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Background: The recovery from cardiac surgery involves resolving inflammation and remodeling with significant connective tissue turnover. Dynamics of smoldering inflammation and injury (white blood cells, platelets, CRP, IL-8, IL-6), vascular inflammation (IL-15, VEGF, RANTES), connective tissue remodeling (tenascin, MMP-9), cardiac injury and remodeling (YKL-40), and vascular remodeling (epiregulin, MCP-1, VEGF) were assessed up to 3 months after cardiac surgery. We hypothesize that at 3 months, studied markers will return to pre-surgical levels., Methods: Patients (n = 139) scheduled for non-emergent heart surgery were included, except for patients with pre-existing immunological aberrancies. Blood was collected before surgery(t baseline ), 24 h later(t 24h ) after the first sample, 7 days(t 7d ), and 3 months(t 3m ) after t baseline . Serum markers were measured via multiplex or ELISA. Electronic medical records (EMR) were used to extract demographical, pre-existing conditions and clinical data. Disposition (discharge home, discharge to facility, death, re-admission) was determined at 28 days and 3 months from admission., Results: Not all inflammatory markers returned to baseline (CRP↑↑, leukocytosis, thrombocytosis, IL-8↓, IL-6↓). Tenascin and YKL-40 levels remained elevated even at t 3m . YKL-40 serum levels were significantly elevated at t 24h and t 7d while normalized at t 3m . VEGF returned to the baseline, yet MCP-1 remained elevated at 3 months. CCL28 increased at 3 months, while RANTES and IL-15 declined at the same time. Disposition at discharge was determined by serum MMP-9, while YKL-40 correlated with duration of surgery and APACHE II 24h ., Conclusions: The data demonstrated an ongoing extracellular matrix turnover at 3 months, while acute inflammation and vascular remodeling resolved only partially., (© 2022. The Author(s).)

BACKGROUND Cardiac surgery triggers acute changes in serum leptin and fibroblast growth factor 21 (FGF-21). Considering their pleiotropic role in inflammation and abnormal glucose metabolism, perseverance of their abnormal serum level can have a long-term impact on recovery and end-organ failures. Long-term dynamics after cardiac surgery are unknown. MATERIAL AND METHODS Serum was collected from 123 patients before cardiac surgery (tbaseline) and 24 h (t24h), 7 days (t7d), and 3 months (t3m) later. Also, interleukin 6 (IL-6) and C-reactive protein (CRP) assessed nonspecific inflammatory responses. Neurodegeneration was gauged with serum amyloid ß1-40 and ß1-42. Demographic and clinical information, including disposition at 28 days and t3m from admission, were collected. RESULTS Serum leptin increased at t24h (leptinbaseline=613+747.9 vs leptin24h=768±718.1; P=0.0083) and decreased at t7d (leptin7d=499.5±540.2; P=0.043). FGF-21 levels increased at t24h and t7d. Cytokines normalized by t3m. Presurgical leptin levels were higher in Asians and were the primary determinant of postoperative leptin changes. Leptin levels were most elevated in patients undergoing aortic valve and arch surgery; the perioperative increase was significant only in patients with mitral valve surgery. Leptin and FGF-21 did not correlate with markers of general inflammation (CRP, IL-6), which partially resolved after t3m. Amyloid ß1-42 at t3m correlated with leptin peak at t24h. Low prehospital FGF-21 level correlated with the incidence of perioperative stroke; postoperative FGF-21 correlated with discharge to facility vs home. CONCLUSIONS Leptin and FGF-21 evolve independently from the inflammatory response in the aftermath of cardiac surgery and correlate with cardiac remodeling and neurodegeneration markers.

