Dravet syndrome (DS), also known as severe myoclonic epilepsy of infancy, is a rare and drug-resistant form of developmental and epileptic encephalopathies, which is both debilitating and challenging to manage, typically arising during the first year of life, with seizures often triggered by fever, infections, or vaccinations. It is characterized by frequent and prolonged seizures, developmental delays, and various other neurological and behavioral impairments. Most cases result from pathogenic mutations in the sodium voltage-gated channel alpha subunit 1 (SCN1A) gene, which encodes a critical voltage-gated sodium channel subunit involved in neuronal excitability. Precision medicine offers significant potential for improving DS diagnosis and treatment. Early genetic testing enables timely and accurate diagnosis. Advances in our understanding of DS's underlying genetic mechanisms and neurobiology have enabled the development of targeted therapies, such as gene therapy, offering more effective and less invasive treatment options for patients with DS. Targeted and gene therapies provide hope for more effective and personalized treatments. However, research into novel approaches remains in its early stages, and their clinical application remains to be seen. This review addresses the current understanding of clinical DS features, genetic involvement in DS development, and outcomes of novel DS therapies.

The variability observed in the annual seed production of perennial plants can be seen as an indication of changes in the allocation of resources between growth and reproduction, which can be attributed to fluctuations in the environment. However, a significant knowledge gap exists concerning the impacts of nitrogen addition on the interannual seed production patterns of perennial plant. We hypothesized that the addition of nitrogen would impact the annual variations in the seed production of perennial plants, ultimately affecting their overall reproductive efficiency. A multiyear field experiment was conducted to investigate the effects of varying nitrogen supply levels (e.g., 0, 4, 8 kg N ha−1 yr−1 of N0, N4, and N8) on the vegetative and floral traits, pollinator visitation rates, and seed traits over a period of four consecutive years. The results showed that the N0 treatment exhibited the highest levels of seed production and reproductive efficiency within the initial two years. In contrast, the N4 treatment displayed its highest level of performance in these metrics in the second and third years, whereas the N8 treatment showcased its most favorable outcomes in the third and fourth years. The similar patterns were found in the number of flowers per capitulum and the number of capitula per plant. There exists a positive correlation between aboveground biomass and several factors, encompassing the number of flowers per capitulum, the number of capitula per plant, the volume of nectar per capitulum, and the seed production per plant. This implies that the addition of N affected the maintenance of plant aboveground biomass, flower traits stability and, subsequently, the frequency of seed production, and the reproductive efficiency. Our results suggest that augmenting the nitrogen content in the soil may have the capacity to modify the inherent variability in seed production that is observed across various years. These findings have the potential to enhance our comprehension of the impact of nitrogen addition on the reproductive performance of perennial herbaceous plants, and the underlying mechanisms of biodiversity in the context of global environmental changes.

A novel drive current model covering the effects of source/drain voltage (VDS) and gate voltage (VGS) and incorporating drift and diffusion current on the surface channel at the nano-node level, especially beyond 28nm node is presented. The effect of the diffusion current added is more satisfactory to describe the behavior of the drive current in nano-node MOSFETs, fabricated with the atomic-layer-deposition (ALD) technology. This breakthrough in model establishment can expose the long and short channel devices together. Introducing the variables of VDS and VGS, the mixed current model more effectively and meaningfully demonstrates the drive current of MOSFETs under the operation of horizontal, vertical, or mixed electrical field. In comparison between the simulation and experimental consequences, the electrical performance is impressive. The error between both is less than 1%, better than the empirical adjustment to issue a set of drive current models.

Elevated salinity is one of the major environmental limitation factors of plant growth and development and salinity stress compromises the production and survival of plantation and urban forests and agricultural crops in the arid, semi-arid, and intertidal zones. Ulmus pumila, a salt- indigenous tree species in Asia and is widely deployed in salt-affected areas in China, and U.pumila is promising for multi-varietal forestry in plantation and urban forests. The comprehensive mechanism of the intraspecific salt tolerance is still not clear yet. Here, we investigated the physiological responses of the salinity stress based on the antioxidant enzyme activities, osmotic adjustments, and gas exchange among salt-tolerant U. pumila genotypes for 100 days under five different NaCl levels (0%, 0.3%, 0.5%, 0.7%, and 0.9% w/v) with natural surroundings and rain shade at age-2. Salt stress decreased height (HR), ground diameter (DR), and dry weight (biomass) were significantly different among genotypes. HR and performance indices were positively correlated with photosynthesis rate (Pn), apparent mesophyll conductance (AMC), and chlorophyll (CHLL) with (r= 0.7 - 0.8 ***), but were negatively related to the free proline, sugar, and protein accumulation (r=-0.5 ~ -0.7***). We found that high accumulation of sugars and more activities of SOD enzyme in leaf tissue contribute to the osmotic adjustment and ROS scavenging system under salinity treatment; the sugar content and SOD activity play key roles in U. pumila’s tolerance to salt stress, and are promising indicators for U. pumila species ex vitro selections. The ex vitro selection results align with the previous in vitro studies [37] and is promising for the MVF development.

This study employed a TSMC 0.18-µm 50 V process to establish a high-voltage n-LDMOS structure. In the reference device, the number of floating-poly (poly-2) turns was 7, and the width and spacing of each turn was 1 µm. Although increasing the number of turns reduces the peak field, directly reducing or increasing the number of poly-2 turns is a common practice. The present experiment was realized in three steps, namely fixing the number of occupied area adjustment turns, adjusting the width of each turn, and adjusting the distance between turns. The first step was fixing the number of occupied area adjustment turns. The number of turns was increased from 7 to 9, and the number of turns was reduced to 5 and 3 in the reference group. A reduction in the number of turns led to a greater decrease in the peak field and increase in the breakdown voltage despite the area remaining unchanged. A comparison of the use of three turns with that of seven turns revealed that the maximum electric field decreased by 42%, from 4.17e+3 to 2.46e+3 V/cm, and that the breakdown voltage (VBK) increased from 30.2 to 35.84 V. The second step was adjusting the width of each turn from 1 to 1.4, 1.2, 0.8, and 0.6 µm in the reference group. This increase in width reduced the maximum electric field and led to a greater increase in VBK. When the width was increased to 1.4 µm, the maximum electric field decreased by 29% from 1.95e+3 to 1.4e+3 V/cm, and the VBK increased by 183% from 30.2 to 85.6 V. The third step was adjusting the spacing of each turn from 1 to 1.4, 1.2, 0.8, and 0.6 µm in the reference group. The results revealed that a reduction in the spacing led to a greater reduction in the maximum electric field and an in-crease in the VBK. When the pitch was reduced to 0.6 µm, the maximum electric field decreased by 33%, from 1.95e+3 to 1.32e+3 V/cm, and the VBK increased by 345%, from 30.2 to 134.4 V.

Detailed kinetics for a 3-wavelength photopolymerization confinement (PC) system is presented for both numerical solutions and analytic formulas. The dynamic profiles are simulated for oxygen, free radical, and conversion for various situations of: blue-light only, 2-light (red and UV), and 3-light (red, blue, UV). An effective PC requires two conditions: (i) a strong N-inhibition for uncured regime with a low conversion (triggered by the UV-light); and (ii) a weak S-inhibition (oxygen-induced) for high conversion under the blue-light or blue and red-light initiation. Good PC candidates are governed by collective factors of: (i) the double ratio of light-intensity and initiator-concentration, (ii) monomers rate-constant; and (iii) effective absorption constants at specific wavelength and initiators. A new reverse feature for the role of N-inhibition on the blue-conversion is found. Higher oxygen concentration leads to a lower conversion, which could be enhanced by reducing the S-inhibition via a red or blue-light pre-irradiation, having a pre-irradiation time TP=200 s for red-light only, and reduced to 150 s, when both red and blue-light. System under UV-only leads a conversion lower than that of blue-only. However, conversion could be improved by the dual-light (blue and UV), and further enhanced by the pre-irradiation of red-light. The two competing factors, N-inhibition and S-inhibition, could be independently and selectively tailored to achieve: (a) high conversion of blue-light (without UV-light), enhanced by red-light pre-irradiation for minimal S-inhibition; and (b) efficient PC initiated by UV-light produced N-inhibition for reduced confinement thickness and for high print speed.

The process of preparing anti-glare thin films by spray-coating silica sol-gel to soda-lime glass was exclusively and statistically studied in this paper. The effects of sol-gel deliver pressure, air transport pressure, and spray gun displacement speed on the gloss, haze, arithmetic mean surface roughness, and total transmittance light were analyzed. The experimental results indicate that the factors of sol-gel deliver pressure, air transport pressure, and displacement speed exhibit significant effect on the haze, gloss, and Ra. In contrast, the variation of total transmittance light with these three factors are insignificant. Because the anti-glare property is predominantly determined by low gloss and high haze, therefore, we aim to minimize gloss and maximize haze to achieve high anti-glare. Central composite design and response rurface methodology are employed to analyze the main and interaction effects of the three factors through quadratic polynomial equations, which are confirmed by the analysis of variance and R². The response surface methodology predict the lowest gloss and highest haze are 9.2 GU and 57.0%, corresponding to the sol-gel deliver pressure, air-transport pressure, and displacement speed of 250 kPa, 560 kPa, and 140 mm/s, and 340 kPa, 620 kPa, and 20 mm/s, respectively. Comparing the predicted optimal data with the real experimental results validates the applicability of the mathematical model. This study provides an important basis for the subsequent production of anti-glare glass with different specifications to satisfy the market demand.

The kinetics and efficacy profiles of photoinitiated polymerization are theoretically presented. For the same dose, lower light intensity achieves a higher steady-state-efficacy (SSE) in type-I; in contrast, type-II has an equal SSE. Higher light intensity has a faster rising efficacy, due to faster depletion of photoinitiator (PS) concentration. However, type-II process is also affected by the available oxygen. Higher light intensity produces more efficient singlet oxygen, resulting a higher transient efficacy, in which all intensities reach the same SSE when oxygen is completely depleted. With external oxygen, type-II efficacy increases with time, otherwise, it is governed only by the light dose, i.e., same dose achieves same efficacy. Moreover, type-II has an efficacy follows Bunsen Roscoe law (BRL), whereas type-I follows non-BRL. The measured type-I efficacy and gelation profile are analyzed by our analytic formulas. Schematics of the photocrosslinking stage defined by the availability of oxygen is developed, where both type-I and –II coexist until the oxygen is depleted. The overall efficacy may be enhanced by resupply of PS or oxygen during the light exposure. The roles of light dose and PS concentration on the efficacy of photoinitiated polymerization should be are governed a new concept of a volume efficacy (Ve), defined by the product of the crosslink (or gelation) depth (CD) and local [efficacy].

Optimal conditions for maximum efficacy of photoinitiated polymerization are theoretically presented. Analytic formulas are shown for the crosslink time, crosslink depth and efficacy function. The roles of photoinitiator (PI) concentration, diffusion depth and light intensity on the polymerization spatial and temporal profiles, for both uniform and non-uniform cases, are presented. For optimal efficacy, a strategy via controlled PI concentration is proposed, where re-supply of PI in high light intensity may achieve a combined-efficacy similar to low light intensity, but has a much faster procedure. A new criterion of efficacy based on the polymerization (crosslink) [strength] and [depth] is introduced. Experimental data are analyzed for the role of PI concentration and light intensity on the gelation time and efficacy.

The kinetics and modeling of dual-wavelength controlled photopolymerization confinement (PC) are presented and measured data are analyzed by analytic formulas and numerical data. The UV-light initiated inhibition effect is strongly monomer-dependent and different monomers have different C=C bond rate constants and conversion efficacy. Without the UV-light, for a given blue-light intensity, higher initiator concentration (C₁₀) and rate constant (k’) lead to higher conversion, as also predicted by analytic formulas, in which the total conversion rate (R_T) is an increasing function of k’R, which is proportional to k[gB₁C₁]^0.5. However, the coupling factor b₁ plays a different role that higher b₁ leads to higher conversion only in the transient regime; whereas higher b₁ leads lower steady-state conversion. For a fixed initiator concentration C₁₀, higher inhibitor concentration (C₂₀) leads to lower conversion due to stronger inhibition effect. However, same conversion reduction was found for the same H-factor of H₀ = [b₁C₁₀ - b₂C₂₀]. Conversion of blue-only are much higher than that of UV-only and UV-blue combined, in which high C₂₀ results a strong reduction of blue-only-conversion, such that the UV-light serves as the turn-off (trigger) mechanism for the purpose of spatial confirmation within the overlap area of UV and blue light. For example, UV-light controlled methacrylate conversion of a glycidyl dimethacrylate resin formulated with a tertiary amine co-initiator, and butyl nitrite, subject to a continuous exposure of a blue light, but an on-off exposure of a UV-light. Finally, we developed a theoretical new finding for the criterion of a good material/candidate governed by a double ratio of light-intensity and concentration, [I₂₀C₂₀.]/[I₁₀C₁₀].

Objective biomarkers have been a critical challenge for the field of psychiatry, where diagnostic, prognostic and theranostics assessments are still based on subjective narratives. Psychopathology operates with idiographic knowledge and subjective evaluations incorporated into clinical as-sessment inventories, but is considered to be a medical discipline and, as such, uses medical in-tervention methods (e.g., pharmacological, ECT; rTMS; tDCS), and therefore is supposed to oper-ate with the language and methods of nomothetic networks. The idiographic assessments are pro-visionally “quantified” into “structured clinical scales” to in some way resemble nomothetic measures. Instead of fostering data merging and integration, this approach further encapsulates the clinical psychiatric methods, as all other, biological tests (molecular, neuroimaging) are per-formed separately, only after the clinical assessment has provided diagnosis. Translational cross-validation of clinical assessment instruments and fMRI is an attempt to address the gap. The aim of this approach is to investigate whether there exist common and specific neural circuits, which underpin differential item responses to clinical self-rating scales during fMRI session in pa-tients suffering from the two main spectra of mental disorders: schizophrenia and major depres-sion. The current status of this research program and future implications to promote the devel-opment of psychiatry as a medical discipline are discussed.

