Neurological damage is the pathological substrate of permanent disability in various neurodegenerative disorders. Early detection of this damage, including its identification and quantification, is critical to preventing the disease’s progression in the brain. Tau, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL), as brain protein biomarkers, have the potential to improve diagnostic accuracy, disease monitoring, prognostic assessment, and treatment efficacy. These biomarkers are released into the cerebrospinal fluid (CSF) and blood proportionally to the degree of neuron and astrocyte damage in different neurological disorders, including stroke, traumatic brain injury, multiple sclerosis, neurodegenerative dementia, and Parkinson’s disease. Here, we review how Tau, GFAP, and NfL biomarkers are detected in CSF and blood as crucial diagnostic tools, as well as the levels of these biomarkers used for differentiating a range of neurological diseases and monitoring disease progression. We also discuss a biosensor approach that allows for the real-time detection of multiple biomarkers in various neurodegenerative diseases. This combined detection system of brain protein biomarkers holds significant promise for developing more specific and accurate clinical tools that can identify the type and stage of human neurological diseases with greater precision. Full article

We examined whether the administration of growth hormone (GH) improves insulin resistance in females of a non-obese hyperglycemic mouse model after birth with low birth weight (LBW), given that GH is known to increase muscle mass. The intrauterine Ischemia group underwent uterine artery occlusion for 15 min on day 16.5 of gestation. At 4 weeks of age, female mice in the Ischemia group were divided into the GH-treated (Ischemia-GH) and non-GH-treated (Ischemia) groups. At 8 weeks of age, the glucose metabolism, muscle pathology, and metabolome of liver were assessed. The insulin resistance index improved in the Ischemia-GH group compared with the Ischemia group (p = 0.034). The percentage of type 1 muscle fibers was higher in the Ischemia-GH group than the Ischemia group (p < 0.001); the muscle fiber type was altered by GH. In the liver, oxidative stress factors were reduced, and ATP production was increased in the Ischemia-GH group compared to the Ischemia group (p = 0.014), indicating the improved mitochondrial function of liver. GH administration is effective in improving insulin resistance by increasing the content of type 1 muscle fibers and improving mitochondrial function of liver in our non-obese hyperglycemic mouse model after birth with LBW. Full article

(1) Background: Cardiometabolic disease progression can be delayed if patients engage in healthy lifestyle behaviors, adherence to which is highly influenced by psychosocial factors. The present study aimed at investigating the association of self-efficacy with the adherence level to healthy lifestyle behaviors among patients with cardiometabolic diseases in Greece. (2) Methods: 1988 patients (1180 females) with cardiometabolic diseases participated. Anthropometric, demographic, socioeconomic, clinical, and lifestyle characteristics were recorded. Patients were also asked to evaluate their efficacy to comply with healthy lifestyle behaviors. (3) Results: The majority exhibited unhealthy lifestyle behaviors. A subgroup demonstrated elevated self-efficacy in maintaining healthy habits despite facing diverse psychosocial challenges. Individuals with higher educational attainment, socioeconomic status, and rural/semi-urban residency had significantly elevated self-efficacy. Those with heightened self-efficacy exhibited significantly lower BMI and reduced prevalence of certain health conditions. Self-efficacy significantly influenced adherence to the Mediterranean diet, physical activity engagement, and smoking cessation, even in challenging circumstances. (4) Conclusions: This study represented an innovative approach in examining the role of self-efficacy in shaping health behaviors and outcomes within a Greek population. By integrating specific psychosocial circumstances into the analysis, valuable insights were provided into the contextual factors influencing self-efficacy and adherence to healthy lifestyle behaviors. Full article

This study reviews the application of artificial intelligence (AI) throughout the food value chain and how it can be leveraged to help companies become more sustainable. A literature review across different parts of the food value chain was conducted to provide an overview of the main themes of current and future AI applications throughout the food industry. Moreover, the paper focuses on the benefits and challenges of change management when integrating AI. A documentary Systematic Review using PRISMA research was conducted to find and analyze the aforementioned applications. The key insight is that change progress varies significantly. Today’s applications are primarily found within food inspection and quality assurance due to relatively straightforward AI applications in the value chain. Such technology is mainly image-based. Companies can use the interconnectedness of AI and sustainability by becoming more efficient through AI and simultaneously saving emissions and resources through optimizing processes. Full article