Although several therapeutics are used to treat coronavirus disease 2019 (COVID-19) patients, there is still no definitive metabolic marker to evaluate disease severity and recovery or a quantitative test to end quarantine. Because severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infects human cells via the angiotensin-converting-enzyme 2 (ACE2) receptor and COVID-19 is associated with renin-angiotensin system dysregulation, we evaluated soluble ACE2 (sACE2) activity in the plasma/saliva of 80 hospitalized COVID-19 patients and 27 non-COVID-19 volunteers, and levels of ACE2/Ang (1-7) in plasma or membrane (mACE2) in lung autopsy samples. sACE2 activity was markedly reduced (p < 0.0001) in COVID-19 plasma (n = 59) compared with controls (n = 27). Nadir sACE2 activity in early hospitalization was restored during disease recovery, irrespective of patient age, demographic variations, or comorbidity; in convalescent plasma-administered patients (n = 45), restoration was statistically higher than matched controls (n = 22, p = 0.0021). ACE2 activity was also substantially reduced in the saliva of COVID-19 patients compared with controls (p = 0.0065). There is a strong inverse correlation between sACE2 concentration and sACE2 activity and Ang (1-7) levels in participant plasmas. However, there were no difference in membrane ACE2 levels in lungs of autopsy tissues of COVID-19 (n = 800) versus other conditions (n = 300). These clinical observations suggest sACE2 activity as a potential biomarker and therapeutic target for COVID-19., Competing Interests: Authors declare no competing interests., (© 2022 The Authors.)

Background: Despite clinical relevance of immunological activation due to histone leakage into the serum following cardiac surgery, long-term data describing their longitudinal dynamic are lacking. Therefore, this study examines the serum levels of histone 3 (tH3) and its modifications (H3K4me3 and H3K27ac) alongside immune system activation during the acute and convalescence phases of cardiac surgery., Methods: Blood samples from fifty-nine individuals were collected before non-emergent cardiac surgery (t pre-op ) and 24 h (t 24hr ), seven days (t 7d ), and three months (t 3m ) post-procedure to examine serum levels of tH3, H3K4me3, and H3K27ac. Serum heat shock protein-60 (HSP-60) was a surrogate of the cellular damage marker. Serum C-reactive protein (CRP) and interleukin 6 (IL-6) assessed smoldering inflammation. TNFα and IL-6 production by whole blood in response to lipopolysaccharide (LPS) evaluated immunological activation. Electronic medical records provided demographic, peri-operative, and clinical information. Paired longitudinal analyses were employed with data expressed as mean and standard deviation (X ± SD) or median and interquartile range (Me[IQ25; 75%]., Results: Compared to pre-operative levels (tH3 Pre-op  = 1.6[0.33;2.4]), post-operative serum tH3 significantly (p > 0.0001) increased after heart surgery (tH3 24hr  = 2.2[0.3;28]), remained elevated at 7 days (tH3 7d  = 2.4[0.37;5.3]), and at 3 months (tH3 3m  = 2.0[0.31;2.9]). Serum H3K27ac was elevated at 24 h (H3K27ac 24hr  = 0.66 ± 0.51; p = 0.025) and seven days (H3K27ac 7d  = 0.94 ± 0.95; p = 0.032) as compared to baseline hours (H3K27ac Pre-op  = 0.55 ± 0.54). Serum H3K4me3 was significantly diminished at three months (H3K4me3 Pre-op  = 0.94 ± 0.54 vs. H3K27ac 3m  = 0.59 ± 0.89; p = 0.008). tH3 correlated significantly with the duration of anesthesia (r 2  = 0.38). In contrast, HSP-60 normalized seven days after surgery. Peri-operative intake of acetaminophen, but no acetylsalicylic acid (ASA), acid, ketorolac or steroids, resulted in the significant depression of serum H3K4me3 at 24 h (H3K4me3 acetom-  = 1.26[0.71; 3.21] vs H3K4me3 acetom+  = 0.54[0.07;1.01]; W[50] = 2.26; p = 0.021). CRP, but not IL-6, remained elevated at 3 months compared to pre-surgical levels and correlated with tH3 24hrs (r 2  = 0.43), tH3 7d (r 2  = 0.71; p < 0.05), H3K4me3 7d (r 2  = 0.53), and H3K27ac 7d (r 2  = 0.49). Production of TNFα by whole blood in response to LPS was associated with serum tH3 24hrs (r 2  = 0.67). Diminished H3K4me3 24hrs, H3K27ac 24hrs , and H3K27ac 3m , accompanied the emergence of liver failure., Conclusions: We demonstrated a prolonged elevation in serum histone 3 three months after cardiac surgery. Furthermore, histone 3 modifications had a discrete time evolution indicating differential immune activation., (© 2022. The Author(s).)

