategies are utilized to help these patients cope with this stress. Prevalence of different types of coping strategies in relation with differential levels of HD-related stress scores and by demographics were assessed. HD patients aged 18 years and above who were seeking regular treatment in a specific HD-unit of a hospital in the upper Midwest, were surveyed between March 2020 and July 2020. Descriptive statistics, correlational analyses, and regression analyses were performed. Females could be expected to have emotional coping scores 8 units greater than males, as B = 8.017 for sex in the model, p =.000. Females could be expected to have coping scores 6.4 points higher than males when adjusted for stress levels, as: B = 6.351, p =.001 for sex in the model. For each 1point increase in Stress Score, the Coping Score could be expected to: increase 6.8 points when adjusted for Sex, where B = 6.751 and p =.000. Increased prevalence of emotional pre-occupation was only observed among female patients which increased with the increase in stress. Psychological interventions in female HD patients should be strongly considered in addressing emotional pre-occupation coping.

Age-related macular degeneration (AMD) is a leading cause of irreversible blindness world-wide. We recently reported that polyethylene glycol (PEG) can activate the alternative pathway of the complement system and induce choroidal neovascularization (CNV) in mice. Currently, no other investigator has demonstrated CNV after PEG injection in the mouse eye. The aim of this article is twofold: we review the histologic changes in mouse retina and retinal pigmented epithelium (RPE) after treatment with PEG, and we summarize a model of wet and dry AMD pathogenesis in mice through subretinal PEG treatment of RPE cells and retinal layers. We injected (subretinal) male C57BL/6 mice with 2 μL of solution containing 0.5 mg and 1.0 mg of PEG or PBS in control groups. Eyes were harvested at day 1, 3 and 5 after injection and processed for analysis. Sections were immunohistochemically stained for complement component C3, mem-brane attack complex (MAC), and cytokeratin 18. Light and laser confocal microscopy was used for image capturing. PEG increased deposition of C3 and MAC on RPE cells and on all retinal layers after 1.0 mg injection. PEG induced loss of cellular contacts between RPE cells and migration of RPE cells in the subretinal space at day 1 after PEG injection. After 0.5 mg PEG injection, increased size of RPE cells was detected at day 3 and 5. Apoptotic bodies were observed in outer nuclear layer at day 3 and 5 after 0.5 mg PEG treatment. RPE cells with dark cytoplasm and condensed chromatin were observed. Higher doses of PEG induce CNV, encouraged RPE cell proliferation and death, and damage photoreceptors in mice. This simple and fast model may be useful to explore the pathogenesis of both dry and wet AMD.

Mid-latitude sporadic-E (Es) is an intermittent phenomenon of the lower E region of the ionosphere. Es clouds are thin, transient, and patchy layers of intense ionization, with ionization densities which can be much higher than in the background ionosphere. Oblique reflection of radio signals in the very high frequency (VHF) range is regularly supported, but the mechanism for it has never been clearly established - specular reflection, scattering, and magnetoionic double refraction have all been suggested. This article proposes using the polarization behaviour of signals reflected from intense midlatitude sporadic-E clouds as an indicator of the true reflection mechanism. Results are presented from a measurement campaign in the summer of 2018, which gathered a large amount of data at a receiving station in the UK using 50 MHz amateur radio beacons as signal sources. In all cases the signals received were elliptically polarized, despite being transmitted with linear polarization; there were also indications that polarization behaviour varied systematically with the orientation of the path to the geomagnetic field. This represents, for all the examples recorded, clear evidence that signals were reflected from midlatitude Es by magnetoionic double refraction.

The primary objective of this study is to report the initial efficacy data observed with the use of cryopreserved human umbilical tissue allograft for the supplementation of cartilage defects in patients with symptomatic knee osteoarthritis. Our primary endpoints were pain, stiffness, and functional recovery scores. In this ongoing study, 55 participants (age 56-93 years) received a single Wharton's jelly tissue allograft application. The study dose consisted of 150mg of Wharton's jelly allograft suspended in approximately 2mL of sterile Sodium Chloride 0.9% solution (normal saline). Each study knee application was performed under ultrasound guidance in a physician's office. The research methodology consisted of NPRS scores and WOMAC subsection scores including pain, stiffness, and physical function. Study enrollment consisted of 55 patients followed for a post-application duration of 90 days. No adverse events or adverse reactions were reported. The results demonstrated statistically significant improvements of NPRS and WOMAC in initial versus 90-day examination. The data represents Wharton's jelly tissue allograft applications are a safe, non-surgical, and efficacious for patients with symptomatic articular cartilage defects associated with osteoarthritis of the knee. 

Modification of Scots pine sapwood (Pinus sylvestris L.) with heterocyclic compounds, imidazole and succinimide, was investigated. Pressure-impregnation with aqueous solutions containing imidazole, imidazole + citric acid, succinimide, succinimide + citric acid, and citric acid + sorbitol (CIOL®) at 5%, 10%, and 15% solid content was followed by oven-curing at 220 °C for 1 hour. Mass changes during treatment steps, bending properties, and anti-swelling efficiency (ASE) were examined. Results indicate that solid concentrations within the range of 5% to 10% were optimal. Results seem to show there are two differing mechanisms in the modification of imidazole and succinimide, respectively. Mass loss due to the heat treatment was highest in imidazole-treated specimens, whereas it remained low and concentration-independent in succinimide-treated specimens. ASE after three cycles reached 31% for imidazole-treated specimens and improved to 38% with the addition of citric acid. For succinimide, ASE increased from 17% to 41%. Bending properties generally showed improvement, except for succinimide + citric acid and CIOL®, which displayed a reduced modulus of rupture. Chemical analyses are warranted to fully understand the reaction mechanisms of the treatments. Imidazole treatment's positive effects are suggested to stem from a thermal reaction between the chemical and wood, indicated by substantial mass loss during leaching and specimen darkening. Succinimide and citric acid might exhibit polymerization with each other and wood components, akin to the CIOL® process. Further research should delve into reaction mechanisms and the impact of imidazole and succinimide on biological durability.

There is a growing interest in the endocannabinoid system and the gut microbiota. Both areas have been suggested to play a role in endometriosis, however this is yet to be studied comprehensively. The purpose of this narrative review is to identify the gaps in endometriosis research in the context of these two areas. It underscores the limited knowledge regarding the involvement of the endocannabinoid system and gut microbiota in endometriosis. Further research in these areas is essential to unlock the therapeutic potential of cannabis and enhance the understanding of endometriosis pathogenesis.

Reduced-order electrothermal models play a key role in the design and control of lithium- ion cell stacks, calling for accurate model parameter calibration. This paper presents a complete electrical and thermal experimental characterization procedure for coupled modeling of cylindrical lithium-ion cells in order to implement them in a prototype Formula SAE hybrid racing car. The main 4goal of the tests is to determine cell capacity variations with temperatures and discharge currents, to predict the open circuit voltage of the cell and its entropic component. A simple approach for the characterization of the battery equivalent electrical circuit and a two-steps thermal characterization method are also shown. The investigations are carried out on four commercial 18650 NMC lithium cells. The model demonstrated to predict the battery voltage at a RMS error lower than 20mV and the temperature to a RMS error equal to 0.5 ◦C. The authors hope that this manuscript can contribute to the development of standardized characterization techniques for such cells, while offering experimental data and validated models that can be used by researchers and BMS designers in different applications.

To prolong the fatigue life of a product handled by machine, parametric accelerated life testing (ALT) is mentioned as an organized technique to pinpoint design flaws and minimize fatigue-connected failures. It requires (1) an ALT procedure, (2) fatigue model, (3) parametric ALTs with adjustment, and (4) an approximate of whether present product complete the BX life. The use of a quantum-transported time-to-failure archetype and a sample size are advised. The improvements in the reliability of a refrigerator ice-maker, comprising an auger motor with bearing, were utilized as a case investigation. In the 1st ALT, a steel rolling bearing cracked due to repeated loads under cold circumstances (below −20 C) in the freezer compartment. The bearing was altered by adjusting the matter from AISI 52100 alloy steel with 1.30-1.60% chromium to lubricated sliding bearing with sintered and hardened steel (FLC 4608-110HT) because of its high fatigue strength at lower temperatures. In the 2nd ALT, a helix made of polycarbonates (PCs) fractured. As an adjustment, a reinforced rib of the helix was thickened. As no troubles in the 3rd ALT occur, the lifetime of an ice-maker was proved to be B1 life 10 years.