This study proposes an image recognition method to assist swine farm managers in collecting health data related to pig feeding and excretion. Analyzing the correlation between sow health data and indoor air quality in the pigsties revealed significant influences of air quality indicators on sow health. Increased levels of TVOC, CO2, and temperature were found to negatively affect feeding health, while increased temperature, humidity, and PM10 were found to negatively impact excretion health. These findings provide a basis for evaluating variables when constructing future sow disease prediction models. Analyzing the correlation between pig health status and air quality can help swine farm managers improve sow production environments, reduce disease risks, enhance production efficiency, and provide valuable insights for future research on disease prediction models.

This study evaluated the mechanical strengths of three types of orthodontic micro-implants by analyzing their structural configurations. Thirty micro-implants of three types (diameter 1.5 mm, Types A, B, C) were assessed. All micro-implants were manually driven into artificial bones at an 8-mm depth. The insertion torque (IT), pullout strength (PS), and gripping volume (GV) of each type were measured. Intergroup comparisons and intragroup correlation were investigated by statistical analysis. Type B had the greatest inner–outer diameter ratio (0.67), and Type A had the smallest (0.53). The IT of Type A (5.26 Ncm) was significantly (p = 0.038) lower than that of Type C (8.8 Ncm). There was no significant difference in the pullout strength (p = 0.868). The GV of Type A (9.7 mm3) was significant (p < 0.01) greater than Type C (8.4 mm3). Type C was significant (p < 0.01) greater than Type B (7.2 mm3). Spearman’s rho rank correlation test showed that PS of Type B was correlated significantly with GV. In conclusion, the design of thread and its GV were the important factors on the mechanical strengths of micro-implant.

Due to the fact that abrasive media can deform flexibly in abrasive flow machining (AFM) making this method easily to polish the complex holes and the curved surface of the hard machining shapes. Although abrasive media dominate the polishing behavior in AFM process, the mechanism of the abrasive media are not easy to understand because of the high viscous gels, therefore, many finishing works need lots of time to design AFM process. Power laws of the abrasive gels is studied here to evaluate the non-Newtonian flow of abrasive gels in complex holes polishing firstly, at the mean time different abrasive gels are utilized to finish the complex holes to follow the results by non-Newtonian flow calculation. Moreover, traditional AFM has difficulty to achieve a uniform roughness of radial distribution in the complex holes polishing because of the non-uniform abrasive forces. So a helical passageway is proposed to create a multiple motion of abrasive medium and to obtain the even surface of the complex holes in AFM process.

Underwater visual detection technology plays a pivotal role in fields such as marine exploration. With the increasing demand for underwater monitoring, the quest for efficient and reliable methods for underwater target recognition has become particularly significant. To address this requirement, this study developed an innovative underwater object detection architecture based on YOLOv8, named YOLOv8-MU, aimed at significantly enhancing detection accuracy.By integrating the LarK module proposed in UniRepLKNet to optimize the backbone network, YOLOv8-MU aims to achieve a larger receptive field without increasing the model’s depth. Further, this research introduces C2fSTR, an innovative method that combines Swin Transformer with the C2f module. Additionally, we have incorporated the SPPFCSPC_EMA module, which combines Cross-Stage Partial Fast Spatial Pyramid Pooling (SPPFCSPC) with attention mechanisms, significantly improving the detection accuracy and robustness of various biological targets. Moreover, by introducing a fusion block based on DAMO-YOLO into the neck of the model, we further enhanced the model’s capability in multi-scale feature extraction. Finally, the adoption of the MPDIoU loss function, designed around vertex distance, effectively tackles the challenges of localization accuracy and boundary clarity in underwater organism detection. Experimental results on the URPC2019 dataset demonstrate that the YOLOv8-MU model achieved an [email protected] of 78.4%, marking improvements of 5.6%, 1.1%, and 4.0% over YOLOv5s, YOLOv7, and YOLOv8n respectively, indicating the leading performance (SOTA) of this method. On the other hand, further evaluation on the URPC2020 dataset confirmed the generalization capability of the YOLOv8-MU architecture, with its [email protected] reaching 80.4%, surpassing various models including YOLOv5x and YOLOv8n, showcasing the wide applicability of our proposed improved model architecture.

Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide. A growing body of evidence suggests that mitochondrial dysfunction and inflammation plays a crucial role as a pathogenetic mechanism in PD. The aim of the present study was to investigate the metabolic profile of PBMCs from PD patients and to search for a possible relationship be-tween cellular bioenergetics and YKL-40. Materials and methods: The study included 18 naïve PD and an age-matched control group (HC, n=7). Patients were diagnosed according to the MDS-PD, the UPDRS and the Hoen–Yahr scales. Mitochondrial activity was measured by a metabolic analyzer on isolated PBMCs from PD’s patients. Gene (qPCR) and protein (ELISA) expression levels of YKL40 were investigated. Results: New data are reported revealing changes in mito-chondrial activity and YKL-40 levels in PD patients. Bioenergetic parameters showed increased respiratory reserve capacity in the PD compared to HC. The protein levels of YKL-40 were three-fold higher in PD. We found a correlation between YKL-40 protein levels and basal respiration and between YKL-40 and ATP production. Conclusion: These observations suggest an interplay between YKL-40 and mitochondrial function in PD. We assume that YKL-40 gene and protein levels in combination with changes in mitochondrial function might serve as an additional tool to monitor the clinical course of PD.

Information is uploaded and downloaded through the Internet day in and day out ever since we immersed ourselves in the Internet. Data security becomes an area demanding high attention and one of the efficient techniques to protect data is data hiding. Among various data hiding schemes, more applications prefer the schemes with reversibility. In recent reversible data hiding studies, the indices of a codebook can be reordered to hide secret bits. The hiding capacity of the codeword index reordering scheme increases when the size of the codebook gets larger. Since the codewords in the codebook are not modified, the visual performance of compressed images is retained. We propose a novel scheme making use of the fundamental principle of codeword index reordering technique to hide secret data in encrypted images. By observing our experimental results, the embedding capacity is significantly larger. Secret data can be extracted when a receiver owns a data hiding key and image can be recovered when a receiver owns an encryption key.

Bone Scan Index (BSI) is an image biomarker for quantification on bone metastasis of cancers. To compute BSI, not only the hotspots (metastasis) but also the bones have to be segmented. Most related researches focus on binary classification on bone scintigraphy: having metastasis or none. Rare studies focus on pixelwise segmentation. In this study we compare three advanced convolutional neural network (CNN) based models to explore the bone segmentation on dataset in house. The best model is Mask R-CNN, which reaches the precision, sensitivity and F1-score: 0.93, 0.87, 0.90 for prostate cancer patients and 0.92, 0.86, 0.88 for breast cancer patients, respectively. The results are the average of 10-fold cross-validation, which reveals the reliability for clinical use on bone segmentation.

Improvement in medical care has turned severe diseases into chronic conditions, but often their treatment and use of medical devices are related to specific complications. Here we present a clinical case of a long-term dialysis patient, who is infected with a rare opportunistic infectious agent – Gordonia sputi. In recent years the incidence of Gordonia spp. infections in immunocompromised patients with central venous catheters (CVC) appear to rise. Their isolation and identification are challenging and require modern techniques. In addition, the treatment is usually persistent and often results in CVC extraction, which is associated with further risk and costs for the patient. We also studied the alternations in the immune status of the patient caused by long-term renal replacement therapy and persistent HCV infection. Antibiotic therapy and immunostimulation with Inosine pranobex lead to successful eradication of the infection without the need for CVC replacement.

This study was conducted to examine whether there are quantitative or qualitative differences in the connectome between psychiatric patients and healthy controls and to delineate the connectome features of major depressive disorder (MDD), schizophrenia (SCZ), bipolar disorder (BD) and the severity of these disorders. Toward this end, we have performed effective connectivity analysis of resting state functional MRI data in these three patient groups and healthy controls. We have used spectral Dynamic Causal Modeling (spDCM), and the derived connectome features were further subjected to machine learning. The results outlined a model of 5 connections, which discriminate patients from controls, comprising major nodes of the limbic system (amygdala (AMY), hippocampus (HPC) and anterior cingulate cortex (ACC)), the salience network (anterior insula (AI), fronto-parietal and dorsal attention network (middle frontal gyrus (MFG) corresponding to dorsolateral prefrontal cortex, frontal eye field (FEF)). Notably, the alterations in the self-inhibitory connection of the anterior insula emerged as a feature of both mood disorders and SCZ. Moreover, 4 out of the 5 connectome features that discriminate mental illness from controls are features of mood disorders (both MDD and BD), namely the MFG→FEF, HPC→FEF, AI→AMY, and MFG→AMY connections, whereas one connection is a feature of SCZ, namely the AMY→SPL connectivity. A large part of the variance in the severity of depression (31.6%) and SCZ (40.6%) was explained by connectivity features. In conclusion, dysfunctions in the self-regulation of the salience network may underpin major mental disorders, while other key connectome features shape differences between mood disorders and SCZ, and can be used as potential imaging biomarkers.

Europium (Eu)-doped fluorapatite (FA) nanorods has a similar biocompatibility with hydroxyapatite (HA) in terms, attracted much attention as cell imaging biomaterials due to their luminescent property. Here, we will discuss the new feature of europium doped fluorapatite (Eu-FA) nanorods as anticancer drug carrier. Eu-FA nanorods was prepared using a hydrothermal method. The morphology, crystal structure, fluorescence and composition are investigated. The specific crystal structure, enabling an effective loading of drug molecules. Doxorubicin (DOX), used as an anticancer model drug, was shown to be effectively loaded onto the surface of the nanorods. The DOX release was fairly pH-dependent, occurring more rapidly at pH 5.5 than pH 7.4 was observed. The intracellular penetration of the DOX-loaded Eu-FA nanorods (Eu-FA/DOX) can be imaged in situ due to the self-fluorescence property. Treatment of melanoma A375 cells with Eu-FA/DOX elicited a more effective apoptosis rate than direct DOX treatment. Overall, Eu-FA show great promise for tracking and treating tumor, may potentially useful as a multifunctional carrier system to effectively load and sustainably deliver drugs.

Lung cancer (LC) stands as the foremost cause of cancer-related fatality rates worldwide. Early diagnosis significantly enhances patient survival rate. Nowadays, low dose computed tomography (LDCT) is widely employed on chest as a tool for large-scale lung cancer screening. Nonetheless, a large amount of chest radiographs causes an onerous burden on radiologists. Some computer-aided diagnostic (CAD) tools can provide insights to medical images for diagnosis and augmenting diagnostic speed. However, due to variation in parameter settings across different patients, substantial discrepancies in image voxels persist. We find different voxel-size causing a compromise between model generalization and diagnostic efficacy. This study investigates the performance disparities of diagnostic models trained on original images and LDCT images reconstructed to different voxel-sizes but isotropic. The application is to differentiate a nodule to be benign or malignant. Using 11 features, a support vector machine (SVM) is trained on LDCT images with an isotropic voxel having side-length of 1.5 mm for 225 patients in house. The result yields a favorable model performance with an accuracy of 0.9596 and an area under the receiver operating characteristic curve (ROC/AUC) of 0.9855. In addition to furnish CAD tools for clinical applications, future research is encouraged to include LDCT images from multi-centers.

The immunization of healthcare workers in the early stages of the rollout of COVID-19 vaccines was prioritized in order to ensure uninterrupted medical care provision. At the same time the increasing number of available COVID-19 vaccines may trigger hesitancy towards the decision to get vaccinated. Thus, accumulating reliable information on the adverse events following immunization may educate and urge the general population to receive a COVID-19 vaccine. The present study aimed to evaluate the adverse events (AEs) following immunization with any of the available COVID-19 vaccine among Bulgarian healthcare workers (HCWs). A cross-sectional study among HCWs in Plovdiv, Bulgaria was conducted in the period March – September 2021. Through a semi-structured online questionnaire, the participants reported the adverse events following the administration of the first and second dose of a COVID-19 vaccine. A total of 253 respondents, vaccinated with one of the available vaccines against COVID-19 took part in the study. Of them 71.9% were females, and 75.9% received mRNA-based vaccines, while 24.1% received a viral-vector based vaccine. Overall 91.6% and 82.6% of all participants reported at least one local AE after the first and second dose of a COVID-19 vaccine. The share of respondents reporting at least one systemic AE after the first and second dose of a COVID-19 vaccine was 59.7% and 62.4% respectively. The most common local AE was pain at the injection spot (84.0%), while the most common systemic AEs were fatigue (54.9%), chills (43.2%), and headache (41.7%). The mRNA-based vaccines versions seem to cause higher prevalence of local AEs, while the vector-based vaccines were linked with increased prevalence of systemic AEs. Female HCWs and the younger age group were associated with an increased risk of adverse events generally. Our results added more evidence that mRNA-based and viral-vector based vaccines are generally safe. The reported adverse events were mild, although they occurred in a high share of the respondents. No serious AEs attributable to the vaccines were reported.

Photothermal therapy (PTT) can overcome cancer treatment resistance by enhancing cell membrane permeability, facilitating drug accumulation, and promoting drug release within the tumor tissue. Iron oxide nanoparticles (IONPs) have emerged as effective agents for PTT due to their unique properties and biocompatibility. Approved for the treatment of anemia, as MRI contrast agents, and as magnetic hyperthermia mediators, IONPs also offer excellent light-to-heat conversion and can be manipulated using external magnetic field for targeted accumulation in specific tissues. Optimizing parameters such as laser wavelength, power density, shape, size, iron oxidation state, functionalization, and concentration is crucial for IONPs effectiveness. In addition to PTT, IONPs enhance other cancer treatment modalities. They improve tumor oxygenation enhancing the efficacy of radiotherapy and photodynamic therapy. IONPs can also trigger ferroptosis, a programmed cell death pathway mediated by iron-dependent lipid peroxidation. Their magneto-mechanical effect can exert mechanical force on cancer cells to destroy tumors, minimizing damage to healthy tissues. This review outlines strategies for managing photothermal performance and PTT efficiency with iron oxide nanoparticles, as well as synergies with other cancer therapies.