Incorporating the advanced practice provider (APP) in the delivery of tele critical care medicine (teleCCM) addresses the critical care provider shortage. However, the current literature lacks details of potential workflows, deployment difficulties and implementation outcomes while suggesting that expanding teleCCM service may be difficult. Here, we demonstrate the implementation of a telemedicine APP (eAPP) pilot service within an existing teleCCM program with the objective of determining the feasibility and ease of deployment. The goal is to augment an existing tele-ICU system with a balanced APP service to assess the feasibility and potential impact on the ICU performance in several hospitals affiliated within a large academic center. A REDCap survey was used to assess eAPP workflows, expediency of interventions, duration of tasks, and types of assignments within different service locations. Between 02/01/2021 and 08/31/2021, 204 interventions (across 133 12-h shift) were recorded by eAPP (n routine  = 109 (53.4%); n urgent  = 82 (40.2%); n emergent  = 13 (6.4%). The average task duration was 10.9 ± 6.22 min, but there was a significant difference based on the expediency of the task (F [2; 202] = 3.89; p < 0.022) and type of tasks (F [7; 220] = 6.69; p < 0.001). Furthermore, the eAPP task type and expediency varied depending upon the unit engaged and timeframe since implementation. The eAPP interventions were effectively communicated with bedside staff with only 0.5% of suggestions rejected. Only in 2% cases did the eAPP report distress. In summary, the eAPP can be rapidly deployed in existing teleCCM settings, providing adaptable and valuable care that addresses the specific needs of different ICUs while simultaneously enhancing the delivery of ICU care. Further studies are needed to quantify the input more robustly., (© 2022. The Author(s).)

Identification of novel immune biomarkers to gauge the underlying pathology and severity of COVID-19 has been difficult due to the lack of longitudinal studies. Here, we analyzed serum collected upon COVID-19 admission (t1), 48 hours (t2), and seven days later (t3) using Olink proteomics and correlated to clinical, demographics, and therapeutic data. Older age positively correlated with decorin, pleiotrophin, and TNFRS21 but inversely correlated with chemokine (both C-C and C-X-C type) ligands, monocyte attractant proteins (MCP) and TNFRS14. The burden of pre-existing conditions was positively correlated with MCP-4, CAIX, TWEAK, TNFRS12A, and PD-L2 levels. Individuals with COVID-19 demonstrated increased expression of several chemokines, most notably from the C-C and C-X-C family, as well as MCP-1 and MCP-3 early in the course of the disease. Similarly, deceased individuals had elevated MCP-1 and MCP-3 as well as Gal-9 serum levels. LAMP3, GZMB, and LAG3 at admission correlated with mortality. Only CX3CL13 and MCP-4 correlated positively with APACHE score and length of stay, while decorin, MUC-16 and TNFRSF21 with being admitted to the ICU. We also identified several organ-failure-specific immunological markers, including those for respiratory (IL-18, IL-15, Gal-9) or kidney failure (CD28, VEGF). Treatment with hydroxychloroquine, remdesivir, convalescent plasma, and steroids had a very limited effect on the serum variation of biomarkers. Our study identified several potential targets related to COVID-19 heterogeneity (MCP-1, MCP-3, MCP-4, TNFR superfamily members, and programmed death-ligand), suggesting a potential role of these molecules in the pathology of COVID-19., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Laudanski, Jihane, Antalosky, Ghani, Phan, Hernandez, Okeke, Wu, Rader and Susztak.)