Imaging of the ocular vasculature can provide new insights into the pathophysiology of ocular diseases. This study proposes a novel high-frequency super-resolution ultrasound localization microscopy (SRULM) technique and evaluates its ability to measure in vivo perfusion changes in the rat eye at elevated intraocular pressure (IOP). A 38.4 MHz center frequency linear array transducer on a VisualSonics Vevo F2 imaging platform was used to collect high frame rate (1 kHz) radiofrequency data of the posterior rat eye following systemic microbubble contrast injection. Following clutter and spatiotemporal non-local means filtering, individual microbubbles were localized and tracked. The microbubble tracks were accumulated over 10,000 frames to generate vascular images quantifying perfusion velocity and direction. Experiments were performed using physiologic relevant controlled flow states for algorithm validation and subsequently performed in vivo on the rat eye at 10 mm Hg IOP increments from 10 to 60 mm Hg. The posterior vasculature of the rat eye, including the ophthalmic artery, long posterior ciliary arteries and their branches, central retinal artery and retinal arterioles and venules were successfully visualized, and velocities quantified at each IOP level. Significant reductions in arterial flow were measured as IOP was elevated. High-frequency SRULM can be used to visualize and quantify perfusion velocity of the rat eye in both the retrobulbar and intraocular vasculature simultaneously. The ability to detect ocular perfusion changes throughout the depth of the eye may help elucidate the role ischemia has in the pathophysiology of ocular diseases such as glaucoma.

Myocardial deformation imaging (strain imaging) is a technique to directly quantify the extent of myocardial contractility and overcomes several of the limitations of ejection fraction. The application of the most commonly used strain imaging method; speckle-tracking echocardiography to patients with sepsis cardiomyopathy heralds an exciting development to the field. However; the body of evidence and knowledge on the utility, feasibility and prognostic value of left ventricular global longitudinal strain in sepsis cardiomyopathy is still evolving. We conducted a review of literature on utility of left ventricular global longitudinal strain in sepsis cardiomyopathy. We discuss the role of left ventricular global longitudinal strain in mortality prediction, utility and limitations of the technique in the context of sepsis cardiomyopathy.

Crimean-Congo hemorrhagic fever virus is one the most important and wide spread tick-borne viruses. Very little is known about the transmission from the tick and the early aspects of pathogenesis. Here, we generate human cutaneous antigen presenting cells: dermal dendritic cells and Langerhans cells, from umbilical cord progenitor cells. In order to mimic the environment created during tick feeding, tick salivary gland extract was generated from semi-engorged Hyalomma marginatum ticks. Our findings indicate that human dermal dendritic cells and Langerhans cells are susceptible and permissive to Crimean-Congo hemorrhagic fever virus infection, however, to different degrees. Infection leads to cell activation and cytokine/chemokine secretion, although these responses vary between the different cell types. Hyalomma marginatum salivary gland extract had minimal effect on cell responses, with some synergy with viral infection with respect to cytokine secretion. However, salivary gland extract appeared to inhibit antigen presenting cell (APC) migration. Based on the findings here we hypothesize that human dermal dendritic cells and Langerhans cells serve as early target cells. Rather affecting Crimean-Congo hemorrhagic fever virus replication, tick saliva likely immunomodulates and inhibits migration of these APC from the feeding site.

The present work studies a swelling porous-elastic system with viscoelastic damping. We establish a general and optimal decay estimate which generalizes some recent results in the literature. Our result is established without imposing the usual equal-wave-speed condition associated with similar problems in literature.

Historical forest management practices in the southwestern US have left forests prone to high intensity, stand-replacement fires. Effective management to reduce the cost and impact of forest-fire management and allow fires to burn freely without negative impact depends on detailed knowledge of stand composition, in particular, above-ground biomass (AGB). Lidar-based modeling techniques provide opportunities to reduce costs and increase ability of managers to monitor AGB and other forest metrics. Using Bayesian Model Averaging (BMA), we develop a regionally applicable lidar-based statistical model for Ponderosa pine and mixed conifer forest systems of the southwestern USA, using previously collected field data. The selected regional model includes a mid and low canopy height metric, a canopy cover, and height distribution term. It explains 72% of the variability in field estimates of AGB, and the RMSE of the two independent validation data sets are 23.25 and 32.82 Mg/ha. The regional model developed is structured in accordance with previously described models fit to local data, and performs equivalently to models designed for smaller scale application. Developing regional models for broad scale application provides a cost-effective, robust approach for managers to monitor and plan adaptively at the landscape scale.

Inherited retinal dystrophies (IRDs) are a global problem that is largely unaddressed, especially in Africa. Black indigenous Africans are rarely represented in research that develop genetic tests and genetic therapies for IRDs yet their genomes are more diverse. The aim of this literature review is to synthesize information on the IRD genetic research conducted among indigenous black Africans to identify challenges and opportunities for progress. PubMed was searched to identify empirical publications reporting the genetic analysis of IRDs among indigenous Africans. A total of 10 articles were selected for the review. Based on the information in the articles, the main genetic testing methods in use include next-generation, whole exome, and Sanger sequencing. The main IRDs characterized by the genetic tests include retinitis pigmentosa, Leber Congenital Amaurosis, Stagardt disease, and cone dystrophy. Examples of implicated genes include MERTK, GUCY2D, ABCA4, and KCNV2 for the four IRDs respectively. Research activities on the genetics of IRDs are generally scanty in Africa. Even in South Africa and North Africa where some research activities were noted, only a few indigenous black Africans were in the study cohorts. There is an urgent need for genetic research on IRDs, especially in East, Central, and West Africa.

The present state of research in Computational Fluid Dynamics (CFD) is marked by an ongoing process of refining numerical methods and algorithms with the goal of achieving accurate modeling and analysis of fluid flow and heat transfer phenomena. Remarkable progress has been achieved in the domains of turbulence modeling, parallel computing, and mesh generation, resulting in heightened simulation precision when it comes to capturing complex flow behaviors. Nevertheless CFD faces a significant challenge due to the time and expertise needed for meticulous simulation setup and intricate numerical techniques. To surmount this challenge, we introduce paint2sim—an innovative mobile application designed to enable on-the-fly 2D fluid simulations using a device’s camera. Seamlessly integrated with OpenLB, a high-performance Lattice Boltzmann-based library, paint2sim offers accurate simulations. The application leverages the capabilities of the Lattice Boltzmann Method (LBM) to model fluid behaviors accurately. Through a symbiotic interaction with the open-source OpenCV library, paint2sim can scan and extract hand-drawn simulation domains, affording the capability for instant simulation and visualization. Notably, paint2sim can also be regarded as a digital twin, facilitating just-in-time representation and analysis of 2D fluid systems. The implications of this technology extend significantly to both fluid dynamics education and industrial applications, effectively lowering barriers and rendering fluid simulations more accessible. Encouragingly, the outcomes of simulations conducted with paint2sim showcase promising qualitative and quantitative results. Overall, paint2sim offers a groundbreaking approach to mobile 2D fluid simulations, providing users with just-in-time visualization and accurate results, while simultaneously serving as a digital twin for fluid systems.

Emerging research has revealed a complex bidirectional interaction between the gut microbiome and cannabis. Preclinical studies have demonstrated that the gut microbiota can significantly influence the pharmacological effects of cannabinoids. One notable finding is the ability of the gut microbiota to metabolise cannabinoids, including Δ^9-tetrahydrocannabinol (THC). This metabolic transformation can alter the potency and duration of cannabinoid effects, potentially impacting their efficacy in cancer treatment. Additionally, the capacity of gut microbiota to activate cannabinoid receptors through the production of secondary bile acids underscores its role in directly influencing the pharmacological activity of cannabinoids. While the literature reveals promising avenues for leveraging the gut microbiome-cannabis axis in cancer therapy, several critical considerations must be accounted for. Firstly, the variability in gut microbiota composition among individuals presents a challenge in developing universal treatment strategies. The diversity in gut microbiota may lead to variations in cannabinoid metabolism and treatment responses, emphasising the need for personalised medicine approaches. The growing interest in understanding how the gut microbiome and cannabis may impact cancer has created a demand for up-to-date, comprehensive reviews to inform researchers and healthcare practitioners. This review provides a timely and invaluable resource by synthesizing the most recent research findings and spotlighting emerging trends. A thorough examination of the literature on the interplay between the gut microbiome and cannabis, specifically focusing on their potential implications for cancer, is presented in this review to devise innovative and effective therapeutic strategies for managing cancer.

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.

Pure-compression shells have been the central topic in the form-finding of shells. This paper studies tension-compression mixed type shells by utilizing a NURBS-based isogeometric form-finding approach that analyzes Airy stress functions to expand the possible plan geometry. A complete set of smooth version graphic statics tools is provided to support the analyses. The method is validated using examples with known solutions, and a further example demonstrates the possible forms of shells that the proposed method permits. Additionally, a guideline to configure a proper set of boundary conditions is presented through the lens of asymptotic lines of the stress functions.