We constructed a novel design integrating the administration of a clinical self-assessment scale with simultaneous acquisition of functional Magnetic Resonance Imaging (fMRI), aiming at cross-validation between psychopathology evaluation and neuroimaging techniques. We hypothesized that areas demonstrating differential activation in two groups of patients (paranoid and depressive) will have distinct connectivity patterns and structural differences.

We give a simple proof of the Chen inequality for the Chen invariant $\underbrace{\delta (2,...,2)}_{k\mbox{ terms}}$ of submanifolds in Riemannian space forms.

The booming wearable market and recent advances in material science has led to the rapid development of the various wearable sensors, actuators, and devices that can be worn, embedded in fabric or accessories, or tattoos directly onto the skin. Wearable actuators, a subcategory of wearable technology, have attracted enormous interest from researchers in various disciplines and many wearable actuators and devices have been developed in the past few decades to assist and improve people's everyday lives. In this paper, we review the actuation mechanisms, structures, applications, and limitations of recently developed wearable actuators including pneumatic and hydraulic actuators, shape memory alloys and polymers, thermal and hygroscopic materials, dielectric elastomers, ionic and conducting polymers, piezoelectric actuators, electromagnetic actuators, liquid crystal elastomers, etc. Examples of the recent applications such as wearable soft robots, haptic devices, and personal thermal regulation textiles are highlighted. Finally, we point out the current bottleneck and suggest the prospective future research directions for wearable actuators.

The aim of this study is to introduce and evaluate a new approach by using 3D printed anthropomorphic breast phantoms in teaching X-ray mammography techniques Radiologic technologists. For this purpose, a physical anthropomorphic breast phantom is created, based on a computational breast version. The phantom is created by a stereolithography 3D printer. The practical exercises were conducted in three sessions with the participation of radiographers students first, second and third year of training, respectively. A survey was prepared to summarise the participants´ opinion about this new form of training in mammography technique. A total of 83 students were trained with the new approach. From these 52 responded to the survey questions. More than half of the students (71.2%) successfully handled the exercise with the physical breast phantom. The training provoked a substantial number of students to express the belief that incorporating modern methods based on digital technologies into their X-ray device training is essential. The instructor was well prepared and with the needed competence. The experience within this training convinces the future professionals to introduce the new technologies in their routine work, particularly for exercising the compression technique and breast positioning.

This study explored the potential synergism within chlorhexidine-silver nanoparticles conjugates against Influenza type A, Staphylococcus aureus, Escherichia coli, and Candida albicans. Silver nanoparticles (SN) were obtained by the reduction of silver ions with green tea total phenolic extract and conjugated with chlorhexidine (Cx). The particles were characterized by UV-Vis and FTIR spectroscopies, dynamic light scattering, X-ray diffraction, and transmission electron microscopy. A stable negatively-charged nano-silver colloid (ζ=-50.01) was obtained with an average hydrodynamic diameter of 92.34 nm. In the presence of chlorhexidine, the spectral data and the shift of the zeta potential to positive values (ζ=+44.59) revealed the successful sorption of the drug onto the silver surface. The conjugates (SN-Cx) demonstrated potentiation in the effects against S. aureus and C. albicans, and synergism against E. coli with minimal inhibitory concentrations of SN 5.5 µg/mL+Cx 8.8 µg/mL. The SN showed excellent, increasing with time, virucidal properties, and low toxicity. The coupling of the cationic chlorhexidine with nano-silver, however, did not reduce its intrinsic cytotoxicity on various cell lines (MDCK, BJ, and А549). The newly-synthesized antimicrobial agent presented with an extended and promising therapeutic spectrum and needs to be further evaluated on relevant to the designated route of administration three-dimensional cell models (e.g., nasal, bronchial, dermal, ocular, etc.).

This study presents a novel approach to analyzing the present value of total profit for non-participating and participating insurance policies in order to determine the optimal profitability of non-participating and participating insurance policies based on applying the approach used in operations research to the field of finance. As such, a comprehensive insurance product evaluation model was developed using both mathematical models and numerical analysis to evaluate the demand for non-participating and participating life insurance policies in response to changes in interest rates. The findings indicate that non-participating life insurance policies offer greater solvency for insurance companies compared to participating policies. The study also highlights the significance of spontaneous and induced demand in determining the total profit of both types of policies. The study concludes that life insurance companies should focus on generating spontaneous consumer demand, reducing induced demand, and implementing the optimal pricing strategy to achieve maximum profits.

Analyzing synovial fluid from joints affected by the pathological process of psoriatic arthritis is part of the overall patient examination, since it may have differential diagnostic significance. The purpose of this study was to assess the presence of crystals in the synovial fluid of psoriatic arthritis patients as biomarkers for disease activity. Materials and methods: The synovial fluid of 156 patients with proven PSA diagnosis (patients covered CASPAR criteria) was analyzed over 24 months and compared to 50 patients with activated gonarthrosis. The Leica DM4500P polarization microscope (Leica Microsystems, Germany) was used for crystal detection. Pain and disease activity measures were also evaluated (PSA VAS for pain, DAPSA, PASDAI, mCPDAI, and HAQ-DI). The statistical analysis was carried out using SPSS version 26 with a significance set at p < 0.05. Results: The macroscopic appearance of synovial fluid from patients with psoriatic arthritis was clear in 84.6% of the patients. Synovial fluid crystals were found in 23.71% of patients with psoriatic arthritis - predominantly monosodium urate (67.58%) but also calcium pyrophosphate (21.62%) and lipid drops (5.4%). The presence of monosodium urate crystals significantly correlates with all pain and disease activity measures – VAS for pain, DAPSA, PASDAI, mCPDAI, and HAQ-DI. In 67.56% of patients with established crystals treatment with an anti-TNF blocker was started at the discretion of the treating rheumatologist due to high levels of disease activity. Conclusion: Examining the synovial fluid in PSA patients is a necessary minimally invasive procedure in cases of joint effusion, since the presence of synovial fluid crystals is a significant indicator of disease severity. The current analyses demonstrate that the presence of synovial fluid crystals in PSA patients can be used as a biomarker for disease severity and the necessity to commence biological treatment (most often TNF-a-blocker).

In order to overcome this problem our group designed a novel machine learning technique, multivariate linear method (MLM) which can capture convergent data from voxel-based morphometry, functional resting state and task-related neuroimaging and the relevant clinical measures. In this paper we report results from convergent cross-validation of biological signatures of disease in a sample of patients with schizophrenia as compared to depression. Our model provides evidence that the combination of the neuroimaging and clinical data in MLM analysis can inform the differential diagnosis in terms of incremental validity to reach 90 % accuracy of the prediction.

Earliest critical context of the pandemic, preceding the first real epidemiological wave of contagion in Bulgaria, was examined in a socio-affective perspective. A retrospective and agnostic analytical approach was adopted. Our goal was to identify traits and trends that explain public health support (PHS) of Bulgarians during the first two months of the declared state of emergency. We investigated a set of variables with a unified method within an international scientific network, named International Collaboration on Social &amp; Moral Psychology of COVID-19 (ICSMP) in April and May 2020. Conspiracy Theories beliefs were a significant predictor of lower PHS. Psychological Well-being was significantly associated with Physical Contact and Anti-Corona Policy Support. Physical Contact was significantly predicted by less Conspiracy Theories beliefs, higher Collective Narcissism, Open-mindedness, higher Trait Self-Control, Moral Identity, Risk Perception, and Psychological Well-Being. Physical Hygiene compliance was predicted by less Conspiracy Theories beliefs, Collective Narcissism, Morality-as-Cooperation, Moral Identity, and Psychological Well-Being. Results revealed two polar trends of support and non-support of public health policies. The contribution of this study is in providing evidence for affective polarization and phenomenology of (non)precarity during the outbreak of the pandemic.

This study aimed to evaluate the early-childhood comorbidities of cerebral palsy (CP) in children with low birth weight (LBW) and assess the impact of maternal bio-psychosocial factors on the risk of CP in preterm infants across varying birth weights. Data for 15,181 prematurely born infants from 2009 to 2013 and 151,810 matched controls from Taiwan's National Health Insurance Research Database were analyzed. Period prevalence of CP, and comorbidities of LBW were verified, and odds ratios (ORs) were calculated. Results confirmed that increasing prematurity and low birth weight (LBW) rates in Taiwan. LBW was associated with higher CP prevalence. Maternal age extremes (&lt;20 and &gt;40 years) were significant risk factors of CP in LBW infants. LBW infants showed higher risks of respiratory, circulatory, and nervous system and psycho-developmental comorbidities compared to controls. Infants with the lowest birth weights had even higher ORs for these comorbidities. However, gastrointestinal and nutritional comorbidities were less prevalent in premature infants. Maternal factors such as family income, number of hospital admissions, and length of hospital stay were significantly correlated with birth weight and subsequent complications. Each additional gestational week significantly reduced the risk of complications in premature infants. Additionally, maternal bio-psychosocial factors were associated with birth weight and related outcomes in premature infants, emphasizing the importance of addressing these factors in prenatal care and interventions.

The Chen circuit system, a three-dimensional autonomous system with intriguing dynamics, has gained considerable attention due to its potential applications in diverse scientific fields. In this article, a Chen circuit-like system is defined and a comprehensive dynamics has been studied. The system exhibits chaotic dynamics, limit cycles, and bifurcations, making it a captivating subject of study. By employing numerical simulations and analytical techniques, we explore the system's stability and identify critical parameter values leading to qualitative changes. Notably, we delve Hopf bifurcations, which give rise to stability changes and the emergence of limit cycles. Furthermore, we analyze the fractal dimension of the system's attractor, providing insights into its complexity and self-similarity. Through a systematic examination of the Chen circuit-like system, we deepen our understanding of its intricate dynamics and offer valuable insights into the underlying mechanisms. The findings contribute to the field of dynamical systems and hold potential implications in areas such as chaos-based secure communications, signal processing, and nonlinear control. This work serves as a valuable reference for researchers and practitioners interested in the dynamics and bifurcation analysis of nonlinear systems.

We have used Mass Multivariate Method on structural, resting state and task related fMRI data from two groups of patients with schizophrenia and depression, respectively, in order to define several regions of significant relevance to the differential diagnosis between those conditions. The regions included the left Planum polare, Left opercular part of the inferior frontal gyrus (OpIFG), Medial orbital gyrus (MOrG), Posterior Insula (PIns), and Parahippocampal gyrus (PHG). This study delivers evidence that multimodal neuroimaging approach can potentially enhance the validity of psychiatric diagnosis. Either structural, or resting state or task related functional MRI modality cannot provide independent biomarkers. Further studies need to consider and implement a model of incremental validity to combine clinical measures with different neuroimaging modalities to discriminate depressive disorders from schizophrenia. Biological signatures of disease on the level of neuroimaging are more likely to underpin broader nosological entities in psychiatry.

Accurate segmentation of the Left Ventricle (LV) in Echocardiogram (Echo) images is essential for cardiovascular analysis. Conventional techniques are labor-intensive and exhibit inter-observer variability. Deep learning has emerged as a powerful tool for automated medical image segmentation, offering advantages in speed and potentially superior accuracy. This study explores the efficacy of employing the YOLO (You Only Look Once) segmentation model for automated LV segmentation in Echo images. YOLO, a cutting-edge object detection model, achieves exceptional speed-accuracy balance through its well-designed architecture. It utilizes efficient dilated convolutional layers and bottleneck blocks for feature extraction, while incorporating innovations like path aggregation and spatial attention mechanisms. These attributes make YOLO a compelling candidate for adaptation to LV segmentation in Echo images. We posit that by fine-tuning a pre-trained YOLO based model on a well-annotated Echo image dataset, we can leverage the model's strengths in real-time processing and precise object localization to achieve robust LV segmentation. The proposed approach entails fine-tuning a pre-trained YOLO model on a rigorously labeled Echo image dataset. Model performance has been evaluated using established metrics such as mean Average Precision (mAP) at an Intersection over Union (IoU) threshold of 50% (mAP50) with 98.31%and across a range of IoU thresholds from 50% to 95% (mAP50:95) with 75.27%. Successful implementation of YOLO for LV segmentation has the potential to significantly expedite and standardize Echo image analysis. This advancement could translate to improved clinical decision-making and enhanced patient care.

This study aimed to investigate the efficacy of probiotics in elderly hospitalized tube-fed patients undergoing antibiotic therapy for Clostridium difficile-associated diarrhea (CDAD). Probiotics were administered to 29 patients, with twice-daily doses for 7 days following the completion of antibiotic treatment. In the probiotic group, while stool form showed no significant change, there was a significant decrease in stool frequency. Conversely, the control group exhibited improved stool form but not frequency. The probiotic group maintained a significant difference in stool form during the follow-up period. Additionally, the control group showed a positive correlation between stool form, frequency, antibiotic therapy, and intensive care unit admission, which was not observed in the probiotic group. These findings suggest that supplementing with probiotics can effectively normalize stool form in elderly hospitalized tube-fed patients undergoing antibiotic treatment for CDAD, highlighting the potential benefits of probiotic intervention in this specific population.