Under the influence of tourism and globalization, heritage production presents a new landscape. As a crucial framework for interpreting heritage, Authorized Heritage Discourse (AHD) has profound significance in discussing its practice characteristics in this context. Taking cities along the Jiangsu–Zhejiang section of the Grand Canal as a case study and drawing upon policy text, this study explores the practice characteristics of AHD in the tourism context. Results indicate that the thematic practices of AHD encompass protection and management, ecological construction, cultural production and inheritance, touristification, infrastructure and services, and marketing and cooperation, forming a clustering pattern with touristification as the central theme. The spatial characteristics manifest as multi-scale practices ranging from global to regional to local, each corresponding to diverse thematic characteristics. This study deepens the understanding of AHD in tourism and advances the research progress of heritage tourism. It also provides practical references for the utilization of urban heritage and the management of heritage tourism. Full article

Background: Lipids, as a fundamental cell component, play an regulating role in controlling the different cellular biological processes involved in viral infections. A notable feature of coronavirus disease 2019 (COVID-19) is impaired lipid metabolism. The function of lipophagy-related genes in COVID-19 is unknown. The present study aimed to investigate biomarkers and drug targets associated with lipophagy and lipophagy-based therapeutic agents for COVID-19 through bioinformatics analysis. Methods: Lipophagy-related biomarkers for COVID-19 were identified using machine learning algorithms such as random forest, Support Vector Machine-Recursive Feature Elimination, Generalized Linear Model, and Extreme Gradient Boosting in three COVID-19-associated GEO datasets: scRNA-seq (GSE145926) and bulk RNA-seq (GSE183533 and GSE190496). The cMAP database was searched for potential COVID-19 medications. Results: The lipophagy pathway was downregulated, and the lipid droplet formation pathway was upregulated, resulting in impaired lipid metabolism. Seven lipophagy-related genes, including ACADVL, HYOU1, DAP, AUP1, PRXAB2, LSS, and PLIN2, were used as biomarkers and drug targets for COVID-19. Moreover, lipophagy may play a role in COVID-19 pathogenesis. As prospective drugs for treating COVID-19, seven potential downregulators (phenoxybenzamine, helveticoside, lanatoside C, geldanamycin, loperamide, pioglitazone, and trichostatin A) were discovered. These medication candidates showed remarkable binding energies against the seven biomarkers. Conclusions: The lipophagy-related genes ACADVL, HYOU1, DAP, AUP1, PRXAB2, LSS, and PLIN2 can be used as biomarkers and drug targets for COVID-19. Seven potential downregulators of these seven biomarkers may have therapeutic effects for treating COVID-19. Full article

Carbonate rocks are important for the petroleum industry, as they contribute significantly to hydrocarbon reserves, although their analysis is complex due to the high cost of core sampling and their high heterogeneity; for this, synthetic rocks aim to provide relatively homogeneous samples with analogous characteristics to natural rocks. In this research, synthetic carbonate rocks were produced by mixing a fixed ratio between limestone powder, obtained from limestone mining waste, and epoxy resin as a cementing material, using compaction energy for consolidation. The work aimed to produce homogeneous samples with high strength, reproducing the intergranular pore system for future applications in rock–fluid interaction analysis. The characteristics and structure of the samples were investigated through X-ray computed microtomography, petrographic images, petrophysical, chemical and geomechanical tests. Results showed a direct increasing relationship between porosity and permeability and a tendency for mechanical strength (UCS) to decrease with increasing porosity. When compared with the natural carbonate rocks, these presented similarities in their mechanical properties and petrophysical measurements, showing that the methodology can be considered as an alternative for the obtention of a realistic material that can be used for future experiments regarding rock mechanics and rock–fluid interaction for prediction of carbonate rocks’ behavior. Full article