This paper presents a finite element analysis of the bi-directional orthogonal model, which incorporates individual crack strain separation and tracking. The objective of the research is to expand the current shear friction model to manage bi-directional cracking at any angle, allowing for a more universal model that can be applied to intricate structures and non-proportional loading cases. The proposed model was initially developed as a total strain-based model, with the assumption that crack strains are equivalent to total strains, but was subsequently recalculated to improve accuracy by separating crack strains from total strains. Furthermore, a separate crack strain formulation was created to account for strains in the concrete's uncracked portions and locked-in crack strains. The article then discusses the testing of various convergence methods and loading programs to achieve high convergence. Comparative analyses of the generalized shear friction model with other models for crack orientation and loading cases similar to those of a reinforced concrete membrane are also presented. The MATLAB program successfully applied the bi-directional cracking model for one finite element under a uniform cyclical strain state, using a secant stiffness formulation.

Wheat (Triticum aestivum L.) breeding programs can take over a decade to release a new variety. However, new methods of selection such as genomic selection (GS) must be integrated to decrease the time it takes to release new varieties to meet the demand of a growing population. The implementation of GS into breeding programs is still being explored, with many studies showing its potential to change wheat breeding through achieving higher genetic gain. In this review, we explore the integration of GS for a wheat breeding program by redesigning the traditional breeding pipeline to implement GS. We propose implementing a two-part breeding strategy by differentiating between population improvement and product development. The implementation of GS in the product development pipeline can be integrated into most stages and can predict within and across breeding cycles. Additionally, we explore optimizing the population improvement strategy through GS recurrent selection schemes to reduce crossing cycle time and significantly increase genetic gain. The recurrent selection schemes can be optimized for parental selection, maintenance of genetic variation, and optimal cross-prediction. Overall, we outline the ability to increase the genetic gain of a breeding program by implementing GS and a two-part breeding strategy.

In the present work, we investigate the possibility that long-range airborne transport of infectious aerosols could initiate an epidemic outbreak at distances downwind beyond one hundred kilometers. For this, we have developed a simple atmospheric transport box-model which, for a hypothetical case of a COVID-19 outbreak, was compared to a more sophisticated 3-dimensional transport-dispersion model (HYSPLIT) calculation. Coupled with an extended Wells-Riley description of infection airborne spread, it shows that, the very low probability of outdoor transmission can be compensated by high numbers and densities, such as occurs in large cities, of infected and susceptible people in the source upwind and in the target downwind respectively. This may result in the creation of a few primary cases. It is worth pointing out that the probability of being infected remains very small at the individual level. Therefore, this process alone, which depends on population sizes, geography, seasonality and meteorology, can only “trigger” an epidemic which could then spread by the standard infection routes

Precision medicine seeks to use genomic data to help provide the right treatment to the right patient at the right time. Next-generation sequencing technology allows for the rapid and accurate sequencing of many genes at once. This technology is becoming more common in oncology, though the clinical benefit of incorporating it into precision medicine strategies remains under significant debate. In this manuscript, we discuss the early findings of the impact of next-generation sequencing on cancer patient outcomes. We investigate why not all patients with genomic variants linked to a specific therapy receive that therapy and describe current barriers. Finally, we explore the current state of health insurance coverage for individual genome sequencing and targeted therapies for cancer. Based on our analysis, we recommend increased transparency around the determination of “actionable mutations” and a heightened focus on investigating the variations in health insurance coverage across patients receiving sequencing-matched therapies.

A multiscale mathematical model is proposed seeking to study the propagation dynamics of the Human Immunodeficiency Virus (HIV) in a group of young people between 15 and 24 years of age, through sexual contact without protection, considering the use of antiretroviral therapy (ART) and therapeutic failure. The model consists in a scale-free complex network that follows a power law, coupled with the immunological dynamics of each individual, that is, it considers the infection by the virus in the immune system of each HIV carrier, through a system of non-linear differential equations that govern the infection’s behavior in the immune system. Propagation of the virus in the network is modelled by taking into account information from the immunological status of each person. The study found that for a population to have high HIV prevalence, it is not necessary at the beginning of the simulation time for the virus to propagate rapidly. In addition, the study proves that with a higher number of sexual partners, there will be greater prevalence of HIV in the population and that the use of ART helps to control the propagation of the infection in the population. As an interesting result, it was also found that there is a higher number of HIV carriers who abandon ART than those who have access to it.

Leader-follower autonomy (LFA) systems have so far only focused on vehicles following other vehicles. Though there have been several decades of research into this topic, there has not yet been any work on human-vehicle leader-follower systems. We present a system in which an autonomous vehicle — our ACTor 1 platform — can follow a human leader who controls the vehicle through gestures. We successfully developed a modular pipeline that uses artificial intelligence/deep learning to recognize hand-and-body gestures from a user in view of the vehicle’s camera and translate those gestures into physical action by the vehicle. We demonstrate our work using our ACTor 1 platform, a modified Polaris Gem 2 electric vehicle. This work has numerous applications, such as material transport in industrial contexts.

We report a photonic-based radio frequency (RF) arbitrary waveform generator (AWG) using a soliton crystal micro-comb source with a free spectral range (FSR) of 48.9 GHz. The comb source provides over 80 wavelengths, or channels, that we use to successfully achieve arbitrary waveform shapes including square waveforms with a tunable duty ratio ranging from 10% to 90%, sawtooth waveforms with a tunable slope ratio of 0.2 to 1, and a symmetric concave quadratic chirp waveform with an instantaneous frequency of sub GHz. We achieve good agreement between theory and experiment, validating the effectiveness of this approach towards realizing high-performance, broad bandwidth, nearly user-defined RF waveform generation.

We report a broadband radio frequency (RF) channelizer with up to 92 channels using a coherent microcomb source. A soliton crystal microcomb, generated by a 49 GHz micro-ring resonator (MRR), is used as a multi-wavelength source. Due to its ultra-low comb spacing, up to 92 wavelengths are available in the C band, yielding a broad operation bandwidth. Another high-Q MRR is employed as a passive optical periodic filter to slice the RF spectrum with a high resolution of 121.4 MHz. We experimentally achieve an instantaneous RF operation bandwidth of 8.08 GHz and verify RF channelization up to 17.55 GHz via thermal tuning. Our approach is a significant step towards the monolithically integrated photonic RF receivers with reduced complexity, size, and unprecedented performance, which is important for wide RF applications ranging from broadband analog signal processing to digital-compatible signal detection.

The study presents a novel approach of programing pain inhibition in chronic pain patients based on the hypothesis that pain perception is modulated by dysfunctional dorsal medial nucleus tractus solitarii (dmNTS) reflex arcs that produce diminished baroreflex sensitivity (BRS) resulting from a conditioned response. This study tested whether administration of noxious and non-noxious electrical stimuli synchronized with the cardiac cycle resets BRS, reestablishing pain inhibition. 30 pain-free normotensives controls (NC) and 32 normotensives fibromyalgia (FM) patients received two, ≈8 minute-epochs of cardiac-gated, peripheral electrical stimuli. Non-painful and painful electrical stimuli were synchronized to the cardiac cycle as the neuromodulation experimental protocol (EP) with 2 control conditions (CC1, CC2). BRS, heart-rate-variability (HRV), pain threshold and tolerance, and clinical pain intensity were assessed.Reduced BRS in FM at baseline increased by 41% during two, ≈8 minute-epochs of stimulation. Thresholds in FM increased significantly during the experimental protocol (all Ps<0.001) as did HRV. FM levels of clinical pain significantly decreased by 35.52% during the experimental protocol but not during control stimulations (P<0.001). Baroreceptor training may reduce FM pain by BRS-mediated effects on intrinsic pain regulatory systems and autonomic pain modulation. These processes seem to be linked by classical and operant conditioning.

An ion exchange dialysis (IED) is used in the recovery of aluminium from residue. In this papers, the face-centered central composite design (FC-CCD) of the response surface methodology (RSM) and desirability approach is used for experimental design, modelling and process optimization of a counter flow IED system. The feed concentration, feed flowrate, sweep flowrate and sweep concentration are selected as the process variables, with the Al-transport across a Nafion 117 membrane as the target response. A total of 30 experimental runs were conducted with 6 center points. The response obtained was analysed by analysis of variance (ANOVA) and fitted to a second-order polynomial model using multiple regression analysis. The actual R2 and standard deviation of the model are 0.9548 and 0.2932 respectively. The influences of significant variables are plotted on 3D surface and contour plots. The designed variables were numerically optimized by applying the desirability function to achieve the maximum Al-transport. The optimised condition values were found to be feed concentration (1600 ppm), feed flowrate (61.76%), sweep flowrate (37.50%) and sweep concentration (0.75 N) for the 80% target response at 32hrs. Overall, the model can be used to effectively predict Al-recovery using the designed system

Nanofluids are a novel class of heat transfer fluid that plays a vital role in industries. In mathematical investigations, these fluids are modeled in terms of traditional integer-order partial differential equations (PDEs). It is recognized that traditional PDEs cannot decode the complex behavior of physical flow parameters and memory effects. Therefore, this article intends to study the mixed convection heat transfer in nanofluid over an inclined vertical plate via fractional derivatives approach. The problem in hand is modeled in connection with Atangana-Baleanu fractional derivatives without singular and local kernel having strong memory. The human blood is considered as base fluid dispersing carbon nanotube (CNTs) (single-wall carbon nanotubes (SWCNTs) and multi-wall carbon nanotubes(MWCNTs )) into it to form blood-CNTs nanofluid. The nanofluids are considered to flow in a saturated porous medium under the influence of an applied magnetic field. The exact analytical expressions for velocity and temperature profiles are acquired using the Laplace transform technique and plotted in various graphs. The empirical results indicate that the memory effect decreases with increasing fractional parameters in the case of both temperature and velocity profiles. Moreover, the temperature profile is higher for blood-SWCNTs by reason of higher thermal conductivity whereas, this trend is opposite in case of velocity profile due densities difference.