The time when a patient has mild cognitive impairment (MCI) is an important period for delaying the onset of dementia and has been the main target of dementia prevention research in recent years. The purpose of this study was to investigate the dietary intake and dietary patterns of MCI patients in Taiwan. In total, 40 subjects were enrolled in this cross-sectional study that was conducted from July 2019 to September 2021 at Linkou Chang Gung Memorial Hospital. Results of the clinical dementia rating (CDR) and mini-mental state examination (MMSE) were obtained from medical records. Participants were divided into two groups: a healthy group (MMSE ≥ 26 points, CDR=0) and an MCI group (MMSE ≥ 26 points, CDR=0.5). Results indicated that the MCI group had significantly higher copper and lower low-fat meat intake compared to the healthy group. Furthermore, the high MIND (Mediterranean-dietary approaches to stop hypertension intervention for neurodegenerative delay) diet score represented a lower risk of MCI. After adjusting for age and gender in the multivariate regression analysis, calcium and fruit intake levels were positively associated with the MMSE. In conclusion, the prevalence of MCI was closely associated with dietary intake, such as copper and calcium, as well as dietary patterns, particularly the MIND diet.

Bone metastasis detection and quantification on bone scintigraphy is challenging and clinical important for treatment and patient’s life quality. To develop a CNN based diagnostic system for automated segmentation on bone metastasis regions is non-trivial, especially for a small dataset. A dataset in house comprising 100 breast cancer patients and 100 prostate cancer patients is utilized for this research. The Double U-Net model is adapted through the integration of background removal, adding negative samples, and transfer learning methods for bone metastasis detection. The performance is investigated via 10-fold cross-validation and computed in pixel-wise scale. The best model we achieved has precision of 63.08%, sensitivity of 70.82%, and F1-score of 66.72%. The developed system has the potential to provide pre-diagnostic reports for physicians in final decisions and the calculation of the bone scan index (BSI) with the combination with bone skeleton segmentation.

Background: We aimed to evaluate the effect of early pelvic binder use in emergency management of suspected pelvic trauma, compared with the conventional stepwise approach. Methods: We enrolled trauma patients with initial stabilization using a pelvic binder for suspecting pelvic injury. Inclusion criteria were traumatic injury requiring a trauma team and at least one of the following: loss of consciousness or Glasgow coma score (GCS) < 13; systolic blood pressure < 90 mmHg; falling from ≥6 m; injury to multiple vital organs; and suspected pelvic injury. Various parameters, including gender, age, mechanism of injury, GCS, mortality, hospital stay, initial vital sign, revised trauma score, injury severity score, and outcome, were assessed and compared with historical controls. Results: A total of 204 patients with high-energy multiple-trauma from single level I trauma center in North Taiwan were enrolled in the study from August 2013 to July 2014. The two group baseline patient characteristics were all collected and compared. The trauma patients with suspected pelvic fractures initially stabilized with a pelvic binder had shorter hospital and ICU stays. The study group achieved statistically significantly improved survival and lower mean blood transfusion volume and mortality rate although they were more severe in the trauma score. Conclusions: We recommend prompt pelvic binder use for suspected pelvic injury before definitive imaging is available, as a cervical spine collar is used to protect the cervical spine from further injury prior to definitive identification and characterization of an injury.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the novel coronavirus responsible for the coronavirus disease 2019 (COVID-19) pandemic, represents a serious threat to public health. The spike (S) glycoprotein of SARS-CoV-2 mediates viral entry into host cells and is heavily glycosylated. In this study, we systemically analyzed the roles of 22 putative N-linked glycans in SARS-CoV-2 S protein expression, membrane fusion, viral entry, and stability. Using α-glycosidase inhibitors, castanospermine and NB-DNJ, we confirmed that disrupting the N-linked glycosylation process blocked the maturation of the S protein, leading to impairment of S protein-mediated membrane fusion. Single substitution of each of the 22 N-linked glycosylation sites with glutamine revealed that 9 out of the 22 N-linked glycosylation sites were critical for S protein folding and maturation, resulting in reduced S protein-mediated cell-cell fusion and viral entry. Of note, N1074Q mutation markedly affected S protein stability and induced significant receptor-independent syncytium (RIS) formation in HEK293T/hACE2-KO cells, and removal of the furin-cleavage site partially compensated instability of N1074Q mutation. Although the corresponding mutation in the SARS-CoV S protein (N1056Q) did not induce RIS in HEK293T cells, the mutants N669Q and N1080Q exhibited increased fusogenic activity and induced syncytia formation in HEK293T cells. Therefore, N-glycans on the SARS-CoV and SARS-CoV-2 S2 subunits are of great importance in maintaining the prefusion state of the S protein. The study revealed the critical roles of N-glycans in S protein maturation and stability, which have implications for the design of vaccines and anti-viral strategies.

(1) Background: Tooth extraction is one of the oldest and most well-known surgical procedures in dental medicine. It is still routinely performed to date by both general practitioners, oral surgeons, and dental undergraduates. The Benex extraction system allows for the extraction of teeth in vertical direction, which avoids most trauma against the surrounding alveolar bone and soft tissues; (2) Methods: The study included 56 patients who were recruited from the department of Oral Surgery at the Faculty of Dental Medicine, Medical University – Plovdiv. Patients were divided into two groups of 28 patients – Group I (control group) and Group II (study group). For each group the success of the extraction, buccal cortical plate preservation, pain experience and early wound healing were assessed; (3) Results: There was no statistical significance between the success of the extractions in both groups. The Benex extractions preserved the buccal cortical plate in 95% of the cases, whereas the forceps extractions only in 71.8%, which shows a statistical significance. On the seventh day patients in group II reported less pain, without a significant difference. There was a significantly bigger number of completely healed extraction wounds on the 10th day; (4) Conclusions: Atraumatic extractions allow for more hard and soft tissues to be preserved in the extraction site. This is all crucial for the successful outcome and aesthetically pleasing results of a following prosthetic or implant restoration.

Background: Microscopic examination of acid-fast stained sputum smears for detecting mycobacterial acid-fast bacilli (AFB) remains the most economical and readily available method for laboratory diagnosis of tuberculosis (TB). However, this conventional approach has limitations, including low sensitivity and labor-intensive procedures. Methods: An automated microscopy system incorporating artificial intelligence (AI) and machine learning for AFB identification was evaluated. The study was conducted at an Infectious Disease Hospital in Jiangsu Province, China, utilizing an intelligent microscope system (TB-Scan, Wellgen Medical, Kaohsiung). A total of 1,000 sputum smears were included in the analysis, with the system capturing digital microscopic images and employing an image recognition model to automatically identify and classify AFB. Referee technicians provided the gold standard for discrepant results. Results: The automated system demonstrated an overall accuracy of 95.00% (950/1,000), sensitivity of 91.24% (177/194), and specificity of 95.91% (773/806). Notably, the system identified 21 smears as positive that were previously reported as negative, with referee technicians confirming 17 of these as true positive and retracting the test results accordingly. Recalculating the performance, the accuracy increased to 96.70% (967/1,000), sensitivity to 91.94% (194/211), and specificity to 97.97% (773/789), with a false negative rate of 8.06% (17/211) and a false positive rate of 2.03% (16/789). Conclusions: The incorporation of AI and machine learning into an automated microscopy system demonstrated the potential to enhance the sensitivity and efficiency of AFB detection in sputum smears compared to conventional manual microscopy. This approach holds promise for widespread application in TB diagnostics and potentially other fields requiring labor-intensive microscopic examination.

Salinity acts as a critical environmental filter on microbial communities in natural systems, negatively affecting microbial diversity. However, how salinity affects the community assembly remains unclear. This study used Wendeng multi-pond saltern as a model to evaluate the prokaryotic community composition and diversity and quantify the relative importance of ecological processes across salinity gradients. Results showed that low saline salterns (45-80 g/L) exhibited higher bacterial diversity than those in high saline salterns (175-265 g/L). The relative abundance of taxa assigned to Halanaerobiaceae, Haloferacaceae, Desulfohalobiaceae, Phormidiaceae, Rohodobacteraceae, and Nitrococcaceae was higher with increasing salinity. Salinity and pH were the primary environmental factors that directly or indirectly determined the composition and diversity of prokaryotic communities. Microbial co-occurrence network dynamics were more complex in the sediment than in water of salterns. An infer Community Assembly Mechanisms by Phylogenetic-bin-based null model analysis (iCAMP) showed that microbial community assembly in sediment and water differed. Our findings provide more information about microbial community structure and the importance of various ecological processes in controlling microbial community diversity and succession along salinity gradients in water and sediment environments.

Women are at higher risk of cognitive impairment and Alzheimer’s disease (AD) after menopause when the estrous cycle becomes irregular and begins to taper off. Numerous studies have shown that estrogen deficiency, especially estradiol (E2), has been shown to play a key role in this phenomenon. Recently, a novel polymeric drug, hyaluronic acid-17β-Estradiol conjugate (HA-E2), has been developed which has the ability to cross the blood-brain barrier (BBB), facilitate a longer E2 release profile and lower risk of estrogen supplement related side effects. In this study, we used an ovariohysterectomy (OHE) rat model of postmenopausal cognitive deficits and explore whether HA-E2 treatment can improve the cholinergic septo-hippocampal innervation system, synaptic transmission in the hippocampal pyramidal neuron and cognitive impairment. Our results show that OHE rats after HA-E2 administration have increased expression of choline acetyltransferase (ChAT) in the medial septal nucleus (MS nucleus) and the hippocampus, increased spine density in hippocampal pyramidal neurons, and improved spatial learning and memory. Therefore, HA-E2 has great potential as a new novel class of drugs for estrogen-deficiency-induced cognitive impairment and AD.

Alzheimer's disease (AD) is a multifaceted neurodegenerative disorder characterized by cognitive decline and neuronal loss, representing a most challenging health issue. We present a computational analysis of transcriptomic data of AD tissues vs. healthy controls, focused on elucidation of functional roles played by long non-coding RNAs (lncRNAs) throughout the AD progression. We first assembled our own lncRNA transcripts from the raw RNA-Seq data generated from 527 samples of dorsolateral prefrontal cortex, resulting in the identification of 31,574 novel lncRNA genes. Based on co-expression analyses between mRNAs and lncRNAs, a co-expression network is constructed. Maximal subnetworks with dense connections are identified as functional clusters. Pathway enrichment analyses are conducted over mRNAs and lncRNAs in each cluster, which serve as the basis for the inference of functional roles played by lncRNAs involved in each of the key steps in an AD development model that we have previously build based on transcriptomic data of protein-encoding genes. Detailed information is presented about the functional roles by lncRNAs in activities related to stress response, reprogrammed metabolism, cell-polarity, and development. Our analyses have also revealed that lncRNAs have discerning power in distinguishing between AD samples of each stage and healthy controls. This study represents the first of its kind.

We study almost hypercomplex structure with Hermitian-Norden metrics on 4-dimensional Lie groups considered as smooth manifolds. All the basic classes of a classification of 4-dimensional indecomposable real Lie algebras depending on one parameter are investigated. There are studied some geometrical characteristics of the respective almost hypercomplex manifolds with Hermitian-Norden metrics.

Bone drilling is a common procedure used to create pilot holes for inserting screws to secure implants for fracture fixation. However, dis process can increase bone temperature, teh excessive heat can lead to cell death and thermal osteonecrosis, potentially causing early fixation failure or complications. We conducted a three-dimensional dynamic elastoplastic finite element model to evaluate teh propagation and distribution of heat during bone drilling and assess teh thermally TEMPeffected zone (TAZ) dat may lead to thermal necrosis. dis model investigates teh parameters influencing bone temperature during bone drilling, including drill diameter, rotational speed, feed force, and predrilled hole. Teh results indicate dat our FE model is sufficiently accurate in predicting teh temperature rise TEMPeffect during bone drilling. Teh maximum temperature decreases exponentially wif radial distance. When teh feed forces are 40 and 60 N, teh maximum temperature does not exceed 45 °C. However, wif feed forces of 10 and 20 N, both teh maximum temperature exceeds 45 °C wifin a radial distance of 0.2 mm, indicating a high-risk zone for potential thermal osteonecrosis. Wif teh two-stage drilling procedure, where a 2.5 mm pilot hole is pre-drilled, teh maximum temperature can be reduced by 14 °C. dis suggests dat higher feed force and rotational speed and/or using a two-stage drilling process could mitigate bone temperature elevation and reduce teh risk of thermal osteonecrosis during bone drilling.

The first appearance of viruses can date back to the late last century. As an effective form of malware, viruses reside in the permanent storage of target hosts. Before a virus can execute, that must load into memory from the persistent storage included in the associated file. Due to the reliable destructive power of viruses, many mechanisms have been developed to defend computer systems against these hazardous threats. Antivirus software is one of the most famous and popular among these mechanisms. Most antivirus software uses static analysis (signature-based) technology on files stored in permanent storage, such as hard disks or USB flashes, to detect viruses hidden in files. Fileless malware was developed to enhance the survivability of malware by circumventing detection. Fileless malware only exists in the target hosts’ memory, not files. Antivirus software cannot even access the fileless malware code, much less analyze it, since it may be performed in memory directly without needing to load it from a disk. As a result, it is difficult for an antivirus engine to defend a system against fileless malware attacks. This paper proposes a kernel-based solution called Check-on-Execution (CoE) to detect fileless malware on a Linux system. When a program is going to execute a piece of code in a writable and executable memory area of a process, CoE suspends the code execution first. Coe retrieves the code from memory, packs the code with an ELF header to create an ELF file, and uses VirusTotal to check the file to prevent a Linux system from executing fileless malware. Experimental results show that CoE noticeably enhances the ability of a Linux system to defend itself again fileless malware. CoE is also suitable for protecting a system from shell code injection attacks, such as buffer and heap overflow attacks. It is capable of handling even packed malware. But in this paper, we only focus on fileless malware.