In this paper, we study the dynamics of the CoVid-19 outbreak in Semarang, Indonesia, using a fractional CoVid-19 model. We first determine the effects of the isolation rate e and infection rate ẞ on the reрго- duction number Ro and infected number V. We find that Ro is directly proportional to ẞ and inversely proportional to e. For V, the effect of physical distancing is not as significant as changing e. As e increases, V decreases, the number of susceptible individuals increases, the number of quarantined individuals decreases sharply, and the number of recovered individuals decreases. Moreover, the effect of vaccination is also considered. The combination of physical distancing, isolation, and vaccination has a significant impact on reducing the number of infected individuals. Analysis of dynamical systems allows us to understand the characteristics of our model, such as its boundedness and non-negativity, the existence of equilibrium points, the existence and uniqueness of solutions, and the local and global stability. To val- idate our fractional CoVid-19 model, we introduce the fractional extended Kalman filter (FracEKF) as a prediction method and compare the results against reported CoVid-19 data. FracEKF is a modified version of the basic extended Kalman filter with a time-fractional memory effect. The prediction results illustrate the accuracy of this model in terms of the root mean square error (RMSE), normalized root mean square еггог (NRMSE), and mean absolute percentage error (MAPE) for each fractional-order. Varying e repro- duces the trends observed in the reported data for the number of infected individuals, i.e., when e increases, the infected number decreases. Moreover, a higher fractional-order results in higher model accuracy. Furthermore, higher values of the process noise Q give smaller errors, whereas higher values of the observation noise Ry produce higher errors. Q, and the fractional-order are inversely proportional to RMSE, NRMSE, and MAPE, whereas Ry is directly proportional to RMSE, NRMSE, and MAPE. [ABSTRACT FROM AUTHOR]

Background/Objectives: For several decades, protein drugs (biologics) made in cell cultures have been delivered as sterile injections, decreasing their affordability and patient preference. Angiotensin Converting Enzyme 2 (ACE2) gum is the first engineered human blood protein expressed in plant cells approved by the FDA without the need for purification and is a cold-chain and noninvasive drug delivery. This biologic is currently being evaluated in human clinical studies to debulk SARS-CoV-2 in the oral cavity to reduce coronavirus infection/transmission (NCT 0543318). Methods: Chemistry, manufacturing, and control (CMC) studies for the ACE2/Ang(1–7) drug substances (DSs) and ACE2 gum drug product (DP) were conducted following USP guidelines. GLP-compliant toxicology studies were conducted on Sprague Dawley rats (n = 120; 15/sex/group) in four groups—placebo, low (1.6/1.0 mg), medium (3.2/2.0 mg), and high (8.3/5.0 mg) doses IP/kg/day. Oral gavage was performed twice daily for 14 days (the dosing phase) followed by the recovery phase (35 days). Plasma samples (n = 216) were analyzed for the product Ang(1–7) by ELISA. Results: The ACE2 protein was stable in the gum for at least up to 78 weeks. The toxicology study revealed the dose-related drug delivery to the plasma and increases in the AUC (56.6%) and Cmax (52.9%) after 28 high-dose gavages (95% C.I.), although this quantitation excludes exogenously delivered membrane-associated ACE2/Ang(1–7). Vital biomarkers and organs were not adversely affected despite the 10-fold higher absorption in the tissues, demonstrating the safety for the first in-human clinical trials of ACE2/Ang(1–7). The NOAEL observed in the rats was 2.5–7.5-fold higher than that of the anticipated efficacious therapeutic dose in humans for the treatment of cardiopulmonary disorders, and it was 314-fold higher than the NOAEL for topical delivery via chewing gum. Conclusions: This report lays the foundation for the regulatory process approval for noninvasive and affordable human biologic drugs bioencapsulated in plant cells. [ABSTRACT FROM AUTHOR]

Copyright of Retos: Nuevas Perspectivas de Educación Física, Deporte y Recreación is the property of Federacion Espanola de Asociaciones de Docentes de Educacion Fisica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For a two-block splitting iterative scheme to solve the complex linear equations system resulting from the complex Helmholtz equation, the iterative form using descent vector and residual vector is formulated. We propose splitting iterative schemes by considering the perpendicular property of consecutive residual vector. The two-block splitting iterative schemes are proven to have absolute convergence, and the residual is minimized at each iteration step. Single and double parameters in the two-block splitting iterative schemes are derived explicitly utilizing the orthogonality condition or the minimality conditions. Some simulations of complex Helmholtz equations are performed to exhibit the performance of the proposed two-block iterative schemes endowed with optimal values of parameters. The primary novelty and major contribution of this paper lies in using the orthogonality condition of residual vectors to optimize the iterative process. The proposed method might fill a gap in the current literature, where existing iterative methods either lack explicit parameter optimization or struggle with high wave numbers and large damping constants in the complex Helmholtz equation. The two-block splitting iterative scheme provides an efficient and convergent solution, even in challenging cases. [ABSTRACT FROM AUTHOR]