Raphanus sativus L. is a potential source of raw material for biodiesel fuel due to the high oil content in its grains. In Brazil, this species is cultivated in the low rainfall off-season, which limits the productivity of the crop. The present study investigated the effects of water restriction on the physiological and biochemical responses, production components, and oil quality of R. sativus at different development stages. The treatments consisted of 100% water replacement (control), 66%, and 33% of field capacity during the phenological stages of vegetative growth, flowering, and grain filling. We evaluated characteristics of water relations, gas exchange, chlorophyll a fluorescence, chloroplast pigment, proline, and sugar content. The production components and chemical properties of the oil were also determined at the end of the harvest cycle. Drought tolerance of R. sativus was found to be mediated primarily during the vegetative growth stage by changes in photosynthetic metabolism, stability of photochemical efficiency, increased proline concentrations, and maintenance of tissue hydration. Grain filling was most sensitive to water limitation and showed a reduction in yield and oil content. However, the chemical composition of the oil was not altered by the water deficit. Our data suggest that R. sativus is a drought-tolerant species. Full article

The European Union faces the pressing challenge of decarbonising the buildings sector to meet its climate neutrality goal by 2050. Buildings are significant contributors to greenhouse gas emissions, primarily through energy consumption for heating and cooling. This study uses the advanced PRIMES-BuiMo model to develop state-of-the-art innovative pathways and strategies to decarbonise the EU buildings sector, providing insights into energy consumption patterns, renovation rates and equipment replacement dynamics in the EU and in two representative Member States, Sweden and Greece. The model-based analysis shows that the EU’s transition towards climate neutrality requires significant investment in energy efficiency of buildings combined with decarbonisation of the fuel mix, mostly through the uptake of electric heat pumps replacing the use of fossil fuels. The Use Case also demonstrates that targeted policy interventions considering the national context and specificities are required to ensure an efficient and sustainable transition to zero-emission buildings. The analysis of transformational strategies in Greece and Sweden provides an improved understanding of the role of country-specific characteristics on policy effectiveness so as to inform more targeted and contextually appropriate approaches to decarbonise the buildings sector across the EU. Full article

Semi-supervised training methods need reliable pseudo labels for unlabeled data. The current state-of-the-art methods based on pseudo labeling utilize only high-confidence predictions, whereas poor confidence predictions are discarded. This paper presents a novel approach to generate high-quality pseudo labels for unlabeled data. It utilizes predictions with high- and low-confidence levels to generate refined labels and then validates the accuracy of those predictions through bi-directional object tracking. The bi-directional object tracker leverages both past and future information to recover missing labels and increase the accuracy of the generated pseudo labels. This method can also substantially reduce the effort and time needed in label creation compared to the conventional manual labeling. The proposed method utilizes a buffer to accumulate detection labels (bounding boxes) predicted by the object detector. These labels are refined for accuracy though forward and backward tracking, ultimately constructing the final set of pseudo labels. The method is integrated in the YOLOv5 object detector and tested on the BDD100K dataset. Through the experiments, we demonstrate the effectiveness of the proposed scheme in automating the process of pseudo label generation with notably higher accuracy than the recent state-of-the-art pseudo label generation schemes. The results show that the proposed method outperforms previous methods in terms of mean average precision (mAP), label generation accuracy, and speed. Using the bi-directional recovery method, an increase in mAP@50 for the BDD100K dataset by 0.52% is achieved, and for the Waymo dataset, it provides an improvement of mAP@50 by 8.7% to 9.9% compared to 8.1% of the existing method when pre-training with 10% of the dataset. An improvement by 2.1% to 2.9% is achieved as compared to 1.7% of the existing method when pre-training with 20% of the dataset. Overall, the improved method leads to a significant enhancement in detection accuracy, achieving higher mAP scores across various datasets, thus demonstrating its robustness and effectiveness in diverse conditions. Full article