(1) Background: In recent years, an innovative approach has emerged in the field of toxicology for managing acute intoxications caused by lipophilic substances: intravenous lipid emulsions (ILE). Through numerous experiments and case reports, the efficacy of lipid emulsions in counteracting toxicities induced by lipophilic agents, including a significant number of antiepileptic drugs (AE), has become increasingly evident. (2) Methods: Data spanning a 10-year period (2010-2020) was analyzed by searching through multiple scientific publication platforms like PubMed, Science Direct, Research Gate, and Springer Link. The study focused on reviewing relevant case reports detailing successful Intravenous lipid emulsion (ILE) administration in pa-tients with acute intoxications with antiepileptics, specifically examining the impact of fat emul-sions on neurological status, Glasgow Coma Scale (GCS) scores, and corrected QT interval con-cerning hemodynamic instability. (3) Results: The typical symptoms of antiepileptic toxicity in-clude central nervous system depression, ataxia, and nystagmus. Intravenous lipid emulsion ap-plication resulted in an increase in Glasgow Coma Scale scores and enhanced recovery from drug intoxication. (4) Conclusions: This study provides a comprehensive overview of the potential utility of ILE as a component to antidote therapy in cases of acute AE poisoning involving neurotropic drugs. The process involves the engagement of various mechanisms of antitoxic activity.

Accurate channel estimation is of utmost importance for massive MIMO systems that allow providing significant improvements in spectral and energy efficiency. In this work, we investigate the spectral efficiency performance and present a channel estimator for multi-cell massive MIMO systems subjected to pilot-contamination. The proposed channel estimator performs well under moderate to aggressive pilot contamination scenarios without prior knowledge of the inter-cell large-scale channel coefficients and noise power. The estimator approximates the performance of a linear Minimum Mean Square Error (MMSE) as the number of antennas increases. Following, we derive a lower bound closed-form spectral efficiency of the Maximum Ratio Combining (MRC) detector in the proposed channel estimator. The simulation results highlight that the proposed estimator performance approaches the linear minimum mean square error (LMMSE) channel estimator asymptotically.

Craters are the most prominent geomorphological features on the surface of celestial bodies, which is playing a crucial role in studying the formation and evolution of celestial bodies, as well as in landing and planning for surface exploration. Currently, the main automatic crater detection models and datasets focus on the detection of large and medium craters. In this paper, we created 23 small lunar crater datasets for model training based on the Chang’E-2 (CE-2) DOM, DEM, Slope, and integrated data with 7 kinds of visualization stretching methods. And then, we proposed the YOLO-Crater model for Lunar and Martian small crater detection by replacing EioU and VariFocal loss to solve the crater samples imbalance problem and introducing a CBAM attention mechanism to mitigate interference from the complex extraterrestrial environment. The results show that the accuracy (P = 87.86%, R = 66.04%, and F1 = 75.41%) of the Lunar YOLO-Crater model based on the DOM-MMS (Maximum-Minimum Stretching) dataset is the highest and better than that of YOLOX model. And the Martian YOLO-Crater, trained by the Martian dataset from the 2022 GeoAI Martian Challenge, achieves good performance with P = 88.37%, R = 69.25%, and F1 = 77.65%. It indicates that the YOLO-Crater model has a strong transferability and generalization capability, which can be applied to detect small craters on the Moon and other celestial bodies.

The purpose of this paper is to evaluate the timing of innovative investment in technology product life cycles using a compound binomial option with management flexibility. Considering the business cycles changes in the macroeconomic will affect consumer purchasing power. The focus is how to evaluate the optimal investment strategy and the project value. It was applied to different product stages (three stages including production innovation, manufacture innovation, and operation innovation) and factored to different risks to build a technology innovation strategy model. An aim of this study is the options premium of the best strategy timing for each innovation stage. Its application of the compound binomial options for the manufacture innovation will only be considered after the execution of the production innovation. The same condition is applied to the operation innovation, which will only be considered after the execution of the manufacture innovation. Then, this paper constructs the dynamic investment sequential decision model, assesses the feasibility of an investment strategy, and makes a decision on the appropriate project value and options premium for each stage under the possible change of Gross Domestic Product (GDP). This paper investigates the product life cycle innovation investment topic by using the compound binomial options method and will provide a more flexible strategy decision compared with other trend forecast criteria.

Influenced by the quasi-stationary Mei-yu front and the development of mesoscale low vortices on the Mei-yu front, a torrential rain event occurred in Suzhou on July 6, 2020. The 24-hour rainfall recorded by the automatic station exceeded 200 millimeters, with the highest hourly intensity surpassing 70 millimeters, accompanied by thunderstorms and strong winds. This heavy precipitation process was characterized by suddenness, extremity, long duration, high precipitation efficiency, and backward propagation. Using various data sources such as the European ERA5 reanalysis data, ground-based automatic stations, sounding, Doppler weather radar, and wind profile radar, this paper analyzed in detail the circulation characteristics and radar echo structures of this torrential rain event, and further studied the triggering, feature evolution, and maintenance mechanisms of the heavy precipitation.The results show: (1) The continuously strengthening low-level jet stream propagates downward forming an ultra-low-level jet stream. Heavy precipitation is located on the left front side of the jet exit area, where strong convergence and lifting in the boundary layer overlap with the ascending branch of the secondary circulation above the shear line, resulting in heavy precipitation. (2) A supercell storm with intense precipitation produced this heavy rainfall event, characterized by a low centroid of strong echo; echo-free vault, bounded weak echo region, and other supercell structural features. During this event, the high reflectivity factor areas corresponded to high KDP value areas, indicating a large amount of liquid water content. Vertically, the KDP column can track the rainwater mixing ratio well, and its location corresponds to the vicinity of the short-term heavy precipitation occurrence. The high KDP value area mainly consists of numerous precipitation particles, and the vertical vortex wind field structure causes rapid growth of precipitation particles through continuous rolling. Furthermore, it can be found through correlation coefficients (CC) that there are always high-value areas for CC since they correspond to areas of intense precipitation. (3) Continuous triggering of mesoscale convective cloud clusters on the east-west ground convergence line leads to new development and forms a "train effect." Strong frontogenesis in both horizontal and vertical directions triggers and sustains this heavy precipitation event. The significant increase in liquid water and water vapor density has indicative significance for the occurrence of heavy precipitation.

Quality of Experience (QoE) metrics can be used to assess user perception and satisfaction in data services applications delivered over the Internet. End-to-end metrics are formed because QoE is dependent on both the users’ perception and the service used. Traditionally, network optimization has focused on improving network properties such as the QoS. In this paper we examine the Adaptive streaming over a software defined network environment. We aimed to evaluate and study the media streams, aspects affecting the stream, and network. This was done to eventually reach a stage of analysing the network’s features and their direct relationship with the perceived QoE. We then use machine learning to build a prediction model based on subjective user experiments. This will help to eliminate future physical experiments and automate the process of predicting QoE.

China promotes nature-based solutions (NbS) as key approaches to addressing climate change, ecosystem damage, and biodiversity loss. However, indigenous and local knowledge (ILK), which is recognized by international scholars as an essential element of successful NbS, has not been thoroughly studied in the Chinese context. By conducting a comprehensive review of Chinese central governmental policies and semi-structured interviews with typical cases, this study finds out diversified sources of ILK and five pathways of ILK integration, including education, supervision, participation, knowledge preservation, and knowledge adoption. An increasing emphasis on community engagement has been driven by central policies such as the ecological civilization, carbon peaking and carbon neutrality goals. From a practical perspective, consistent core ideas of ILK exist in selected typical Chinese cases and studies in other countries, namely co-existence and reciprocity with nature. While supportive central policies can set the scene, ILK integration could not be realized without local governmental endorsement, context-based implementation, and long-term multi-stakeholder participation. Furthermore, this study also figures out a potential deficiency in terms of realizing effective ILK integration in mainstream and conventional practices, which can be further investigated by future studies.

Background: Hypoalbuminemia is known to be associated with adverse outcome in critical illness. In this study, we attempted to identify if hypoalbuminemia on emergency department (ED) arrival a reliable predictor for in-hospital mortality in necrotizing fasciitis (NF). patients. Method: A retrospective cohort study of hospitalized patients with NF was conducted in a tertiary teaching hospital in Taiwan between March 2010 and March 2018. Blood samples were collected in the ED upon arrival, and serum albumin levels were determined. we evaluated the predictive value of serum albumin level at ED presentation for in-hospital mortality. All collected data were statistically analyzed. Result: Of the 707 NF patients, 40 (5.66%) died in the hospital. The mean serum albumin level was 3.1 ± 0.9 g/dL and serum albumin levels were significantly lower in the non-survivor group than in the survivor group (2.8± 0.7 g/dL vs. 3.5 ± 0.8 g/dL). In the multivariable logistic regression model, albumin was associated with in-hospital mortality significantly (odds ratio[OR] 0.92, 95% confidential interval (CI) 0.88–0.96, P <0.001). The area under-the-receiver-operating-characteristic curve (AUC) for in-hospital survival was 0.77 (95% CI 0.72–0.82) and corresponding sensitivity, specificity, positive predictive value, negative predictive value, positive and negative likelihood ratio were 66%, 74%, 33%, 88%, 2.25 and 0.48, respectively. High sensitivity (96%) was shown at albumin level of 4.0 g/dL and high specificity (91%) was shown at level of 2.5 g/dL. Conclusion: Initial serum albumin levels were independently associated with in-hospital mortality among adult patients with necrotizing fasciitis and demonstrated fair discriminative performance in the prediction of in-hospital mortality. NF patients with hypoalbuminemia on ED arrival should be closely monitored for signs of deterioration and consider early and aggressive intervention to prevent mortality.

In this article, the geometry of pseudoparallel, Ricci-generalized pseudoparallel and 2-Ricci-generalized pseudoparallel invariant submanifolds of an almost $\alpha$-cosymplectic $(\kappa,\mu,\nu)$ space has been searched under the some conditions. We also give some characterizations for such submanifolds. I think that obtained new results contribute to differential geometry.

In order to tackle the issue of severe rocking phenomenon under seismic conditions in structures equipped with steel spring isolation bearings, this paper investigates a novel type of anti-rocking bearing. Firstly, the structural configuration and working principle of the novel anti-rocking bearing are introduced, and a design method for bearing parameters is proposed. Secondly, a finite element analysis model is established using SAP2000 software to conduct nonlinear dynamic time history analysis under seismic loading. The analysis results show that the structural arrangement of the novel anti-rocking bearing reduces both the vertical displacement difference and the rocking angle of the isolation layer. The bearing exhibits a certain level of anti-rocking effect, but it may cause significant tensile forces in some bearings, necessitating the installation of anti-tensile reinforcement. The effectiveness of the anti-rocking effect improves as the stiffness of the steel tension rod in the bearing increases; however, it also leads to higher maximum tension in individual bearings as well as the total tension in all bearings. For structures equipped with the novel anti-rocking bearing, the acceleration amplifies under most cases, with amplification coefficients ranging from 0.82 to 1.55. The performance of the novel anti-rocking bearing varies significantly for different seismic waves. The stiffness of the steel tension rod should be determined considering the reference pressure of the bearing and the maximum designed tension of the bearing. Through the finite element simulation of the bearing, the mechanical properties of the bearing are basically the same as the theoretical analysis results. For the cylinder and the joint bearing, certain structural measures need to be taken to ensure its strength and stiffness.

Background: Recent researches have investigated the biological importance of RNA N1-methyladenosine (m1A) modifications in oncogenesis and progression of head and neck squamous cell carcinoma (HNSCC). However, whether m1A modifications also have latent effect in tumor microenvironment (TME) generation and immune regulation in HNSCC is unknown. Methods: We evaluated the m1A modification patterns and related to these modification patterns with TME cell infiltration features in 1041 HNSCC samples by bioinformatics approach. Results: The m1A score is an independent prognostic indicator. HNSCC patients with low m1A score group with poor overall survival (OS) was mainly characterized by stroma activation, lack of sufficient immune infiltration, and exhibited an immune- desert TME phenotype. Low m1A scores were also correlated with increased tumor mutation burden (TMB), and HNSCC patients with high TMB and low m1A scores had the worst OS. In addition, anti-CTLA-4 combined with anti-PD1 treatment was more effective in the high m1A score subgroup than in the low m1A score subgroup. Conclusions: This study revealed that m1A modifications play a non-negligible role in developing the TME versatility and complexity of HNSCC. Assessing m1A modification patterns in HNSCC helps improve our comprehension of its TME infiltration profile and guides more effective immunotherapeutic approaches.

The integration of three-dimensional (3D) printed resin denture teeth represents a significant ad-vancement in digital dentistry. This study aimed to assess their ability to withstand chipping and indirect tensile fractures, comparing them with conventionally manufactured resin denture teeth. Four groups, each comprising 30 specimens, were examined: Group 1 featured 3D printed denture teeth (NextDent, 3D Systems, Soesterberg, The Netherlands), while the others included commer-cially obtained Ivostar Shade, SpofaDent Plus, and Major Super Lux teeth. Stereolithography 3D printing was utilized to produce methacrylate-based photopolymerized resin teeth models for Group 1, while the remaining groups were commercially sourced. Chipping and indirect tensile fracture tests were performed at a speed of 1 mm/min until fracture occurred. Statistical analysis was conducted using one-way analysis of variance (ANOVA) with Tukey's honestly significant difference multiple comparisons test (p < 0.05). Results indicated that 3D-printed teeth exhibited higher indirect tensile fracture resistance than Major Super Lux and Ivostar Shade but lower than SpofaDent Plus. Additionally, in the chipping test, buccal chipping occurred in 3D-printed resin teeth without distortion. In the indirect tensile test, the fracture line emerged near the loading point, extending cervically from the inner incline of both cusps. Overall, denture teeth produced via 3D printing with printable resin materials demonstrated sufficient fracture resistance, making them suitable for prosthetic applications.