The optimization of maintenance intervals is crucial for enhancing efficiency, sustainability, and cost-effectiveness in transport operations. This paper presents a method for optimizing maintenance intervals for vehicles in various modes of transport, focusing on minimizing downtime due to repairs and maintenance. By integrating advanced technologies like artificial intelligence (AI) and the Internet of Things (IoT), maintenance intervals are dynamically adjusted using real-time data, resulting in better resource utilization and reduced operational costs. The key findings of this research indicate significant reductions in downtime and maintenance costs, leading to improved efficiency and sustainability across transport modes. Although the case study is based on railway vehicles, the approach is applicable to road, maritime, and air transport as well. By leveraging optimization algorithms, such as machine learning, this solution predicts optimal maintenance timing, thereby reducing resource consumption and improving operational efficiency. The case study on pantograph maintenance demonstrates significant financial savings and reduced waste. This research highlights the benefits of maintenance optimization for sustainability and efficiency across the entire transport sector. [ABSTRACT FROM AUTHOR]

Background/Objectives: Taste dysfunction is a frequent symptom of acute coronavirus disease (COVID)-19 caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). While the majority of those affected reported recovery over time, emerging data suggest that 20–25% of individuals experience persistent taste dysfunction, constituting a common symptom of long COVID. Gustation is mediated by continuously renewing taste bud cells. A balance between the counteracting processes of cell generation and cell death maintains the homeostatic turnover. Sonic hedgehog (SHH) is a morphogenic protein that promotes taste cell proliferation and differentiation. Enzymatic proteins such as gustin modulate the environment around the taste receptors and influence taste perception. Hence, we hypothesized that increased taste cell turnover and reduced taste-related salivary proteins contribute to the taste dysfunction in long COVID. Methods: Unstimulated whole saliva (UWS) was collected from individuals with long COVID experiencing taste dysfunction after obtaining informed consent. The normal control included archived saliva samples catalogued prior to 2019. Taste perception was objectively determined by the waterless empirical taste test. The SHH, gustin, and inflammatory cytokines in UWS were determined with ELISA. The expressions of epithelial and taste-cell-specific markers in cellular saliva were assessed by immunoflurorescence. Results: Impaired bitter taste was the most common dysfunction in the long-COVID cohort. Salivary gustin was significantly lower in those with long COVID and correlated with lower bitter taste score. Cellular saliva showed keratin-10- and small-proline-rich protein-positive epithelial cells as well as SHH-, occluding- and KCNQ1-positive taste cells. Conclusions: Salivary gustin could be a marker for impaired bitter taste in long COVID. [ABSTRACT FROM AUTHOR]

In the medical image analysis field, brain tumors (BTs) classification is a complicated process. For effortlessly detecting the tumor devoid of any surgical interference, the radiologists are aided with automated along with computerized technology. Currently, in the field of medical image processing along with analysis, admirable progress has been made by deep learning (DL) methodologies. In medical fields, for resolving several issues, huge attention was paid to DL techniques. For automation of several performed by radiologists like (1) lesion detection, (2) segmentation, (3) classification, (4) monitoring, along with (5) also prediction of treatment response that is not achievable without software, DL might be wielded. Nevertheless, classifying BTs by utilizing magnetic resonance imaging (MRI) has various complications like the difficulty of brain structure along with the intertwining of tissues in it; additionally, the brain's higher density nature also makes the BT Classification (BTC) process quite complex. Therefore, by utilizing novel systems, MRI-centric Automatic segmentation together with classifications of BT and swelling have been proposed to overcome the aforementioned issues. The proposed methodology underwent various operations to detect BTs effectively. Initially, by utilizing the Range-centric Otsu's Thresholding (ROT) algorithm, the skull stripping (SS) is conducted. After that, by performing contrast enhancement (CE) along with noise removal, the skull-stripped images are pre-processed. Next, by employing the Rectilinear Watershed Segmentation (RWS) algorithm, the tumor or swelling areas are segmented. Afterward, to obtain the precise tumor or swelling region, the morphological operations are executed on the segmented areas; subsequently, the desired along with relevant features are extracted. Lastly, the features being extracted are inputted to the classifier termed Uniform Convolution neural network (UCNN). The tumor tissues along with the swelling tissues are classified precisely in the classification phase. Here, the openly accessible BT Image Segmentation Benchmark (BRATS) datasets are utilized. Then, the outcomes obtained are analogized with prevailing methodologies. The experiential outcomes displayed that the BTC is performed by the proposed model with a higher accuracy rate; thus, outshined the other prevailing models. [ABSTRACT FROM AUTHOR]