This phenomenological qualitative study examined the lived experience of pediatric nurse residents’ transition to practice during the COVID-19 pandemic. The purposive sample included nine pediatric nurses, participating in a nurse residency program, who entered the nursing profession during the first year of the pandemic. The setting was a free-standing, Magnet-recognized, pediatric academic medical center in the Northeastern U.S. Individual interviews were audio recorded and transcribed. Narratives were analyzed using a hermeneutic phenomenological approach. Five themes emerged from the data: Our New Normal; The Rules Keep Changing; I’m Not Ready for This (transition to practice); The Toll of COVID; and Shattered Family-Centered Care. Sub-themes emerged in The Toll of COVID theme: COVID and the Nursing Care Environment, Emotional Toll of COVID, Burnout: A Universal Truth, and The Pandemic within the Pandemic. The nurse residents’ narratives uncovered the essence of their uncertainty, sorrow, growth, and resilience. Through the eyes of pediatric nurse residents, this study illuminated the experiences of these novices as they entered the nursing profession amid a pandemic. Full article

To ensure precise positioning of the macro–micro platform with a symmetrical structure, it is crucial to mitigate the impact of various perturbations, including disturbances, as well as complex factors such as external loads, electrical noise, and model parameter variations. This paper proposes a novel macro–micro master–slave control structure that incorporates adaptive fuzzy linear active disturbance rejection control (AFLADRC). The K_p and K_d parameters of the linear state error feedback (LSEF) are dynamically tuned and adjusted using fuzzy reasoning. This approach enhances the robustness of the system and simplifies the tuning process. In addition, this paper also analyzes the symmetry of the coupling effect between macro and micro, as the coupling will affect the motor force and the reaction potential of the motor. The macro–micro platform adopts a symmetric design; the macro stage is driven by a permanent magnet synchronous linear motor (PMLSM), and the micro stage is driven by a voice coil motor. Finally, we built the macro–micro linear motion experimental platform to verify the control effect of the proposed method by conducting trajectory tracking experiments and comparison experiments. Full article

The LSTM neural network is often employed for time-series data prediction due to its strong nonlinear mapping capability and memory effect, allowing for better identification of complex data characteristics. However, the large computational workload required by neural networks can result in longer prediction times, making deployment on time-sensitive embedded devices challenging. To address this, TensorRT, a software development kit for NVIDIA hardware platforms, offers optimized network structures and reduced inference times for deep learning inference applications. Though TensorRT inference is GPU-based like other deep learning frameworks, TensorRT outperforms comparable frameworks in terms of inference speed. In this paper, we compare the inference time consumption and prediction deviation of various approaches on CPU, GPU, and TensorRT, while also exploring the effects of different quantization approaches. Our experiments demonstrate the accuracy and inference latency of the same model on the FPGA development board PYNQ-Z1 as well, though the best results were obtained using NVIDIA Jetson Xavier NX. The results show an approximately 50× improvement in inference speed compared to our previous technique, with only a 0.2% increase in Mean Absolute Percentage Error (MAPE). These works highlight the effectiveness and efficiency of TensorRT in reducing inference times, making it an excellent choice for time-sensitive embedded device deployments that require high precision and low latency. Full article

Process design critically depends on the characterization of fuels and their kinetics under process conditions. This study steps beyond the fundamental methods of thermogravimetry to modulated (MTGA) and Hi-Res™ (high resolution) techniques to (1) add characterization detail and (2) increase the utility of thermal analysis data. Modulated TGA methods overlay sinusoidal functions on the heating rates to determine activation energy as a function of temperature with time. Under devolatilization conditions, Hi-Res™ TGA maintains a constant mass loss with time and temperature. These two methods, run independently or overlaid, offer additional analysis in which multiple samples at different heating rates are run to different final temperatures. Advanced methods allow researchers to use fewer samples by conducting fewer runs, targeting practical experimental designs, and quantifying errors easier. The parameters of the studies included here vary the heating rate at 10, 30, and 50 °C/min; vary gas-phase oxygen for pyrolysis or combustion conditions; and particle size ranges of 100–125 µm, 400–425 µm, and 600–630 µm. The two biomass fuels used in the studies are pinewood from Northern Sweden and wheat straw. The influence of torrefaction is also included at temperatures of 220, 250, and 280 °C. Apparent activation energy results align with the previous MTGA data in that combustion conditions yield higher values than pyrolysis conditions—200–250 kJ/mol and 175–225 kJ/mol for pine and wheat combustion, respectively, depending on pre-treatment. Results show the dependence of these parameters upon one another from a traditional thermal analysis approach, e.g., the Ozawa-Flynn-Wall method, as well as MTGA and Hi-Res™ thermogravimetric investigations to show future directions for thermal analysis techniques. Full article