Androgenetic alopecia, the most common cause of hair loss affecting both men and women, is typically treated using pharmaceutical options such as minoxidil and finasteride. While these medications work for many individuals, they are not suitable options for all. To date, the only non-pharmaceutical option that the United States Food and Drug Administration has cleared as a treatment for androgenetic alopecia is low-level laser therapy (LLLT). Various clinical trials utilizing LLLT devices of various types are available. However, a myriad of other physical treatments for this form of hair loss are reported in the literature. This review evaluated the effectiveness of microneedling, pulsed-electromagnetic field (PEMF) therapy, low-level laser therapy (LLLT), fractional laser therapy, and non-ablative laser therapy for the treatment of androgenetic alopecia (AGA). It also explores the potential of multimodal treatments combining these physical therapies. LLLT has the majority of evidence in the literature as a physical therapy for androgenetic alopecia. However, other physical treatments, such as non-ablative laser treatments, and multimodal approaches, such as PEMF-LLLT, seem to have the potential to be equally or more promising and merit further exploration.

Drug nanosuspensions offer a promising approach to improve bioavailability for poorly soluble drug candidates. Such formulations often necessitate the inclusion of an excipient to stabilize the drug nanoparticles. However, a rationale to choose the correct excipient for a given drug candidate remains unclear. To gain molecular insight into formulation design, this work first utilizes molecular dynamics simulation to computationally investigate drug-excipient interactions for a number of combinations that have been previously studied experimentally. We find that hydrophobic interactions drive excipient adsorption to drug nanoparticles, and that the fraction of polar surface area serves as a predictor for experimental measurements of nanosuspension stability. To test these ideas prospectively, we applied our model to an uncharacterized drug compound, GDC-0810. Our simulations predicted that salt forms of GDC-0810 would lead to more stable nanosuspensions than the neutral form; therefore, we tested the stability of salt GDC-0810 nanosuspensions and found that the salt form readily formed nanosuspensions even without excipient. To avoid computationally expensive simulations in the future, we extended our model by showing that simple, two-dimensional properties of the single drug molecule can be used to rationalize nanosuspension design without simulation. In all, our work demonstrates how computational tools can provide molecular insight into drug-excipient interactions, and aid in rational formulation design.

Neural-objective and image optimization approaches for drilling fluid rheology automation are crucial for drilling engineering optimization. A myriad of intelligent computational models are employed to predict and monitor the parameters of mud rheology and filter cake permeability posture using an artificial neural network feedforward (ANN-FF) function, a non-ANN-FF function, an image processing tool, and a model optimization tool. 498 datasets of synthetic-based mud (SBM) flat rheology from a drilling mud laboratory at Nazarbayev University were imported into a user-friendly MATLAB application using image processing and nftool. Apart from the Google TensorFlow Sequential API DNN architecture used, a Levenberg-Marquardt training algorithm with input sigmoid hidden neurons 10, 12, and 18 coupled with a linear output layer was also used to predict the SBM flow index. OBM and SBM filter cakes were processed for void spaces; however, a model study was extrapolated to maximize filtration volume Vf. The study’s findings show that the ANN-FF model employed for rheological property monitoring and prediction had higher steady and exponential levels of accuracy and a correlation coefficient of 0.96-0.99. More so, SBM and OBM image processing presented an area of void spaces of 1790M2 and 1739M2, respectively. The porosity and permeability postures of both SBM and OBM resulted in a significant void space capable of maximizing the flow index. In addition, the single-objective modelling based on a genetic algorithm did validate the experimental rheological data for flow index or filtration volume Vf optimization; the study resulted in the finding that the constrained physics-informed objective function hindered maximizing oil recovery and instead predicted possible formation damage. It is empirical to note that automating flow predictions with neural, objective, and image functions has presented an alternative novel method for non-programmers using MATLAB and Google Colabs that is capable of enhancing mud rheological parameters, drilling efficiency, and hydrocarbon recovery.

The study analyzed Ecuador's presence in the Web of Science (WoS) post-pandemic from a multivariate dynamic, highlighting a significant transformation in scientific communication towards open access (OA). The methodology integrated multivariate statistical techniques, using R and specialized tools, to process 9,085 relevant articles, 52% of the Ecuadorian publications in WoS between 2019 and 2021 were open access. This movement reflects a commitment to quality research and accessibility, showing an increase in publications and citations under OA. The research underscores the importance of establishing robust national OA policies in Ecuador to promote scientific collaboration and an equitable distribution of knowledge. Despite funding challenges and the lack of specific regulations, educational institutions in Ecuador have maintained a constant scientific output, adapting to the global environment and the demand for transparent information. The study concludes that there is an urgent need for a holistic approach to OA in the country, recognizing the progress made despite the difficulties.

Micro-combs [1-4] - optical frequency combs generated by integrated micro-cavity resonators – offer the full potential of their bulk counterparts [5,6], but in an integrated footprint. The discovery of temporal soliton states (DKS – dissipative Kerr solitons) [4,7-11] as a means of mode-locking micro-combs has enabled breakthroughs in many fields including spectroscopy [12,13], microwave photonics [14], frequency synthesis [15], optical ranging [16,17], quantum sources [18,19], metrology [20,21] and more. One of their most promising applications has been optical fibre communications where they have enabled massively parallel ultrahigh capacity multiplexed data transmission [22,23]. Here, by using a new and powerful class of micro-comb called “soliton crystals” [11], we achieve unprecedented data transmission over standard optical fibre using a single integrated chip source. We demonstrate a line rate of 44.2 Terabits per second (Tb/s) using the telecommunications C-band at 1550nm with a spectral efficiency – a critically important performance metric - of 10.4 bits/s/Hz. Soliton crystals exhibit robust and stable generation and operation as well as a high intrinsic efficiency that, together with a low soliton micro-comb spacing of 48.9 GHz enable the use of a very high coherent data modulation format of 64 QAM (quadrature amplitude modulated). We demonstrate error free transmission over 75 km of standard optical fibre in the laboratory as well as in a field trial over an installed metropolitan optical fibre network. These experiments were greatly aided by the ability of the soliton crystals to operate without stabilization or feedback control. This work demonstrates the capability of optical soliton crystal micro-combs to perform in demanding and practical optical communications networks.

We demonstrate a photonic RF integrator based on an integrated soliton crystal micro-comb source. By multicasting and progressively delaying the input RF signal using a transversal structure, the input RF signal is integrated discretely. Up to 81 wavelengths are provided by the microcomb source, which enable a large integration time window of ~6.8 ns, together with a time resolution as fast as ~84 ps. We perform signal integration of a diverse range of input RF signals including Gaussian pulses with varying time widths, dual pulses with varying time intervals and a square waveform. The experimental results show good agreement with theory. These results verify our microcomb-based integrator as a competitive approach for RF signal integration with high performance and potentially lower cost and footprint.

Personality changes have been reported to occur following organ transplantation, and most commonly among heart transplant recipients. We set out to examine whether personality changes do occur following transplantation, and specifically, what types of changes occur among heart transplant recipients compared to other organ recipients. A cross-sectional study was conducted in 2022, in which 47 participants (23 heart recipients and 24 other organ recipients) completed an online survey. In this study, 89% of all transplant recipients reported experiencing personality changes after receiving their organ transplant, which was similar for heart and other organ recipients. With the exception of physical attributes, the types of personality changes reported were similar between the two groups. These finding indicate that heart transplant recipients are not unique in their reported experience of personality changes following organ transplantation. Further studies are needed to deepen our understanding of what causes these personality changes following organ transplantation.