Objectives: This study was performed to identify predictive markers of worse outcomes in patients with severe COVID-19 in an intensive care unit. Methods: Sixty patients with severe COVID-19, hospitalized in the Intensive Care Unit (ICU) between March and July 2021, were stratified into two groups according to the outcome survivors and non-survivors. After admission to the ICU, blood samples were collected directly for biomarker analysis. Routine hematological and biochemical biomarkers, as well as serum levels of cytokines, chemokines, and immunoglobulins, were investigated. Results: Lymphopenia, neutrophilia, and thrombocytopenia were more pronounced in non-surviving patients, while the levels of CRP, AST, creatinine, ferritin, AST, troponin I, urea, magnesium, and potassium were higher in the non-surviving group than the survival group. In addition, serum levels of IL-10, CCL2, CXCL9, and CXCL10 were significantly increased in patients who did not survive. These changes in the biomarkers evaluated were associated with increased mortality in patients with severe COVID-19. Conclusion: The present study confirmed and expanded the validity of laboratory biomarkers as indicators of mortality in severe COVID-19. [ABSTRACT FROM AUTHOR]

The pantograph–catenary system (PCS) is essential for trains to obtain electrical energy. As the train's operating speed increases, the vibration between the pantograph and the catenary intensifies, reducing the quality of the current collection. Active control may significantly reduce the vibration of the PCS, effectively lower the cost of line retrofitting, and enhance the quality of the current collection. This article proposes an improved deep deterministic policy gradient (IDDPG) for the pantograph active control problem, which delays updating the Actor and Target–Actor networks and adopts a reconstructed experience replay mechanism. The deep reinforcement learning (DRL) environment module was first established by creating a PCS coupling model. On this basis, the controller's DRL module is precisely designed using the IDDPG strategy. Ultimately, the control strategy is integrated with the PCS for training, and the controller's performance is validated on the PCS. Simulation experiments show that the improved strategy significantly reduces the training time, enhances the steady-state performance of the agent during later training stages, and effectively reduces the standard deviation of the pantograph–catenary contact force (PCCF) by an average of over 51.44%, effectively improving the quality of current collection. [ABSTRACT FROM AUTHOR]

Transport networks, such as vasculature or river networks, provide key functions in organisms and the environment. They usually contain loops whose significance for the stability and robustness of the network is well documented. However, the dynamics of their formation is usually not considered. Such structures often grow in response to the gradient of an external field. During evolution, extending branches compete for the available flux of the field, which leads to effective repulsion between them and screening of the shorter ones. Yet, in remarkably diverse processes, from unstable fluid flows to the canal system of jellyfish, loops suddenly form near the breakthrough when the longest branch reaches the boundary of the system. We provide a physical explanation for this universal behavior. Using a 1D model, we explain that the appearance of effective attractive forces results from the field drop inside the leading finger as it approaches the outlet. Furthermore, we numerically study the interactions between two fingers, including screening in the system and its disappearance near the breakthrough. Finally, we perform simulations of the temporal evolution of the fingers to show how revival and attraction to the longest finger leads to dynamic loop formation. We compare the simulations to the experiments and find that the dynamics of the shorter finger are well reproduced. Our results demonstrate that reconnection is a prevalent phenomenon in systems driven by diffusive fluxes, occurring both when the ratio of the mobility inside the growing structure to the mobility outside is low and near the breakthrough. [ABSTRACT FROM AUTHOR]

Place naming of a local area is closely related to geographic elements. Local names can also be used as a cultural identity and natural condition of a region. Nglanggeran Ancient Volcano (AV) area has local name elements highly influenced by those conditions. It is an interesting study material where a three-dimensional (3D) model can contribute as a medium to collect the place naming traces (toponym) in this area through participatory mapping. Participatory mapping, usually using 2D models in the form of sketches or maps, will be a separate story in interactive 3D media usage resulting from the photogrammetry process. It is expected that the media be able to show the geographical appearance of the Nglanggeran A. V area more clearly, such as geomorphology, geology, vegetation, hydrology; and even local culture, and contribute unexplored information* The results of participatory mapping in toponym collection are expected to be a medium that organizes the place naming of a local area into a complete database, along with the origin of the place names. It is also proposed that the results of participatory mapping through the 3D model be a means of preserving local culture in the Nglanggeran A.V area, making it more familiar to local residents and tourists. [ABSTRACT FROM AUTHOR]