The width of a stop-mining coal pillar is of great significance to the stability of the surrounding rock of the main roadway and the safety of production in the mine. This paper focuses on the west panel of Sihe Coal Mine as the engineering background, analyzes the evolution characteristics of front abutment pressure in the mining area under conditions of rapid advancement and large mining height and its sensitivity to influencing factors, explores the coupling mechanism between the width of the stop-mining coal pillar and the surrounding rock of the main roadway, and analyzes the differences in mining pressure characteristics such as internal stress of the coal pillar, vertical stress, deformation, and failure of the main roadway’s surrounding rock under different coal pillar widths with the influence of mining. The comprehensive results indicate that the influence range of front abutment pressure on the working face is 65 m, and the significance ranking of different mining factors acting on it is as follows: mining height > working face length > advancing speed. The rational width of the stop-mining coal pillar is determined to be 80 m while the stress field of the surrounding rock in the main roadway is in a critical state of mining disturbance. Industrial tests have shown that the relative displacements between the roof and floor as well as the ribs of the main roadway are relatively small, at 105 and 260 mm, respectively, which can effectively maintain the stability of the surrounding rock of the main roadway. The research results can provide a scientific basis and engineering reference for the design of stop-mining coal pillars in mines with similar geological conditions. Full article

While scholars have long recognized the central importance of the cross within Syriac-speaking Christian communities in late antique Mesopotamia, the question of how physical crosses functioned as aids for prayer has only recently begun to be explored. The present article addresses this question with respect to East Syrian monastic communities in seventh-century Mesopotamia, focusing on the context of the monastic cell. Bringing together accounts of cross-directed prayer in Syriac monastic literature with archaeological evidence for crosses from the region, the article concludes that physical crosses played an important role as mediating devices of divine presence that were both always at hand and the frequent objects of monastics’ sensorial attention. These conclusions are subsequently discussed through the lens of recent research from the field of new media studies toward the goal of understanding how cross-directed prayer may have served to bridge monastic spirituality and sociality in Mesopotamia. Full article

This article presents the case of a 27-year-old female patient with idiopathic congenital complete heart block who does not consent to the implantation of a cardiac pacemaker but was referred by her primary care physician for cardiological evaluation. The conduction disturbance was recognized at the age of 6 and was asymptomatic. The professional disqualification from pacemaker implantation included a detailed history of a patient’s symptoms, an echocardiographic assessment of the heart, exercise testing and ECG Holter monitoring. The aid of salbutamol administered orally was also useful. Full article