Objective: To investigate the feasibility and preliminary effects of a 12-week home-based moderate intensity cycling programme in stroke survivors. Design: Single-blinded, parallel group, Randomised Controlled Trial Setting: Home-based Participants: Participants will be survivors of first-ever stroke and randomly assigned to an Active Cycling Group (ACG) or control group. Intervention: The ACG performed a 12-week home-based cycling programme, three sessions per week. Work intervals were executed at 75% of the maximal heart rate (HR_max), recovery intervals at 50% of HR_max. Work interval duration increased from three ten-minute intervals to 30 minutes continuous cycling. The control group completed a 12-week neurocognitive exercise programme. Main outcome measurements: Primary outcome measures are compliance with training, adherence to protocol and safety as measured by adverse events. Secondary outcome measurements included a: simplified modified Rankin Scale questionnaire (stroke severity), Six-Minute Walking Test (walking ability), Ten-meter Walk Test (walking ability), Rivermead Mobility Index (walking ability), graded submaximal cycling test (exercise capacity), Physical Activity for Individuals with Physical Disability questionnaire (physical activity), EQ-5D-5L (quality of life), Stroke Specific Quality of Life questionnaire (quality of life), Montreal Cognitive Assessment (cognition), General Self-Efficacy Scale (self-efficacy), and Exercise Self-Regulation Questionnaire (self-regulation).

The generation of forensic DNA profiles consisting of single nucleotide polymorphisms (SNPs) is now being facilitated by wider adoption of next-generation sequencing (NGS) methods in casework laboratories. At the same time, and in part because of this advance, there is an intense focus on the generation of SNP profiles from evidentiary specimens for so-called forensic or investigative genetic genealogy (FGG or IGG) applications. However, FGG methods are constrained by the algorithms for genealogical database searches, which were designed for use with single-source profiles, and the fact that many forensic samples are mixtures. To enable the use of two-person mixtures for FGG, we developed a workflow, MixDeR, for the deconvolution of mixed SNP profiles. MixDeR, a flexible and easy to use R package and Shiny app, processes ForenSeq Kintelligence® (QIAGEN, Inc.) SNP genotyping results and directs deconvolution of the profiles in EuroForMix (EFM). MixDeR then filters the EFM outputs to produce inferred single-source genotypes in reports formatted for use with GEDmatch® PRO. An optional MixDeR output includes metrics that assist with testing and validation of the workflow. As the Shiny app provides a graphical user interface and the software is designed to be run offline, MixDeR should be suitable for use by any laboratory developing FGG capabilities, no matter their bioinformatic resources or expertise.

Non-tuberculous mycobacteria (NTM) are opportunistic pathogens that cause illness primarily in the elderly, in the immunocompromised or in patients with underlying lung disease. Mycobacterium chimaera is a NTM species belonging to the M. avium Complex (MAC) group of species. Since 2013, a global outbreak of M. chimaera infection related to heater-cooler units (HCU) used in cardio-thoracic surgery has been identified. This outbreak was caused by a single strain of M. chimaera. In order to estimate the prevalence of this outbreak strain in Israel, we sampled M. chimaera from several HCU machines in Israel, as well as from patients, sequenced their genomes and compared them to the outbreak strain. The presence of mixed mycobacteria species in the samples complicated the analysis of obtained sequences. By applying a metagenomic binning strategy, we were able to obtain genomes of single strains from the mixed samples, and characterized them. M. chimaera strains were compared to each other and to previously reported genomes from other countries. The strain causing the outbreak related to the HCU machines was identified in several such machines in Israel but not in any of the clinical samples.

Linear elastic fracture modeling coupled with empirical material tension data result in good quantitative agreement with experimental measurements of fracture failure for both brittle and tough epoxy nanocomposites. The nanocomposites comprise diglycidyl ethers of bisphenol A cured with O,O’ bis (2-aminopropylpropylene glycol) (Jeffamine D230) and doped with rubber nanoparticles of varying concentrations. Toughness, critical load, and critical displacement in quasi-static single edge-notched three-point bending are predicted accurately using both surface-based cohesive zone (CZS) and extended finite element (XFEM) methods implemented in Abaqus software. Fracture initiation within a crack is taken at the yield stress from uniaxial tension data. Prediction of fracture processes using a generalized truncated linear traction-separation law was significantly improved by considering the case of a linear softening function. There are no adjustable parameters in the XFEM model. The CZS model requires only optimization of the element displacement at fracture parameter. Thus, these continuum methods describe these materials in mode I fracture with a minimum number of independent parameters.

The increasing complexity of the design and operation evaluation process of multi-energy grids (MEGs) requires tools for the coupled simulation of power, gas and district heating grids. Most tools analyzed in this paper either do not allow coupling of infrastructures, simplify the grid model or are not publicly available. We introduce the open source piping grid simulation tool pandapipes that – in interaction with pandapower - fulfills three crucial criteria: clear data structure, adaptable MEG model setup and performance. In an introduction to pandapipes we illustrate how it fulfills these criteria through its internal structure and demonstrate how it performs in comparison to STANET®. Then we show two case studies that have been performed with pandapipes already. The first case study demonstrates a peak shaving strategy as interaction of a local electricity and district heating grid in a small settlement. The second case study analyzes the potential of a power-to-gas device to serve as flexibility in a power grid under consideration of gas grid constraints. They both show the importance of a clear database, a simple simulation setup and good performance to set up different large and complex studies on grid infrastructure design and operation.

Many estuarine ecosystems and the fish communities that inhabit them have undergone substantial changes in the past several decades, largely due to multiple interacting stressors that are often of anthropogenic origin. Few are more impactful than droughts, which are predicted to increase in both frequency and severity with climate change. In this study, we examined over five decades of fish monitoring data from the San Francisco Estuary, California, U.S.A, to evaluate the resistance and resilience of fish communities to disturbance from prolonged drought events. High resistance was defined by the lack of decline in species occurrence from a wet to a subsequent drought period, while high resilience was defined by the increase in species occurrence from a drought to a subsequent wet period. We found some unifying themes connecting the multiple drought events over the fifty-year period. Pelagic fishes consistently declined during droughts (low resistance), but exhibit a considerable amount of resiliency and often rebound in the subsequent wet years. However, full recovery does not occur in all wet years following droughts, leading to permanently lower baseline numbers for some pelagic fishes over time. In contrast, littoral fishes seem to be more resistant to drought and may even increase in occurrence during dry years. Based on the consistent detrimental effects of drought on pelagic fishes within the San Francisco Estuary and the inability of these fish populations to recover in some years, we conclude that freshwater flow remains a crucial but not sufficient management tool for the conservation of estuarine biodiversity.

Syndemics theory has been applied to study interactions between biomedical and social factors leading to clustering of diseases. Because syndemics theory focuses on interactions that enhance risk, the concept of vulnerability is central to this approach. We conducted a scoping review to better understand how syndemics theory helped to define, operationalize, and tackle issues of vulnerability during the COVID-19 pandemic. Original research, review, and opinion pieces elaborating on syndemics, vulnerability and COVID-19, published between December 2019 and October 2022 and available in PubMed, were eligible. We analysed 40 records and identified three framings of syndemics operating during this period: (1) interactions between COVID-19, diseases/health conditions and specific social factors; (2) interactions between COVID-19 and social determinants of health; and (3) impacts of COVID-19 on specific populations. Emerging conceptualizations described vulnerability to COVID-19 as a systemic issue; explained the impact of COVID-19 control measures on increased vulnerability; and presented COVID-19 as a syndemic on its own. However, this theory's potential for deepening our understanding of vulnerability during this pandemic was constrained by superficial explorations of the interactions between biomedical and social spheres, and insufficient theoretical and methodological support from the social sciences.

The ability to predict physical characteristics from DNA presents significant opportunities for forensic science. Giving scientists an ability to make predictions about the donor of genetic material at a crime scene can then give investigators new intelligence leads for cold cases where DNA evidence has not identified any person of interest. However, the interpretation of this new form of intelligence requires careful analysis. The responses to an online survey, conducted in 2018-19, were used to examine how actors in the criminal justice system assess and interpret different types of DNA evidence and intelligence. The groups of focus for the survey were investigators, legal practitioners and the general public (as potential jurors). Several statistically significant effects were identified based on occupation and whether an individual had prior exposure to new DNA technology. Monitoring how those involved in interpreting reports from different types of DNA evidence and intelligence interpret them helps to ensure that decisions are made based on a sound understanding of their capabilities and limitations and may inform broader training and awareness strategies.

Differentiation of induced pluripotent stem cells to a range of useful, mature target cell types is ubiquitous in monolayer culture. To further improve the phenotype of the cells produced, 3D organoid culture is becoming increasingly prevalent. Mature organoids typically require the involvement of cells from multiple germ layers. The aim of this study was to produce pulmonary organoids from defined endodermal and mesodermal progenitors. Endodermal and mesodermal progenitors were differentiated from iPSCs then combined in 3D Matrigel hydrogels and differentiated for a further 14 days to produce pulmonary organoids. The organoids expressed a range of pulmonary cell markers such as SPA, SPB, SPC, AQP5 and T1α. Furthermore, organoids expressed ACE2 capable of binding SARS-Cov2 spike protein demonstrating the physiological relevance of the organoids produced. This study demonstrates the rapid production of pulmonary organoids using a multi-germ layer approach that could be used for studying novel respiratory disease interactions.