The RAS is a hormonal system playing a pivotal role in the control of blood pressure and electrolyte homeostasis, the alteration of which is associated with different pathologies, including acute respiratory distress syndrome (ARDS). As such, it is not surprising that a number of studies have attempted to elucidate the role and balance of the renin–angiotensin system (RAS) in COVID-19. In this review article, we will describe the evidence collected regarding the two main enzymes of the RAS (i.e., ACE and ACE2) and their principal molecular products (i.e., AngII and Ang1-7) in SARS-CoV-2 infection, with the overarching goal of drawing conclusions on their possible role as clinical markers in association with disease severity, progression, and outcome. Moreover, we will bring into the picture new experimental data regarding the systemic activity of ACE and ACE2 as well as the concentration of AngII and Ang1-7 in a cohort of 47 COVID-19 patients hospitalized at the IRCCS Sacro Cuore-Don Calabria Hospital (Negrar, Italy) between March and April 2020. Finally, we will discuss the possibility of considering this systemic pathway as a clinical marker for COVID-19. [ABSTRACT FROM AUTHOR]

Dendritic mesoporous silica nanoparticles own three‐dimensional center‐radial channels and hierarchical pores, which endows themselves with super‐high specific surface area, extremely large pore volumes, especially accessible internal spaces, and so forth. Dissimilar guest species (such as organic groups or metal nanoparticles) could be readily decorated onto the interfaces of the channels and pores, realizing the functionalization of dendritic mesoporous silica nanoparticles for targeted applications. As adsorbents and catalysts, dendritic mesoporous silica nanoparticles‐based materials have experienced nonignorable development in CO2 capture and catalytic conversion. This comprehensive review provides a critical survey on this pregnant subject, summarizing the designed construction of novel dendritic mesoporous silica nanoparticles‐based materials, the involved chemical reactions (such as CO2 methanation, dry reforming of CH4), the value‐added chemicals from CO2 (such as cyclic carbonates, 2‐oxazolidinones, quinazoline‐2,4(1H,3H)‐diones), and so on. The adsorptive and catalytic performances have been compared with traditional silica mesoporous materials (such as SBA‐15 or MCM‐41), and the corresponding reaction mechanisms have been thoroughly revealed. It is sincerely expected that the in‐depth discussion could give materials scientists certain inspiration to design brand‐new dendritic mesoporous silica nanoparticles‐based materials with superior capabilities towards CO2 capture, utilization, and storage. [ABSTRACT FROM AUTHOR]

Emotional research in film and animation has long been implemented in the West. This is because Elements of emotion are essential in an animated film to generate an affective impression and emotions in the audience. Malaysia's animation industry has increased recently, and Malaysian animators have produced many animation products. However, previous studies stated that the current situation of local animated films needed a more potent storytelling technique. There is a West scholar who argues that good storytelling can evoke the emotions of the audience. Applying emotions in animation through computer technology is complicated compared to live-action films that can control emotions through the actors' acting techniques. Thus, this study identified the elements of emotion in developing the case study of storytelling Agent Ali in the movie. The mixed method was used to identify aspects of emotion in Agent Ali the Movie, such as Freytag's Pyramid model and Hume AI. As a result, this study found that aspects of emotion exist in the story development process in Agent Ali the Movie, such as happiness, sadness, and anger in every three acts of structure (exposition, conflict, and resolution). The existence of emotion has proved that animated films in Malaysia need to be focused to overcome the weak storytelling technique. At the end of the discussion, this study also found that Artificial intelligence (AI) technology like Hume AI could speed up the animation production process, especially in identifying the facial expressions and body language of characters in the process of storytelling development. [ABSTRACT FROM AUTHOR]