The primary objective of this current study is to conduct a comprehensive review of existing literature that discusses research on post and core restorations, covering aspects such as their composition, manufacturing methods, and clinical effectiveness. The methodology employed in this review encompasses the implementation of a well-defined search strategy, the establishment of criteria for inclusion and exclusion, and the selection of relevant studies to summarize their findings. To gather relevant literature published between 1993 and 2023, the research team conducted separate searches on PubMed, Scopus, and Embase databases. In total, 165 titles were initially retrieved from these electronic databases. By applying the predefined exclusion criteria, the researchers identified 73 articles that specifically address the conventional and computer-aided design/computer-aided manufacturing (CAD/CAM) technologies employed in post and core restorations. These restorations are frequently utilized procedures for repairing teeth that have undergone endodontic treatment and subsequently lost dental structure. The development of computerized technology for the creation of customized posts and cores has emerged as a straightforward and efficient alternative to traditional methods. The review encompasses a synthesis of papers discussing the various techniques and materials employed in constructing post and cores using CAD/CAM technology. Notably, different strategies for restoring endodontically treated teeth through CAD/CAM post and cores have been documented, revealing both direct and indirect approaches. The most mentioned materials for these restorations include zirconia, composite resin, and hybrid ceramics. While the available literature on CAD/CAM post and core procedures is somewhat limited, the review underscores the need for further research to explore the long-term outcomes and efficacy of this treatment approach.

Lithium-sulfur (Li-S) battery has been regarded as an important candidate for the next-generation energy storage system due to its high theoretical capacity (1675 mAh g-1) and high energy density (2600 Wh kg-1). However, the shuttle effect of polysulfide seriously affects the cycling stability of the Li-S battery. Here, a novel Fe3C decorated folic acid-derived graphene-like N-doped carbon sheet (Fe3C@N-CS) was successfully prepared as the polysulfide catalyst to modify the separator of Li-S battery. The porous layered structures can successfully capture polysulfide as a physical barrier, and the encapsulated Fe3C catalyst can effectively trap and catalyze the conversion of polysulfide, thus accelerating the redox reaction kinetics. Together with the highly conductive networks, the cell with Fe3C@N-CS modified separator evinces superior cycling stability with 0.06% capacity decay per cycle at 1 C rate over 500 cycles and excellent specific capacity with an initial capacity of 1260 mAh g-1 at 0.2 C. Besides, at a high sulfur loading of 4.0 mg cm-2, the batteries also express superb cycle stability and rate performance.

Thermal fluctuations in two-dimensional (2D) isotropy systems at non zero finite temperatures can destroy the long-range (LR) magnetic order due to Mermin-Wanger theory. Interestingly, the magnetic anisotropy related to spin-orbit coupling (SOC) could stabilize magnetic order in 2D systems. Recently, 2D FexGeTe2 (3≤x≤7) with high curie temperature (TC), as a typical 2D van der Waals metallic ferromagnet, has not only made significant progress in synthetic methods and controlling ferromagnetism (FM), but also actively explored many device applications. In this Review, we introduce six experimental methods, ten ferromagnetic modulation strategies, and three spintronic devices of 2D FexGeTe2 materials. Overall, we have outlined the challenges and potential research directions in this field.

Recent advances in quantum computing systems attract tremendous attention. Commercial companies, such as IBM, Amazon, and IonQ, have started to provide access to noisy intermediate-scale quantum computers. Researchers and entrepreneurs attempt to deploy their applications that aim to achieve a quantum speedup. Grover’s algorithm and quantum phase estimation are the foundations of many applications with the potential for such a speedup. While these algorithms, in theory, obtain marvelous performance, deploying them on existing quantum devices is a challenging task. For example, quantum phase estimation requires extra qubits and a large number of controlled operations, which are impractical due to low-qubit and noisy hardware. To fully utilize the limited onboard qubits, we develop a distributed application with a key-value data structure based on Grover’s algorithm called IQuCS . Consider a database with duplicates. By encoding each element to a binary type with a unique key and forming a key-value pair, we can count the number of occurrences of each element in the database based on quantum computing. We have optimized the operation process by filtering data points to make it more efficient. To determine the effect of this optimization, we evaluate it with datasets of different sizes and with different numbers of duplicates. With the assistance of classical computers, IQuCS can reduce the problem set for each query. Due to this reduction, IQuCS requires fewer qubits. Through the iterative management, IQuCS achieves a reduction of qubit virtualized consumption, up to 66.2%, with reasonable accuracy.

This study investigates the impact of specimen size on the mechanical properties of wood, specifically focusing on compression strength, elastic modulus, and Poisson's ratio. Compression tests were conducted using three different specimen sizes (20mm×20mm×30mm, 40mm×40mm×60mm, 60mm×90mm×90mm) in the longitudinal, radial, and tangential directions. Mechanical parameters, failure mechanisms, load-displacement curves, and stress-strain relationships were systematically analyzed for each size. The study also evaluated the influence of specimen size on the accuracy of finite element numerical simulations by utilizing the obtained mechanical parameters. The results reveal a significant correlation between compressive strength and specimen size, indicating a decrease in compressive strength with increasing specimen size. Conversely, elastic modulus and Poisson's ratio exhibit less sensitivity to variations in specimen size. Notably, parameters derived from small-sized specimens (20mm×20mm×30mm) exhibited substantial errors, while those obtained from medium-sized (40mm×40mm×60mm) and large-sized specimens (60mm×90mm×90mm) demonstrated greater reliability, providing precise results in finite element numerical simulations.

Digital transformation provides new drivers for economic performance growth in enterprises, but can it further improve ESG performance and support sustainable development? Based on the perspective of resources and capabilities, this paper uses the relevant data of 1588 listed companies in strategic emerging industries from 2011 to 2021 to study the differential impact of digital transformation on enterprise ESG performance, and further tests the mediating role of absorptive capacity and the moderating role of regional digital level. The research results indicate that: firstly, digital transformation of enterprises can positively promote the improvement of ESG performance; Secondly, there are significant differences in the impact of digital transformation on the ESG performance of enterprises in terms of property rights and industry characteristics. The ESG performance of state-owned enterprises and high-end equipment manufacturing enterprises is more sensitive to digital transformation; Thirdly, absorptive capacity plays a mediating role between digital transformation and corporate ESG performance; Fourthly, the positive regulation of regional digital level promotes the ESG performance of enterprises through digital transformation. The research conclusion is based on a digital perspective, providing relevant insights for improving the ESG performance of strategic emerging industry enterprises and expanding their ESG development paths.

Image encryption is increasingly becoming an important area of research in information security and network communications, as digital images are widely used in various applications and are vulnerable to various types of attacks. In this research work, a color image cryptosystem that is based on a 3-layer permutation-substitution network (PSN) is proposed. For every layer, an encryption key and an S-box are generated and utilized. Those are based on a four-dimensional (4D) dynamical Chen system of a fractional-order, the Mersenne Twister, OpenSLL, Rule 30 Cellular Automata and Intel’s MKL. The sequential application of Shannon’s ideas of diffusion and confusion for 3 times guarantees a total distortion of any input plain image, resulting in a totally encrypted one. Apart from the excellent and comparable performance to counterpart algorithms from the literature, showcasing resistance to visual, statistical, entropy, differential, known plaintext and brute-force attacks, the proposed image cryptosystem provides an exceptionally superior performance in 2 aspects: a vast key space of 2^1658 and an average encryption rate of 3.34 Mbps. Furthermore, the proposed image cryptosystem is shown to successfully pass all the tests of the NIST SP 800 suite.

Aim. In the current study, we aimed at identifying resting-state brain networks, which are different in patients with depression compared to healthy individuals. Moreover, we analyzed the potential for clinical use of different network measures that could discriminate the two groups and thus help the diagnostic process. Method and subjects. We recruited 90 subjects: 49 healthy controls (HC) and 41 patients with a major depressive episode (MDE). All subjects underwent clinical evaluation and functional resting-state MRI. The data were processed to investigate functional connectivity network measures across the two groups using Brain Connectivity Toolbox. The statistical inferences were made at the functional networks level, using false discovery rate method. Independent samples t-test was performed on the network measures mean values to reveal differences between HC and MDE groups. Permutation-based statistical testing was used to test the significance of the difference between the distributions of the network measures by nodes for HC and MDE groups. Linear discriminant analysis was used to differentiate between the groups. Results and discussion. Significant differences in FC between depressed patients and healthy controls were found with the most prominent changes encompassing within-region as well as between-region connectivity of occipital lobe areas such as precuneus (PreCu), cuneus (Cu), superior occipital gyrus (SOG), lingual gyrus (LG), fusiform gyrus (FG), cerebellum, along with limbic structures including the hippocampus (Hipp) and cingulate gyrus. Linear discriminant analysis demonstrated that the full connectivity matrices, as well as those with only the significant connections identified in advance, were the most precise in differentiating between depression and health. These measures reached precision levels of 97% and 94%, respectively. Conclusion. Our study delivered further evidence about impairment of functional connectivity networks in MDE that may contribute to differentiate patients with depression from healthy subjects.

In this study, a new type of temperature sensor device was developed. The circular electrode of the thermal sensitive sensor was modified with TMT and O₂ plasma to enhance the conductivity by forming a thin SnOxCy layer on the electrode surface. The Nano-Au particles were subjected to O₂ plasma pretreatment to form peroxide groups on the surface. The thermally sensitive sensor was made by mixing the above-treated Nano-Au particles with N-isopropylacrylamide (NIPAAm) to form solution and then UV-induced grafting polymerization of the NIPAAm-containing solution onto the electrode substrate. The composite hydrogels on the electrode introduce thermo-sensitive polymeric surface films for temperature sensing. Using ambient environment resistance test to measure the resistance, the LCST (lower critical solution temperature) of Nano-Au (MUA) mixed with NIPAAm hydrogel was found to be 32 °C. At ambient temperatures higher than LCST, the electrode resistance decreases linearly.

BACKGROUND: The number of waitlisted patients requiring mechanical circulatory support (MCS) as a bridge to heart transplantation is increasing. The data concerning the results of double-bridge strategy are limited. We sought to investigate the post-transplant outcomes across the different bridge strategies. METHODS: We retrospectively reviewed a heart transplantation database from Jan 2009 to Jan 2019. Intra-aortic balloon pump (IABP), extracorporeal membrane oxygenation (ECMO), and ventricular assist devices (VAD) were the MCS that we investigated. The pre- and post-transplant characteristics and variables of patients bridged with the different types of MCS were collected. The post-transplant survival was compared using Kaplan-Meier survival analysis. RESULTS: A total of 251 heart transplants were reviewed; 115 without MCS and 136 with MCS. The patients were divided to five groups: Group 1 (no MCS): n=115; Group 2 (IABP): n=15; Group 3 (ECMO): n=33; Group 4 (ECMO-VAD): double-bridge (n=59); Group 5 (VAD): n=29. Survival analysis demonstrated that the 3-year post-transplant survival rates were significantly different among the groups (Log-rank p < 0.001). There was no difference in survival between group 4(ECMO-VAD) and group 1(no MCS)1 (p = 0.136), or between group 4(ECMO-VAD) and group 5(VAD) (p = 0.994). Group 3(ECMO) had significantly inferior 3-year survival than group 4(ECMO-VAD) and group 5(VAD). CONCLUSION: Double bridge may not lead to worse mid-term results in patients who could receive a transplantation. Initial stabilization with ECMO for critical patients before implantation of VAD might be considered as a strategy for obtaining an optimal post-transplant outcome.

Antibody-Drug Conjugates (ADCs) are a powerful therapeutic modality for cancer treatment. ADCs are multi-functional biologics in which a disease-targeting antibody is conjugated to an effector payload molecule through a linker. The success of currently used ADCs has been largely attributed to the development of linker systems which allow targeted release of cytocidal payload drugs inside cancer cells. Many lysosomal proteases are over-expressed in human cancers. They can effectively cleave a variety of peptide sequences, which can be exploited in the design of ADC linker systems. As a well-established linker, valine-citrulline-p-aminobenzyl carbamate (ValCitPABC) is used in many ADCs that are already approved or under preclinical and clinical development. Although ValCitPABC and related linkers are readily cleaved by cathepsins in the lysosome while remaining reasonably stable in human plasma, many studies have shown that they are susceptible to carboxylesterase 1C (Ces1C) in mouse and rat plasma, which hinders preclinical evaluation of the ADCs. Furthermore, neutropenia and thrombocytopenia, two of the most commonly observed dose-limiting adverse effects of ADCs, are believed to result from the premature hydrolysis of ValCitPABC by human neutrophil elastase. In addition to cathepsin-cleavable linkers, there is also growing interest in legumain-sensitive linkers for ADC development. Increasing plasma stability while maintaining lysosomal cleavability of ADC linkers is an objective of intensive current research. This review reports recent advances in the design and structure-activity relationship studies of various peptide/peptidomimetic linkers in this field.

Background and Objectives: Trichomonas tenax is a protozoan, participating in the human oral microflora. It is considered as a potential paradontopathogen. This microorganism is also reported in the respiratory tract. We aimed to analyze the available literature about the prevalence of Trichomonas tenax in the population affected by periodontal disease. Materials and Methods: Тhe searching with keywords: ,,Trichomonas tenax” and “periodontal diseases’’ in Scopus, PubMed and ScienceDirect databases was able to identify several systematic reviews and original articles until July 2023. All studies with suffering from periodontal disease people, mentioned year of publication, country, specified detection methods, total number of tested samples as well as the percentage of those infected with Trichomonas tenax were included. Irrelevant articles were excluded. Results: We found 137 studies, but only 64 studies about distribution of Trichomonas tenax in patients with gum disease underwent qualitative analysis. The highest number of studies have been conducted in Iran, Poland and Iraq. Different methods have been used to detect the unicellular organism, each with different specificity and sensitivity. Conclusions: Interest in Trichomonas tenax has grown considerably since 2000. Because of its association with periodontal disease, Trichomonas tenax role in the inflammatory process shouldn’t be overlooked.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

Colchicine has a number of effects that suggest it may be useful in the treatment of COVID-19. Myeloid cells are a major source of dysregulated inflammation in COVID-19. The hyperactivation of the NLRP3 inflammasome and the subsequent cytokine storm take place precisely inside them and can lead to multiorgan damage and death. NLRP3 inflammasome inhibition has been assessed at micromolar colchicine concentrations which cannot be achieved in serum. However, colchicine has remarkable ability to accumulate intensively in leukocytes, where the cytokine storm is generated. Over 50 observational studies and randomized clinical trials, small randomized non-controlled trials and retrospective cohort studies were initiated to test its healing effect in vivo, leading to conflicting, rather disappointing results. WHO gives ”Strong recommendation against” the use of colchicine for COVID-19 treatment. This is because low doses of colchicine are always used, where the concentrations required to inhibit the NLRP3 inflammasome in leukocytes cannot be reached. Considering this, from March 2020 we started the administration of higher doses of colchicine. Our assumption was that safe increase in colchicine doses to reach micromolar concentrations in leukocytes will result in NLRP3 inflammasome/cytokine storm inhibition. We demonstrated that in 785 inpatients treated with increasing doses of colchicine, mortality fell between 2 and 7 times. Our data, including also a large number of COVID-19 outpatients, showed that nearly 100% of the patients treated with this therapeutic regimen escaped hospitalization. In addition, post-covid symptoms in those treated with colchicine were significantly less. As a large number of viruses can overactivate the NLRP3 inflammasome (like seasonal influenza), we are convinced that higher colchicine doses would be useful in these cases as well.