Background: Poor patient flow can lead to adverse outcomes for patients and organisational inefficiency. Many hospitals have addressed suboptimal patient flow by increasing resourcing, such as bed stock and staffing, however, this is an unsustainable approach. In determining the nature of poor patient flow issues, it is important to collect data from healthcare professionals who manage patient flow on a daily basis. Doing so provides insights into the current state of patient flow management in its entirety, whilst also helping with the development of sustainable solutions.; Methods: Thirteen semi-structured interviews were conducted with clinicians who were directly involved with patient flow at a tertiary care centre in Tasmania, Australia. Results: Through a thematic analysis method, four major themes were developed: managing patient flow, communication for decisions, tools as enablers and barriers and increasing complexity. Conclusions: The findings of this study provide great insights into patient flow issues, with potential solutions identified to address them.

Biomarkers have the potential to aid in the study of Alzheimer’s disease (AD); unfortunately, AD biomarker values often have a high degree of overlap between healthy and AD individuals. This study investigates the potential utility of a series of novel AD biomarkers, the sixty second ¹²⁹Xe retention time, and the xenon washout parameter, based on the washout of hyperpolarized ¹²⁹Xe from the brain of AD participants following inhalation. The xenon washout parameter is influenced by cerebral perfusion, T1 relaxation of xenon, and the xenon partition coefficient, all factors influenced by AD. Participants with Alzheimer’s disease (n=4) and healthy volunteers (n=4) were imaged using hyperpolarized ¹²⁹Xe magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) to determine the amount of retain xenon in the brain. At 60 sec post breath hold, AD patients retained significantly higher amounts of ¹²⁹Xe compared to healthy controls. Data was fit to a pharmacokinetic model and the xenon washout parameter was extracted. Xenon washout in white and grey matter occurs at a slower rate in Alzheimer’s participants (¹²⁹Xe half-life time of 42s and 43s, respectively) relative to controls (20s and 16s, respectively). Following larger scale clinical trials for validation, the xenon washout parameter has the potential to become a useful biomarker for the support of an AD diagnosis.

Marine water pH is becoming progressively reduced in response to atmospheric CO2 elevation. Considering that marine environments support a vast global biodiversity and provide a variety of ecosystem functions and services, monitoring of the coastal and intertidal water pH assumes obvious significance. Because current monitoring approaches using meters and loggers are typically limited in application in heterogeneous environments and are financially prohibitive, we sought to evaluate an approach to acidification biomonitoring using living gastropod shells. We investigated snail populations exposed naturally to corrosive water in Brunei (Borneo, South East Asia). We show that surface erosion features of shells are generally more sensitive to acidic water exposure than other attributes (shell mass) in a study of rocky-shore snail populations (Nerita chamaeleon) exposed to greater or lesser coastal geochemical acidification (acid sulphate soil seepage, ASS), by virtue of their spatial separation. We develop a novel digital approach to measuring the surface area of shell erosion. Surficial shell erosion of a muddy-sediment estuarine snail, Umbonium vestiarium, is shown to capture variation in acidic water exposure for the timeframe of a decade. Shell dissolution in Neripteron violaceum from an extremely acidic estuarine habitat, directly influenced by ASS inflows, was high variable among individuals. In conclusion, gastropod shell dissolution potentially provides a powerful and cost-effective tool for rapidly assessing marine pH change across a range of spatial and temporal frameworks and coastal intertidal environments. We discuss caveats when interpreting gastropod shell dissolution patterns.

Cannabis, renowned for its historical medicinal use, harbours various bioactive compounds—cannabinoids, terpenes, and flavonoids. While major cannabinoids like THC and CBD have received extensive scrutiny for their pharmacological properties, emerging evidence underscores the collaborative interactions among these constituents, suggesting a collective therapeutic potential. This comprehensive review explores the intricate relationships and synergies between cannabinoids, terpenes, and flavonoids in cannabis. Cannabinoids, pivotal in cannabis's bioactivity, exhibit well-documented analgesic, anti-inflammatory, and neuroprotective effects. Terpenes, aromatic compounds imbuing distinct flavours, not only contribute to cannabis's sensory profile but also modulate cannabinoid effects through diverse molecular mechanisms. Flavonoids, another cannabis component, demonstrate anti-inflammatory, antioxidant, and neuroprotective properties, particularly relevant to neuroinflammation. The entourage hypothesis posits that combined cannabinoid, terpene, and flavonoid action yields synergistic or additive effects, surpassing individual compound efficacy. Recognizing the nuanced interactions is crucial for unravelling cannabis's complete therapeutic potential. Tailoring treatments based on the holistic composition of cannabis strains allows optimization of therapeutic outcomes while minimizing potential side effects. This review underscores the imperative to delve into the intricate roles of cannabinoids, terpenes, and flavonoids, offering promising prospects for innovative therapeutic interventions and advocating continued research to unlock cannabis's full therapeutic potential within the realm of natural plant-based medicine.

Entheseal spinal inflammation and new bone formation with progressive ankylosis may occur in ankylosing spondylitis (AS) and psoriatic arthritis (PsA). This study evaluated whether JAK inhibition with tofacitinib modulated the key disease associated cytokines, TNF and IL-17A and whether tofacitinib also modulated bone marrow stromal cell-derived mesenchymal stem cells (MSCs) function including osteogenesis, since post inflammation new bone formation occurs in these conditions. Methods: Conventional entheseal derived αβ CD4+ and CD8+ T-cells were in-vestigated following anti-CD3/CD28 bead stimulation to determine IL-17A and TNF levels in Tofacitinib treated (1000nM) peri-entheseal bone (PEB) and peripheral blood mononuclear cells (PBMC) following ELISA. Bone marrow stromal cell-derived mesenchymal stem cells (MSCs) colony forming unit (CFU-F) and multilineage potential was evaluated using tofacitinib (dosag-es ranging between 100, 500, 1000 and 10000nM). Results: Induced IL-17A and TNF cytokine production from both entheseal CD4+ T-cells and CD8+ T-cells were effectively inhibited by to-facitinib. Tofacitinib treatment did not impact on CFU-F potential or in vitro chondro- and oste-ogenesis. However, tofacitinib stimulation increased MSC adipogenic potential with greater Oil Red O stained area. Conclusion: Inducible IL-17A and TNF production by healthy human enthe-seal CD4+ and CD8+ T-cells was robustly inhibited in vitro by tofacitinib. However, tofacitinib did not impact on MSC osteogenesis but stimulated in vitro MSC adipogenesis, the rele-vance of which needs further evaluation given the adipocytes are associated with new bone formation in SpA.

Hispanics are disproportionately affected by low rates of physical activity and high rates of chronic diseases. Hispanics generally and Mexican Americans specifically are underrepresented in research on physical activity and its impact on mental well-being. Some community-based interventions have been effective in increasing physical activity among Hispanics. This study examined data from a sample of low-income Hispanic participants in free community exercise classes to characterize the association between self-reported frequency of exercise class attendance, intensity of physical activity, and participant well-being. As part of two cross-sectional samples recruited from a stratified random sample of community exercise classes, 302 participants completed a questionnaire consisting of a modified version of the Godin-Shephard Leisure-Time Exercise Questionnaire (LTEQ) and the Mental Health Continuum Short Form (MHC-SF). Adjusted binary logistic regression analyses indicated that those who achieve moderate and strenuous self-reported physical activity have 130% higher odds (p = 0.0422) of positive mental well-being after adjustment for age, attendance, and self-reported health. This study provides evidence that physical activity intensity and time are associated with flourishing mental health among Hispanics. The study provides insight into the planning and development of community-based physical activity programming tailored to low-income populations.

Optical artificial neural networks (ONNs) — analog computing hardware tailored for machine learning [1,2] — have significant potential for ultra-high computing speed and energy efficiency [3]. We propose a new approach to architectures for ONNs based on integrated Kerr micro-comb sources [4] that is programmable, highly scalable and capable of reaching ultra-high speeds. We experimentally demonstrate the building block of the ONN — a single neuron perceptron — by mapping synapses onto 49 wavelengths of a micro-comb to achieve a high single-unit throughput of 11.9 Giga-FLOPS at 8 bits per FLOP, corresponding to 95.2 Gbps. We test the perceptron on simple standard benchmark datasets — handwritten-digit recognition and cancer-cell detection — achieving over 90% and 85% accuracy, respectively. This performance is a direct result of the record small wavelength spacing (49GHz) for a coherent integrated microcomb source, which results in an unprecedented number of wavelengths for neuromorphic optics. Finally, we propose an approach to scaling the perceptron to a deep learning network using the same single micro-comb device and standard off-the-shelf telecommunications technology, for high-throughput operation involving full matrix multiplication for applications such as real-time massive data processing for unmanned vehicle and aircraft tracking.