IoT is a very fast-growing technology. IoT can be defined as interconnected small smart devices linked over the Internet to communicate with each other to perform meaningful action. There are major concerns regarding the security of data being produced from millions of devices in the IoT system. Different security concerns in various IoT system tiers have been covered in this study. IoT security concerns can be reduced by using Blockchain Technology, which is a decentralized distributed ledger with several Blockchain potentials, including persistence, transparency, verifiability, encryption, and operationaly strong The paper reviews whether they make a good fit along with certain challenges of Blockchain that should be examined while integrating it with IoT for resolving various security issues. [ABSTRACT FROM AUTHOR]

The study analyzed the relationship of leadership to knowledge management, leadership to innovation capability, psychological security climate to knowledge management, psychological security climate to innovation capability, self-efficacy to knowledge management, self-efficacy to innovation capability, knowledge management to innovation capability. The unit of analysis was vocational teachers and principals of vocational schools. The number of teachers from the respondents education unit is 3,056 teachers. By using the Slovin formula, the minimum number of sample sizes is 354 people and the sampling technique used was simple random sampling. The data analysis technique in this study uses partial least square (PLS). The results of data processing show that leadership has a significant effect on knowledge management, leadership has a significant effect on innovation capability, psychological security climate has a significant effect on knowledge management, psychological security climate has a significant effect on innovation capability, self-efficacy has a significant effect on knowledge management, self-efficacy has a significant effect on innovation capability, knowledge management has a significant effect on innovation capability. This research contributes to improving the quality of curriculum, teachers, and graduates of vocational schools/polytechnics in the 21st century. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Babylon Center for Humanities Studies is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Internet of Things (IoT) is the amalgamation of hardware, like sensors and trackers, which monitor several parameters of the environment or physical objects, and software that processes all the data gathered by hardware. Globally, the IoT market is anticipated to reach 53.8 billion USD by 2025. This enhancing demand is due to its innate ability to automate, which drives several industries to adopt IoT. In addition, minimum memory cost, processing, and storage with an increase in Big Data (BD), cloud, and conjunction of industrial networks and the internet are the added factors for the increase in IoT development. Due to this significance, IoT has applications in numerous areas like medical management, farming, wearable technology, smart energy meters, smart cities, etc. The applications are not limited to the examples mentioned above. Considering this, existing studies have considered different applications and attempted to execute them. As different applications have been focused on by these studies, the present review intends to provide a compilation of potential applications of IoT as considered by conventional research between 2018 and 2022. The study also intends to explore the advantages and disadvantages of different IoT applications (deliberated by conventional studies) through tabular analysis. Further, this review emphasizes IoT’s major key challenges and countermeasures to resolve its security issues. Finally, the study affords recommendations that will assist all IoT experts in bringing IoT products with enhanced security into the market. [ABSTRACT FROM AUTHOR]

Background: The SARS-CoV-2 virus as well as the COVID-19 mRNA vaccines cause an increased production of proinflammatory cytokines. Aim: We investigated the relationship between ACE2, CTSL, AngII, TNFα and the serum levels of IL-6, IL-10, IL-33, IL-28A, CD40L, total IgM, IgG, IgA and absolute count of T- and B-lymphocytes in COVID-19 patients, vaccinees and healthy individuals. Methods: We measured the serum levels ACE2, AngII, CTSL, TNFα and humoral biomarkers (CD40L, IL-28A, IL-10, IL-33) by the ELISA method. Immunophenotyping of lymphocyte subpopulations was performed by flow cytometry. Total serum immunoglobulins were analyzed by the turbidimetry method. Results: The results established an increase in the total serum levels for ACE2, CTSL, AngII and TNFα by severely ill patients and vaccinated persons. The correlation analysis described a positive relationship between ACE2 and proinflammatory cytokines IL-33 (r = 0.539) and CD40L (r = 0.520), a positive relationship between AngII and CD40L (r = 0.504), as well as between AngII and IL-33 (r = 0.416), and a positive relationship between CTSL, total IgA (r = 0.437) and IL-28A (r = 0.592). Correlation analysis confirmed only two of the positive relationships between TNFα and IL-28A (r = 0.491) and CD40L (r = 0.458). Conclusions: In summary, the findings presented in this study unveil a complex web of interactions within the immune system in response to SARS-CoV-2 infection and vaccination. [ABSTRACT FROM AUTHOR]