We previously reported that nano-pulse treatment (NPT), a pulsed power technology, resulted in 4T1-luc mammary tumor elimination and a strong in situ vaccination, thereby completely protecting tumor-free animals against a second live tumor challenge. The mechanism whereby NPT mounts effective antitumor immune responses in the 4T1 breast cancer predominantly immunosuppressive tumor microenvironment (TME) remains unanswered. In this study, orthotopic 4T1 mouse breast tumors were treated with NPT (100 ns, 50 kV/cm, 1000 pulses, 3 Hz). Blood, spleen, draining lymph nodes, and tumors were harvested at 4-h, 8-h, 1-day, 3-day, 7-day, and 3-month post-treatment intervals for the analysis of frequencies, death, and functional markers of various immune cells in addition to the suppressor function of regulatory T cells (Tregs). NPT was verified to elicit strong in situ vaccination (ISV) against breast cancer and promote both acute and long-term T cell memory. NPT abolished immunosuppressive dominance systemically and in the TME by substantially reducing Tregs, myeloid-derived suppressor cells (MDSCs), and tumor-associated macrophages (TAMs). NPT induced apoptosis in Tregs and TAMs. It also functionally diminished the Treg suppression capacity, explained by the downregulation of activation markers, particularly 4-1BB and TGFβ, and a phenotypic shift from predominantly activated (CD44⁺CD62L⁻) to naïve (CD44⁻CD62L⁺) Tregs. Importantly, NPT selectively induced apoptosis in activated Tregs and spared effector CD4⁺ and CD8⁺ T cells. These changes were followed by a concomitant rise in CD8⁺CD103⁺ tissue-resident memory T cells and TAM M1 polarization. These findings indicate that NPT effectively switches the TME and secondary lymphatic systems from an immunosuppressive to an immunostimulatory state, allowing cytotoxic T cell function and immune memory formation to eliminate cancer cells and account for the NPT in situ vaccination. Full article

Intensive increases in electrical energy storage are being driven by electric vehicles (EVs), smart grids, intermittent renewable energy, and decarbonization of the energy economy. Advanced lithium–sulfur batteries (LSBs) are among the most promising candidates, especially for EVs and grid-scale energy storage applications. In this topical review, the recent progress and perspectives of practical LSBs are reviewed and discussed; the challenges and solutions for these LSBs are analyzed and proposed for future practical and large-scale energy storage applications. Major challenges for the shuttle effect, reaction kinetics, and anodes are specifically addressed, and solutions are provided on the basis of recent progress in electrodes, electrolytes, binders, interlayers, conductivity, electrocatalysis, artificial SEI layers, etc. The characterization strategies (including in situ ones) and practical parameters (e.g., cost-effectiveness, battery management/modeling, environmental adaptability) are assessed for crucial automotive/stationary large-scale energy storage applications (i.e., EVs and grid energy storage). This topical review will give insights into the future development of promising Li–S batteries toward practical applications, including EVs and grid storage. Full article

Tooth decay, also known as caries, is a significant medical problem that harms teeth. Treatment is based on the removal of the carious material and then filling the cavity left in the tooth, most commonly with amalgam or composite resin. The consequences of filling failure include repeating the filling or performing another treatment such as a root canal or extraction. Dental amalgam contains mercury, and there is a global effort to reduce its use. However, no consensus has been reached regarding whether amalgam or composite resin materials are more durable, and which is the best restorative material, when using randomized clinical trials. To determine which material is superior, we performed a retrospective cohort study using a large database where the members of 58 dental clinics with 440 dental units were treated. The number of failures of the amalgam compared to composite resin restorations between 2014 and 2021 were compared. Our data included information from over 650,000 patients. Between 2014–2021, 260,905 patients were treated. In total, 19,692 out of the first 113,281 amalgam restorations failed (17.49%), whereas significantly fewer composite restorations failed (11.98%) with 65,943 out of 555,671. This study indicates that composite is superior to amalgam and therefore it is reasonable to cease using mercury-containing amalgam. Full article

Platelets have a fundamental role in mediating hemostasis and thrombosis. However, more recently, a new idea is making headway, highlighting the importance of platelets as significant actors in modulating immune and inflammatory responses. In particular, platelets have an important role in the development of vascular amyloid-b-peptide(ab) deposits, known to play a relevant role in Alzheimer’s disease (AD) through accumulation and deposition within the frontal cortex and hippocampus in the brain. The involvement of platelets in the pathogenesis of AD opens up the highly attractive possibility of applying antiplatelet therapy for the treatment and/or prevention of AD, but conclusive results are scarce. Even less is known about the potential role of platelets in mild cognitive impairment (MCI). The aim to this brief review is to summarize current knowledge on this topic and to introduce the new perspectives on the possible role of platelet activation as therapeutic target both in AD and MCI. Full article