Safe administration of highly cytotoxic chemotherapeutic drugs is a challenging problem in cancer treatment due to the adverse side effects and collateral damage to non-tumorigenic cells. To mitigate these problems, new promising approaches, based on the paradigm of controlled targeted drug delivery (TDD), utilizing drug nanocarriers with biorecognition ability to selectively target neoplastic cells, are being considered in cancer therapy. Herein, we report on the design and testing of a nanoparticle-grid based biosensing platform to aid in the development of new targeted drug nanocarriers. The proposed sensor grid consists of superparamagnetic gold-coated core-shell Fe₂Ni@Au nanoparticles, further functionalized with folic acid targeting ligand, model thiolated chemotherapeutic drug doxorubicin (DOX), and a biocompatibility agent, 3,6,-dioxa-octanethiol (DOOT). The employed dual transduction based on electrochemical and enhanced Raman scattering detection have enabled efficient monitoring of the drug loading onto the nanocarriers, attached to the sensor surface, as well as the drug release under simulated intracellular conditions. The grid’s nanoparticles serve here as the model nanocarriers for new TDD systems under design and optimization. The superparamagnetic properties of the Fe₂Ni@Au NPs aid in nanoparticles’ handling and constructing a dense sensor grid with high plasmonic enhancement of the Raman signals due to the minimal interparticle distance.

The ability to control the flow of quantum information deterministically is useful for scaling up quantum computation. In this paper, we demonstrate a controllable quantum switchboard which directs the teleportation protocol to one of two targets, fully dependent on the sender’s choice. The quantum switchboard additionally acts as a optimal quantum cloning machine. We also provide a physical implementation of the proposal using a coupled-cavity array. The proposed switchboard can be utilized for the efficient routing of quantum information in a large quantum network.

: F-box proteins are a large gene family in plants, and play crucial roles in plant growth, development, and stress response. However, a comprehensive investigation of F-box family genes in cultivated peanut (Arachis hypogaea L.), has not been undertaken. In this study, we used a bioinformatics approach to identify and analyze F-box protein family genes in the cultivated peanut genome, and examined their expression profiles. Herein, a total of 95 F-box protein family members on 18 chromosomes were identified in cultivated peanut, which were sequentially designed as AhFBX1-AhFBX95. Phylogenetic analysis classified these AhFBXs into four different groups (Group I - IV), and eight subfamilies based on the structural domains of the C-terminal. Structural analysis revealed the presence of ten unique motifs within these genes. Additionally, the investigation of non-synonymous and synonymous substitution rates (Ka/Ks), and synteny in the F-box proteins, provided valuable insights into the evolutionary and domestication processes of AhFBX genes in peanut. Furthermore, in silico expression profiling of 22 different tissues demonstrated that most genes were predominantly expressed in leaves, pistils, and the aerial gynophore tip, while some members showed tissue-specific expression at the apex of both vegetative and reproductive shoots. Subsequently, we validated the expression of 9 differentially expressed genes (DEGs) using transcriptomeic data of lateral branch development and qRT-PCR analysis. These DEGs may be involved in regulating the development of lateral branches and subsequently affect the architecture of peanut plants.

This study delves into the performance evaluation of an avant-garde technology in mobile communications known as Large Intelligent Surface (LIS), poised to be an integral component of the sixth-generation (6G) networks. This groundbreaking technology has the potential to markedly augment the Signal-to-Interference plus Noise Ratio (SINR) by orchestrating signals originating from the base station through a network of digitally controlled reflectors meticulously engineered to modulate the phase of incoming electromagnetic waves. A LIS can establish a Line of Sight (LoS) within channels that inherently do not have a LoS. In addition, it can also be optimized to increase transmission security by ensuring that the signal reaches only the target users of the message with better quality. In this study, analytical expressions were derived to calculate the distribution parameters, the bit error probability, and the secrecy outage probability. These calculations consider the presence of an eavesdropper link, highlighting the potential of the LIS to increase the confidentiality of digital communication systems. The accuracy of the proposed formulas was demonstrated by showing how the performance of the LIS varies with different design parameters and environmental fading.

Taiwan cobra (Naja atra) bites account for approximately 20% of all venomous snakebites in Taiwan. In Taiwan, the rates of wound necrosis and secondary infection from Taiwan cobra bites are higher than those associated with other venomous snakebites. Clinical tools to evaluate the infection risk after Taiwan cobra bites are lacking. Therefore, in this study, we developed a useful clinical tool to evaluate the infection risk after Taiwan cobra bites. Moreover, we investigated wound infection bacteriology. We analyzed the data of patients bitten by N. atra who had undergone freeze-dried neurotoxic antivenin treatment in emergency rooms of the Chang Gung Memorial Hospital network, which comprises seven hospitals and the largest medical system in Taiwan, from January 2001 to May 2017. Because patients with wound necrosis required antibiotics for infection treatment, we included only patients with wound infection but without tissue necrosis in the development of our Cobra Bacteriology of Infections in Taiwanese snake Envenomation (Cobra BITE) score by using univariate and multiple logistic regression. In total, 8,295,497 emergency department visits occurred from January 2001 to May 2017, and 195 patients were diagnosed has having cobra bites. Among them, 23 and 30 patients had wound necrosis and wound infection, respectively. The wound infection rate was 27.2% (53/195). Regardless of whether the patients had necrosis, Enterococcus faecalis and Morganella morganii were the main bacteria identified in the culture report. Gentamicin, ceftriaxone, ciprofloxacin, and levofloxacin are the ideal first-line antibiotics for treating N. atra bite wounds in Taiwan. As per our Cobra BITE score, the three factors predicting secondary wound infection after cobra bites are hospital admission, a white blood cell count (in 103/µL) × by neutrophil–lymphocyte ratio value of ≥114.23, and the use of antivenin medication. The area under the receiver operating characteristic curve for the Cobra BITE score system was 0.88. The ideal sensitivity and specificity were 0.89 and 0.76, respectively, and the optimal cutoff point for Cobra BITE score was 7. The Hosmer–Lemeshow p value was 0.4. In conclusion, our Cobra BITE study established a new practical clinical tool for clinicians to evaluate infection risk after N. atra bites. This score system enables the assessment of wound infections after N. atra bites, and it could be modified and improved in future for other Naja spp. bites.

In China, 65 types of venomous snakes exist, with the Chinese Cobra Naja atra being prominent and a major cause of snakebites in humans. Furthermore, N. atra is a protected animal in some areas, as it has been listed as vulnerable by the International Union for Conservation of Nature. Recently, due to the medical value of snake venoms, venomics has experienced growing research interest. In particular, genomic resources are crucial for understanding the molecular mechanisms of venom production. Here, we report a highly continuous genome assembly of N. atra, based on a snake sample from Huangshan, Anhui, China. The size of this genome is 1.67 Gb, while its repeat content constitutes 37.8% of the genome. A total of 26,432 functional genes were annotated. This data provides an essential resource for studying venom production in N. atra. It may also provide guidance for the protection of this species.

Background: Identifying genetic mutations that lead to spermatogenic impairment is essential for offering patients informed genetic counseling and preventing the transmission of genetic defects to their offspring, often through the use of advanced reproductive technologies. Objectives: The purpose of this study was to identify potential single nucleotide polymorphisms (SNPs) associated with male infertility. Methods and Materials: Genetic variants that may cause infertility are identified by combining targeted next generation sequencing (NGS) panel and whole exome sequencing (WES). The validation step of Sanger sequencing adds confidence to the identified variants. Results: Our analysis revealed five distinct affected genes covering seven SNPs: based on targeted NGS panel and WES data, namely SPATA16 (rs16846616, 1515442, 1515441), CFTR (rs213950), KIF6 (rs2273063), STPG2 (r2903150) and DRC7 (rs3809611). Infertile men have a higher mutation rate than fertile men, especially those with azoospermia. Discussion and Conclusions: These findings strongly support the hypothesis that dysfunction of microtubule-related and spermatogenesis-specific genes contributes to idiopathic male infertility. The SPATA16, CFTR, KIF6, STPG2 and DRC7 mutations are associated with male infertility, specifically azoospermia, further examination of this genetic function is required.

Hyper duplex stainless steels, HDSS, are a new alloy group of duplex stainless steels with the highest corrosion resistance and mechanical properties among the existing modern stainless steel. Due to the addition of extra high content of alloying elements, e.g. Cr, Ni, Mo, etc., the crystallization behavior of the δ-ferrite from the liquid is of vital importance for controlling the steel properties. In this work, the effect of cooling rate (i.e. 4°C/min and 150 °C/min) on the growth process of δ-ferrite in S33207 during the solidification process was investigated using high-temperature confocal scanning laser microscopy (HT-CLSM) in combination with electron microscopes and thermodynamic calculation. The results showed that the solidification mode of S33207 steel was a ferrite-austenite type (FA mode). L→δ transformation occurred at a certain degree of supercooling, and merging occurred during the growth of δ phase dendrites. Similar microstructures were observed after solidification under these two different cooling rates. The variation of area fraction of δ ferrite at the free surface and temperature as well as time during solidification of S33207 steels were calculated at different cooling rates of 4 °C/min and 150 °C/min, respectively. The current HT-CLSM study provides in-situ experimental evidence to confirm that a low cooling rate favored the growth of primary δ-ferrite, whereas a high cooling rate favored the nucleation of primary δ-ferrite during the solidification process. The post-microstructure as well as composition evolution is also briefly investigated. This work shed light on the real time insights for the crystallization behavior of hyper duplex stainless steels during solidification, which aims to contribute to the process control of manufacturing of this steel grade.

Modified aluminum slag (MAS) was applied as an adsorbent for Congo red (CR) prepared by the hydrothermal treatment of Ca (OH) 2. At 25 ℃, with a MAS dosage of 0.3g, initial CR concentration of 100 mg/L and initial pH=5, and the adsorption time was 40 min, the CR removal efficiency was 98.41%. The adsorption trend of CR conformed to the second-order kinetics, and the adsorption isotherm follows the Freundlich isotherm model. Compared with RAS, MAS has a larger pore volume and specific surface area. The mechanism of action of MAS on CR was the interaction between membrane diffusion and internal diffusion, and the adsorption rate during the membrane diffusion was the fastest.

This study explores the public library service evaluation domain through user-generated content on Google Maps, highlighting digital feedback's significant yet underexplored potential in understanding public library patronage across Taiwan's six major cities. Utilizing a mixed-methods research design, this study integrates Google Maps review content analysis with Social Network Analysis to delineate public perceptions and identify areas for service enhancement in public libraries. It innovatively leverages personal experiences extracted from over 60,000 Google Maps reviews to evaluate public library services in cities such as Taipei, New Taipei, Taoyuan, Taichung, Tainan, and Kaohsiung. The research taps into the National Library of Taiwan's National Library Statistics System to provide a robust analysis of library performance and user satisfaction, offering a novel perspective by emphasizing user-centric feedback from Google Maps as a primary data source. This approach provides quantitative data on library usage and geographic distribution and enriches our understanding of the qualitative experiences of library users. In analyzing the keywords from Google Maps reviews of public libraries, we categorize and interpret these under the three core LibQUAL+ dimensions—Affect of Service, Information Control, and Library as Place. The findings expose variances in perceived service quality among the cities, with Kaohsiung and Taichung receiving the highest accolades for service satisfaction. Simultaneously, the study identifies potential areas for improvement, particularly in cities with lower satisfaction ratings like Taipei. This personalized feedback illustrates the intimate relationship between public libraries and their communities, offering invaluable insights for policymakers and library management to enhance service delivery and user experience.

The quality of healthcare services is a very important indicator of social welfare in developed and emerging countries. Good quality levels are critical to ensuring patient safety, improving health outcomes, increasing patient satisfaction, optimizing resource utilization, and meeting regulatory requirements. The stable and sustainable operation of medical institutions urgently requires the establishment of a reliable and effective medical quality performance evaluation platform. However, the complexity of the evaluation process, involving numerous evaluators and the consideration of different subjective and objective criteria, poses significant challenges and essentially constitutes a group multi-criteria decision-making problem. This article uses the overall medical environment of the institution, medical service attitude, medical security, administrative service measures, etc. as measurement standards to deal with this challenge. It proposes a medical service quality measurement model suitable for both qualitative and quantitative analysis. In view of the heterogeneity of information, the two-tuple fuzzy language calculation method is introduced to enable evaluators to skillfully manage diverse information and effectively avoid potential information omission problems in the subjective evaluation integration process. The effectiveness and feasibility of the model were demonstrated by applying it to the operational framework of a medical institution in central Taiwan.