Plant geneticists and breeders have used marker technology since the 1980s in quantitative trait locus (QTL) identification. Marker-assisted selection is effective for large-effect QTL but has been challenging to use with quantitative traits controlled by multiple minor effect alleles. Therefore, genomic selection (GS) was proposed to estimate all markers simultaneously, thereby capturing all their effects. However, breeding programs are still struggling to identify the best strategy to implement it into their programs. Traditional breeding programs need to be optimized to implement GS effectively. This review explores the optimization of breeding programs for variety release based on aspects of the breeder’s equation. Optimizations include reorganizing field designs, training populations, increasing the number of lines evaluated, and leveraging the large amount of genomic and phenotypic data collected across different growing seasons and environments to increase heritability estimates, selection intensity, and selection accuracy. Breeding programs can leverage their phenotypic and genotypic data to maximize genetic gain and selection accuracy through GS methods utilizing multi-trait and, multi-environment models, high-throughput phenotyping, and deep learning approaches. Overall, this review describes various methods that plant breeders can utilize to increase genetic gains and effectively implement GS in breeding .

Dengue virus infections are a serious public health problem worldwide. Aedes aegypti is the primary vector of dengue in Cuba. Since there is no vaccine or specific treatment, the control efforts are directed to reduce mosquito populations. The indiscriminate use of pesticides can lead to increase insecticide resistance as well as adverse effects on human health. The sterile insect technique is a species-specific and environmental friendly method of insect control based on the release of large numbers of sterile males. The success of this technique in sustainable control of agricultural pests has encouraged its evaluation for mosquito control. Here, we describe an open field trial to evaluate the effect of the release of irradiated males on a wild population of Aedes aegypti. The case-control study was performed in a suburb of Havana, and compared the mosquito population before and after the intervention, in both control and treated areas. The wild population was monitored by an ovitrap network, recording frequency and density of eggs as well as their hatch rate. A significant induced sterility was observed in the field population, compared to the control. The ovitrap index and the mean eggs/ trap declined dramatically after an expected lag period of twelve and five weeks, respectively. For the last three weeks, no egg was collected in the treated area, evidencing a significant suppression of the wild population. We conclude that the sterile males released competed successfully, and induced enough sterility to suppress the local Aedes aegypti population.

Direct cardiac reprogramming of fibroblasts into induced cardiomyocytes (iCMs) is a promising approach but remains a challenging technology of regenerative medicine for damaged myocardium. Efforts have been focused on improving the efficiency by understanding fundamental mechanisms. One of the major challenges is that the plasticity of cultured fibroblast varies batch to batch with unknown mechanisms. Here, we noticed that a portion of in vitro cultured fibroblasts have been activated to differentiate into myofibroblasts, marked by the expression of αSMA, even in the primary cell culture of tissues. Both forskolin, which activates adenylyl cyclase and increases cAMP concentration, and TGFbeta inhibitor SB431542 can efficiently suppress myofibroblast differentiation of cultured fibroblasts. However, SB431542 improved but forskolin blocked iCM reprogramming of fibroblasts that were infected with retroviruses of Gata4, Mef2c and Tbx5 (GMT). Moreover, inhibitors of cAMP downstream signaling pathways, PKA or CREB-CBP, significantly improved the efficiency of iCM reprogramming. Consistently, inhibition of p38/MAPK, another upstream regulator of CREB-CBP, also improved reprogramming efficiency. We then investigated if inhibition of these signaling pathways in primary cultured fibroblast could improve their plasticity for reprogramming, and found that preconditioning of cultured fibroblasts with CREB-CBP inhibitor significantly improved the cellular plasticity of fibroblasts to be reprogrammed, yielding ~2-fold amount of reprogrammed iCMs compared to that of untreated control cells. In conclusion, suppression of cAMP/PKA/CREB signaling axis improves fibroblast plasticity for direct cardiac reprogramming.

Fabrics comprised of porous fibers could provide effective passive protection against chemical and biological (CB) threats whilst maintaining high air permeability (breathability). Here, we fabricate hierarchically porous fibers consisting of regenerated silk fibroin (RSF) and activated-carbon (AC) prepared through two fiber spinning techniques in combination with ice-templating – namely cryogenic solution blow spinning (Cryo-SBS) and cryogenic wet-spinning (Cryo-WS). The Cryo-WS RSF fibers had exceptionally small macropores (as low as 0.1 µm) and high specific surface areas (SSAs) of up to 79 m2 g-1. The incorporation of AC could further increase the SSA to 210 m2 g-1 (25 wt. % loading) whilst also increasing adsorption capacity for volatile organic compounds (VOCs).

This research investigates the exposure of plant species to extreme drought events in the Brazilian Atlantic Forest, employing an extensive dataset collected from 205 automatic weather stations across the region. Meteorological indicators derived from hourly data, encompassing precipitation, maximum and minimum air temperature, were utilized to quantify past, current, and future drought conditions. The dataset, comprising 10,299,236 data points, spans a substantial temporal window and exhibits a modest percentage of missing data. Missing data were excluded from analysis, aligning with the decision to refrain from imputation methods due to potential bias. Drought quantification involved the computation of the Aridity Index, the analysis of consecutive hours without precipitation, and the classification of wet and dry days per month. Mann-Kendall trend analysis was applied to assess trends in evapotranspiration and maximum air temperature, considering their significance. The hazard assessment, incorporating environmental factors influencing tree growth dynamics, facilitated the ranking of meteorological indicators to identify regions most exposed to drought events. The results revealed consistent occurrences of extreme rainfall events, indicated by positive outliers in monthly precipitation values. However, significant trends were observed, including an increase in daily maximum temperature and consecutive hours without precipitation, coupled with a decrease in daily precipitation across the Brazilian Atlantic Forest. No significant correlation between vulnerability ranks and weather station latitudes and elevation were found, suggesting geographical location and elevation does not strongly influence observed dryness trends.

Betadine (Providone-Iodine) solution is a topically applied antiseptic, which has been used for wound care and surgery for decades for the prevention and treatment of skin and wound infections. However, several studies have documented the ineffectiveness of Betadine solution. Other topical antimicrobial dressings, including those that contain silver, have been used in the management of infected wounds. The present study was undertaken to determine if the combination of 5% Betadine solutions and silver colloidal gel (Ag-gel), is more effective than the individual materials in inhibiting the growth of both Gram negative and Gram positive bacteria. These determinations were carried out by both the colony forming unit (CFU) assay, and confocal laser scanning microscopy (CLSM). Ag-gel showed complete inhibition on all the bacteria, except Klebsiella pneumoniae CI strain while 5% Betadine concentrations did not completely kill any of the tested bacteria. However, K. pneumoniae was completely eliminated in the presence of the combination of 5% Betadine solution plus Ag-gel. Confocal laser microscopy confirmed the CFU results. Thus this study demonstrated that while the individual treatments are not effective in killing all the bacteria tested, the combination of 5% Betadine solution and Ag-gel completely kill all bacteria tested, including K. penumoniae CI.

Human-to-human communication via the computer is mainly done using a keyboard or microphone. In the field of Virtual Reality (VR), where the most immersive experience possible is desired, the use of a keyboard contradicts this goal, while the use of a microphone is not always desirable (e.g. silent commands during task force training) or simply not possible (e.g. if the user has a hearing loss). Data gloves help to increase immersion within the VR as they correspond to our natural interaction. At the same time, they offer the possibility to accurately capture hand shapes, such as those used in non-verbal communication (e.g. thumbs up, okay gesture, ...) and in sign language. In this paper, we present a hand shape recognition system using Manus Prime X data gloves, including data acquisition, data preprocessing, and data classification to enable nonverbal communication within VR. We investigate the impact on accuracy and classification time of using an Outlier Detection and a Feature Selection approach in our data preprocessing. To obtain a more generalized approach, we also studied the impact of artificial Data Augmentation, i.e., we create new artificial data from the recorded and filtered data to augment the training dataset. With our approach, 56 different hand shapes could be distinguished with an accuracy of up to 93.28%. With a reduced number of 27 hand shapes, an accuracy of up to 95.55% could be achieved. Voting Meta-Classifier (VL2) has proven to be the most accurate, albeit slowest, classifier. A good alternative is Random Forest (RF), which was even able to achieve better accuracy values in a few cases and was generally somewhat faster. Outlier Detection has proven to be a effective approach, especially in improving classification time. Overall, we have shown that our hand shape recognition system using data gloves is suitable for communication within VR.