Acute myeloid leukemia (AML) is the second common hematologic malignancy in children. The incidence of childhood AML is much lower than acute lymphoblastic leukemia (ALL), which makes the childhood AML a rare disease in children. The role of genetic abnormalities in AML classification, management and prognosis prediction is much more important than before. The WHO classification of myeloid neoplasms and the European LeukemiaNet (ELN) classification were both revised in 2022. The application of the new information in childhood AML will be upcoming in the next few years. The frequency of each genetic abnormality in adult and childhood AML is different, therefore, in this review we emphasize in well-known genetic subtypes in childhood AML, including Core-binding factor AML (CBF AML), KMT2Ar (KMT2A/11q23 rearrangement) AML, normal karyotypes AML with somatic mutations, unbalanced cytogenetic abnormalities AML, NUP98 11p15/NUP09 rearrangement AML and acute promyelocytic leukemia (APL). Current risk group classification, management algorithm in childhood AML and novel treatment modalities, such as targeted therapy, immune therapy, chimeric antigen receptor (CAR) T-cell therapy are reviewed. Finally, the indications of hematopoietic stem cell transplantation (HSCT) in AML are discussed.

The aim of the presents study is to further expand the model of translational cross-validation by investigating the brain circuits or networks which underpin the same tasks by means of group independent component analysis for FMRI toolbox (GIFT). We hypothesized that there will be neural network patterns of activation and deactivation, which correspond to real time performance on clinical self-evaluation scales. We recruited 42 subjects: 20 healthy controls and 22 patients with major depressive episode. All subjects underwent functional MRI scanning using paradigm comprised of diagnostic clinical self-assessment depression scale contrasted to neutral scale. The data were processed with group independent component analysis for functional MRI toolbox and statistical parametric mapping. The results have demonstrated that there exist positively or negatively modulated brain networks during processing of diagnostic specific task questions for major depressive disorder. There have also been confirmed differences in the networks processing diagnostic versus off blocks between patients and controls in anterior cingulate cortex and middle frontal gyrus. Diagnostic conditions (depression scale) when contrasted to neutral conditions demonstrate differential activity of right superior frontal gyrus and right middle cingulate cortex in the comparison of patients with healthy controls. It is for the first time when potential neuroimaging state dependent biomarker has been directly linked with clinical assessment self-evaluation scale, administered as stimuli simultaneously with the fMRI acquisition. It may be regarded as further evidence in support of the ability of both methods to concordantly distinguish groups by means of incremental translational cross-validation.

Laser powder bed fusion (LPBF) is an additive manufacturing technique that is gaining popularity for producing metallic parts in various industries. However, parts produced by LPBF are prone to residual stress, deformation, cracks and other quality defects due to uneven temperature distribution during the LPBF process. To address this issue, in prior work, the authors have proposed SmartScan, a method for determining laser scan sequence in LPBF using a model-based and optimization-driven approach, rather than using heuristics, and applied it to simple 2D geometries. This paper presents a generalized SmartScan methodology that is applicable to arbitrary 3D geometries. This is achieved by: (1) expanding the thermal model and optimization approach used in SmartScan to multiple layers; (2) enabling SmartScan to process shapes with arbitrary contours and infill patterns within each layer and (3) providing SmartScan with global foresight to make it less myopic in its optimization. Sample 3D parts are printed using the proposed generalized SmartScan and compared to those printed using standard heuristic scan sequences. Reductions of up to 93% in temperature inhomogeneity, 87% in residual stress, and 26% in maximum deformation were observed, without significantly sacrificing print speed. However, SmartScan was found to cause minor (<5%) to significant (up to 20%) increases in surface roughness compared to the heuristic approaches, depending on the scan pattern used.

Magnetic levitation vibration isolation platform are essential for testing space telescopes. This paper presents the design of a Large Air-Gap Voice Coil Motor (LAG-VCM) specifically for use in such platforms. The electromagnetic design of the voice coil motor begins with the Equivalent Magnetic Circuit Method, followed by the analysis and optimization of the motor design using Finite Element Analysis (FEA). Subsequently, a prototype was constructed and tested. The test results confirm that the prototype meets the design specifications and requirements.

Psychotic disorders occur as a result of pathobiochemical processes in the brain, which disrupt the central neurotransmission of molecules such as dopamine and glutamate. The dopamine hypothesis, adopted more than 2 decades ago, has repeatedly asserted its position as an etiopathogenetic substrate through the action of psychostimulants and neuroleptics on the mesolimbic and mesocortical systems, giving insight into the origin of positive and negative schizophrenic symptoms. On the other hand, cognitive impairments in schizophrenia remain not fully understood but are thought to be present during all stages of the disease, as well as in the prodromal the interictal and residual phases. Over the last decade, functional magnetic resonance imaging has focused on research of brain networks like the Default mode network, the Salience network and Central executive network, enabling a deeper understanding of cognitive deficits, as well as other phenomena such as disorganization of thought and behavior. The study of the nodes of these networks, such as the precuneus and insula, informs about their complex significant roles as structures responsible for important cognitive domains such as concentration, attention, ability to understand and reproduce information, as well as memory functions. It is suggested that the neurotransmission of dopamine and glutamate play a key role in these processes and their successful modulation in the correct brain regions through psychopharmacological and biomedical instrumental methods may lead to a significant reversal of conventional paradigms. Pharmaco-magnetic resonance imaging is a neuroimaging method that can provide the translation of scientific knowledge about the neural networks and the disruptions in and between different brain regions, into clinically applicable and effective therapeutic results in the management of severe psychotic disorders.

It is introduced and studied para-Ricci-like solitons with potential Reeb vector field on almost paracontact almost paracomplex Riemannian manifolds. The special cases of para-Einstein-like, para-Sasaki-like and having a torse-forming Reeb vector field have been considered. It is proved a necessary and sufficient condition the manifold to admit a para-Ricci-like soliton which is the structure to be para-Einstein-like. Explicit examples are provided in support of the proven statements.

Individual users' payment behaviors have changed. The diffusion of mobile devices makes people suitable for proximity mobile payment (PMP) services without the need for traditional payment. Existing mobile payment literature mainly focuses on users' adoption and continuous usage behavior, nevertheless, switching behavior on payment received little attention, especially focusing on why users switch from traditional payment to PMP. Thus, the objective of the current research is to investigate factors influencing users’ traditional payment - PMP switching to comprehend how these factors shape users’ switching intentions. We developed a traditional payment - PMP transition model based on the push-pull-mooring framework derived from migration theory. This research adopted a structural equation modeling analysis on 311 valid data. The findings indicate that a push factor drives users away from traditional payment in terms of dissatisfaction. The pull factors, including perceived substitutability and perceived usefulness, attract users to PMP. Furthermore, in terms of perceived technical compatibility, a positive mooring factor facilitates users' switching to PMP. The negative mooring factor, in terms of perceived risk, hinder users' switching intention. However, another pull factor - perceived ease of use, failed to influence switching intention significantly. This study found some distinctions between mobile payment switching and mobile payment adoption. These findings provide pivotal insights for mobile payment service providers.

Excessive high fat diet (HFD) consumption can induce food addiction which is believed to involve the communication between the hypothalamus and mesolimbic dopaminergic neurons, originating in the ventral tegmental area (VTA) and projecting to the nucleus accumbens (NAc). These brain regions are densely populated with opioid receptors, raising the possibility that these receptors, and particularly mu opioid receptors (MORs), are involved in mediating reward induced by palatable foods. This study sought to investigate the involvement of MORs in high fat diet (HFD)-induced reward and if there is any difference between male and female subjects in this response. We also assessed if exposure to HFD would potentiate the rewarding action of oxycodone, a relatively selective MOR agonist. The place conditioning paradigm was used to determine if conditioning for a short time (STC, 2 h) or long time (LTC, 16 h) with HFD induces reward or alters the rewarding action of oxycodone. Male and female C57BL/6J mice as well as MOR knockout and wildtype mice of both sexes were tested for basal place preference on day 1 and then conditioned with HFD in one chamber and regular chow diet (RCD) in another chamber and tested for place preference again after three sets of STC and again after a set of LTC. Each set consisted of two conditioning with RCD and two conditioning with HFD. Controls were conditioned with RCD in both conditioning chambers. Following the last place preference test, mice were treated with oxycodone and conditioned in the HFD-paired chamber and saline in the RCD-paired chamber for one hour once a day to explore the possibility if the HFD could alter oxycodone reward. The result showed that HFD induced conditioned place preference (CPP) in both male and female subjects following the LTC. This response was further potentiated after oxycodone conditioning. The latter response was mediated via MORs, as it was blunted in MOR knockout mice. However, HFD-induced CPP was observed following LTC in only female MOR knockout mice, suggesting for sexual dimorphism in this response.

Background: Mucoadhesive polymers represent a major part of site-specific and localized retention strategies in oral drug delivery. Present research was designed to synthesize and characterize a novel mucoadhesive carbohydrate polymer (thiolated gum ghatti; TGG) which was further employed to fabricate mucoadhesive tablets of domperidone using an industrially viable compression coating technique. Methods: Thiolation of gum ghatti was achieved by the ester formation (esterification) between hydroxyl group and carboxyl group of gum ghatti and thioglycolic acid. Results: TGG was characterized by various physico-chemical techniques such as FTIR, XRD, SEM and DSC techniques. In rheological studies, the observed viscosities of pure gum-mucin were 45.45 and 71.75 mPas and that of thiolated gum were 78.7 and 112.58 mPas respectively in water and simulated gastric fluid. Signifi-cant increase in viscosity for thiolated gum may be attributed to increased macromolecular interactions responsible for enhanced mucoadhesive potential of thiolated gum. In-silico studies corroborate the role of mucin gum interaction and energetic stabilization for en-hanced mucoadhesion properties of thiolated gum. Ex-vivo mucoadhesion strength of gum ghatti and thiolated gum ghatti coated tablets was found to be ranging between 4.67± 0.79 to 8.99± 0.75 g and 11.76± 1.34 to 18.83± 2.07 g respectively. Conclusion: Thiolated gum ghatti may be regarded as a promising polymer for developing different mucoadhesive drug delivery systems.

Esculetin is a coumarin compound, which belongs to the class of benzopyrone enriched in various plants such as Sonchus grandifolius, Aesculus turbinata, and many others. Glycosides and caffeic acid conjugates are the common forms of esculetin present in medicinal plants. Esculetin acts as an antioxidant, anti-inflammatory, anti-diabetic, anti-hepatic, and anti-cancer agent by inhibiting the production of free radicals, inflammatory mediators, and genes that cause liver diseases and cancer. It also aids in the regulation of blood sugar. Scientists developing pharmaceutical formulations require some rationale and preliminary studies for drug design, but a small number of clinical studies on humans containing esculetin limit its potential for use as a safe alternative drug. Therefore, in this review article, the published studies have been reviewed to identify the pathogenesis of cancer, oxidative stress, inflammation, arthritis, diabetes and fatty liver along with the discussion on potential therapeutic strategies of esculetin. Advancements in our understanding of these diseases will aid in the development of new and innovative medications for treating many ailments. In conclusion, esculetin has immense potential to be used as a safe drug against many diseases but requires further testing and confirmation through clinical trials.

Density is a crucial parameter for quantitatively describing the physical properties of liquids. It serves as an important indicator for scientific research, production process control, pipeline transportation, and other aspects. In oil pipeline transportation and raw material processing, real-time online measurement of liquid density is of great significance. This paper analyzes the working principle of an on-line vibrating tube densitometer and derives the fitting equation for temperature, pressure, and density；it also conducts experiments with an on-line vibrating tube liquid densitometer and establishes a traceability chain for the experimental device. The experimental setup includes a desktop densitometer system, a multi-temperature field constant temperature stirring system, a walk-in constant temperature box, an automatic blowing system, and a frequency acquisition and calculation system. The uncertainty of the device's evaluation is U= 0.08kg/m3, k=2.The experimental research on the on-line vibrating tube liquid densitometer can be carried out within the range of (650~1400) kg/m3, (10~70)℃, (0~50)bar the metrological performance of the vibrating tube densitometer can be researched by utilizing the straight tube type and the elbow type on-line vibrating tube densitometer. A preliminary study was conducted on the effects of different densities, temperatures, and pressures on the vibrating tube system's vibration cycle. The fit coefficient and error were calculated, and the experimental results were compared to the theoretical analysis to confirm the device's conformity. The study verified the device's scientific and reasonable design, and demonstrated that it is feasible to use the device for follow-up research.

University students, particularly those in the healthcare disciplines, constitute a category of particular interest in regard to COVID-19 vaccines and the attitudes to vaccination, as their future professional role will enable them to inform and educate citizens regarding vaccination. The objectives of the study were to investigate the vaccination coverage with a COVID-19 vaccine among students from different degree programs at the Medical universities in Bulgaria behaviors and attitudes toward vaccination with a COVID-19 vaccine. A prospective cross-sectional study in the period September 2021- March 2022 was conducted. Information on demographics, university program, year of study, general attitudes and behavior towards vaccines and attitudes and personal experience with COVID-19 and COVID-19 vaccines were collected. The chi-square test was used to test for associations and binominal logistic regression was used to identify possible predictors for vaccination. A total of 3050 students with a median age of 22 years, predominantly female took part in the study. Three-thirds of the students (73.5%) have been vaccinated against COVID-19. The main reasons for vaccine hesitancy in both group of students were the fear of side effects and the doubts about the safety of the vaccines although non-vaccinated students significantly more frequently express those fears. Respondents who considered to have: a) limited access to sufficient information to inform COVID-19 vaccine uptake; b) lack of public awareness and education campaigns about effectiveness and safety of COVID-19 vaccines; c) insufficient information about COVID-19 vaccines during the University education; and d) had a positive COVID-19 diagnosis were less likely to be vaccinated. Students who have not completed the mandatory immunization cycle according to country schedule were also less likely to have completed COVID-19 vaccination. The students showed an overall positive attitude towards the COVID-19 vaccines. Promoting informational campaigns that emphasize the vaccine's safety will be more effective to further increase the vaccination coverage with COVID-19 vaccines.