Executive functioning is a key component involved in many of the processes necessary for effective weight management behavior change (e.g., setting goals). Cognitive behavioral therapy (CBT) and third-wave CBT (e.g., mindfulness) are considered first-line treatments for obesity, but it is unknown to what extent they can improve or sustain executive functioning. This pilot randomized controlled trial examined if a CBT-based generalized weight management intervention would affect executive functioning and executive function-related brain activity in individuals with obesity or overweight. Participants were randomized to an intervention condition (N=24) that received the Noom Weight program or to a control group (N=26) receiving weekly educational newsletters. EEG measurements were taken during Flanker, Stroop, and N-back tasks at baseline and months 1 through 4. After 4 months, the intervention condition evidenced greater accuracy over time and, to some extent, neural markers of executive function (error-related negativity and beta and gamma band powers) compared to the control group on the Flanker and Stroop tasks. The intervention condition also lost more weight than controls (-7.1 pounds vs. +1.0 pounds). Given mixed evidence on whether CBT-based interventions can change markers of executive function, this study contributes preliminary evidence that a multicomponent CBT-based weight management intervention (i.e., that provide both support for weight management and is based on CBT) can help individuals sustain executive function compared to controls.

Excessive extracellular histones can damage cells despite their importance in DNA structure and gene regulation. We previously showed the harmful effect of histone 3.3 (H3.3) and its acetylated form (AcH3.3) in chronic obstructive pulmonary disease (COPD), but further research is needed to understand the in vivo underlying mechanisms. To investigate this, we administered a single dose of recombinant histones via intra-tracheal instillation in C57BL/6 mice and analyzed the outcomes after 48 hours. Both rH3.3 and rAcH3.3 effectively reached the bronchial and alveolar space. Lung histology revealed severe immune cell infiltration, rupture, damage, and thickening of many alveolar walls. Micro-CT scans showed macroscopic structure changes with a decreased tissue volume to total volume ratio. The administration of rH3.3 and rAcH3.3 induced lung apoptotic activity, as indicated by increased levels of cleavage caspase 3 and 9. Moreover, elevated plasma levels of pro-inflammatory cell mediators, including TNF-alpha, IL-6, MCP-3, and CXCL-1, were observed. The pathological changes and pro-inflammatory cytokine response were more pronounced in animals treated with rAcH3.3, which also exhibited leukocytosis and lymphocytosis. These findings emphasize the crucial role of extracellular H3.3 acetylation in inducing cytotoxicity and a robust, acute inflammatory response similar to what occurs in the lungs of COPD patients.

Soluble cell adhesion molecules (sCAMs) are secreted ectodomain fragments of surface adhesion molecules, ICAM1 and VCAM1. sCAMs have diverse immune functions beyond their primary function, impacting immune cell recruitment and activation. Elevated sVCAM1 levels have been associated with poor cardiovascular disease (CVD) outcomes, supporting its role as a potential diagnostic marker and therapeutic target. Inhibiting sVCAM1 release or interaction with immune cells could offer cardioprotection in conditions such as diabetes. Membrane bound surface adhesion molecules are widely expressed in a wide variety of cell types with higher expression in endothelial cells (ECs), but the source of sCAMs in the circulation is not clear. Hypothesizing that endothelial cells (ECs) could be a potential source of sCAMs, this study investigated whether dysfunctional EC signaling mechanisms during diabetes cause VCAM1 ectodomain shedding. Our results from samples from a inducible diabetic mouse model revealed increased sVCAM1 plasma levels in diabetes. Protein analysis indicated upregulated VCAM1 expression and metalloproteases ADAM10 and ADAM17 in diabetic ECs. ADAMs are known for proteolytic cleavage of adhesion molecules, contributing to inflammation. GSK3β, implicated in EC VCAM1 expression, was found to be activated in diabetic ECs. GSK3β overexpression in control ECs increased ADAM10/17 and VCAM1. A GSK3β inhibitor reduced active GSK3β and VCAM1 ectodomain shedding. These findings suggest that diabetic ECs with elevated GSK3β activity led to VCAM1 upregulation and ADAM10/17-mediated sVCAM1 shedding. This mechanism underscores the potential therapeutic role of GSK3β inhibition in reducing the levels of circulating sVCAM1. The complex roles of sCAMs extend well beyond CVD. Thus, unraveling the intricate involvement of sCAMs in the initiation and progression of vascular disease particularly in diabetes, holds significant therapeutic potential.

With the renewed interest for lunar surface exploration, the European Space Agency envisions to stimulate the creation of lunar communications and navigation services (LCNS) to enable, among others, autonomous navigation capabilities for lunar rovers. As the number of satellites foreseen in such a service is much smaller compared to Earth based global navigation satellite systems (GNSS), different complementary technologies are pursued to improve the attainable navigation accuracy for lunar rovers. One way to improve the position accuracy provided by the LCNS satellites is to constrain the vertical position using a high resolution digital elevation model (DEM). This article presents the results of a variance covariance analysis of an extended Kalman filter (EKF) implementation in which the LCNS ranging measurements are used together with DEM from the LRO LOLA instrument. Assuming a realistic orbit determination and time synchronization (ODTS) accuracy of the LCNS satellites, the usage of a navigation grade IMU and an oven controlled crystal oscillator (OCXO), a 3-sigma position accuracy of less than 10 meters can be obtained. Furthermore, the availability is substantially improved as the DEM aided solution enables a position solution in case of only 3 visible satellites.

Real-time quaking-induced conversion (RT-QuIC) assays have become common in the detection of chronic wasting disease (CWD) and are very sensitive provided the assay duration is sufficient. However, a prolonged assay duration may lead to non-specific signal amplification. The wide range of pre-defined assay durations in current RT-QuIC applications presents a need for optimization of the RT-QuIC assay duration. In this study, receiver operating characteristic (ROC) analysis was applied to optimize assay duration for detection of CWD in obex and retropharyngeal lymph node (RLN) tissue specimens. Two different fluorescence thresholds were used: a fixed threshold based on background fluorescence (Tstdev) and a max-point ratio (maximum/background fluorescence) threshold (TMPR) to determine CWD positivity. The optimal assay duration was 27 h for both obex and RLN based on Tstdev, and 27 and 28 h for obex and RLN, respectively, based on TMPR. The optimized assay durations were then evaluated for screening CWD in white-tailed deer from an affected farm. Results by RT-QuIC using optimized duration based on Tstdev and TMPR were in 100% and 92.3 % or higher agreement with those by the widely used screening assay, ELISA. In comparison, when using a 40 h assay duration, the agreement between RT-QuIC and ELISA reduced to 89.2% or higher, and the RT-QuIC results were significantly (p < 0.05) different from those using optimum durations. These findings demonstrated that the application of ROC analysis for the optimization of assay duration could improve the RT-QuIC assay for screening CWD in white-tailed deer.

The World Health Organization has defined the outbreak of the new coronavirus as a public health emergency of international concern. The average age of patients affected by the disease caused by the virus ranges from 49 to 59 years. The symptoms of coronavirus disease 2019 (COVID-19) infection include fever, cough, acute respiratory disease, and, in severe cases, the disease may progress to pneumonia and renal failure that may lead to death. Many oral and maxillofacial hospital procedures produce aerosol and droplets contaminated by blood, bacteria, and viruses. The purpose of this study is to gather recommendations from health authorities and scientific articles in order to educate surgeons regarding the procedures to assist and treat in oral and maxillofacial surgeries. The objective is to prevent the transmission of COVID-19 during the treatment of patients in urgent and emergency situations. The study’s methodology used the guidelines provided by the Brazilian College of Oral and Maxillofacial Surgery, in addition to the recommendations and epidemiologic data from national and international health authorities. The implementation of special precautions in oral and maxillofacial surgeries may elucidate questions related to the transmission of the disease by asymptomatic carriers and help control the spread of the virus.

The cost to train a basic qualified U.S. Navy fighter aircraft pilot is nearly $10M. The training includes primary, intermediate, and advanced stages, with the advanced stage involving extensive flight training and being very expensive as a result. Despite the screening tests in place and early-stage attrition taking place, 4.5% of aviators undergo attrition in this most expensive stage. Key reasons for aviator attrition include poor flight scores, voluntary withdrawals, and medical causes. Reduction in late-stage attrition offers several financial and operational benefits to the U.S. Navy. To that end, this research leverages feature extraction and machine-learning techniques on the very sparse flight test grades of student aviators to identify those with a high risk of attrition early in training. Using about 10 years of historical U.S. Navy pilot training data, trained models accurately predicted 50% of attrition with a 4% false positive rate. Such models could help the U.S. Navy save nearly $20M a year in attrition costs. In addition, machine-learning models were trained that can recommend a suitable training aircraft type for each student aviator. These capabilities could help better answer the need for pilots and reduce the time and cost to train them.