This work aimed to study the atmospheric boundary layer height (ABLH) from COSMIC-2 refractivity data, endeavoring to refine existing ABLH detection algorithms and scrutinize the resulting spatial and seasonal distributions. Through validation analyses involving different ground-based methodologies (involving data from lidar, ceilometer, microwave radiometers, and radiosondes), the optimal ABLH determination relied on identifying the lowest refractivity gradient negative peak with a magnitude at least $\tau$% times the minimum refractivity gradient magnitude, where $\tau$ is a fitting parameter representing the minimum peak strength relative to the absolute minimum refractivity gradient. Different $\tau$ values were derived accounting for the moment of the day (daytime, nighttime, or sunrise/sunset) and the underlying surface (land or sea). Results show discernible relations between ABLH and various features, notably, the land cover and latitude. On average, ABLH is higher over oceans (≈1.5 km), but extreme values (maximums > 2.5 km, and minimums < 1 km) are reached over intertropical lands. Variability is generally subtle over oceans, whereas seasonality and daily evolution are pronounced over continents, with higher ABLHs during daytime and local wintertime (summertime) in intertropical (middle) latitudes. Full article

This research examines the ways people acquire dogs in the US as well as the ways the dogs leave the household and the way these differ by income level in seven geographically diverse study communities. A web-based panel survey was distributed and received 6318 responses. Individuals were asked a series of demographic and socioeconomic questions as well as how they acquired their current dogs, how previous dogs left their household, and where they left to. The results indicate that the likelihood of acquiring a dog through friends and family decreased monotonically as income increased, while the opposite was observed for adopting and purchasing a dog. The likelihood of giving a dog away to a friend or family member also decreased as income increased, as opposed to shelter surrender—a person earning over USD 100,000 annually was more than four times likelier to surrender to a shelter than a person earning under USD 15,000. The results suggest a stronger reliance on informal social networks in lower-income communities for both obtaining and placing dogs. As these dogs would otherwise end up in the shelter system, animal shelters may support low-income pet owners to help keep their dogs within their community of care. Full article

The potential for native proteins to serve as a platform for biocompatible, targeted, and personalized therapeutics in the context of genetic and metabolic disorders is vast. Nevertheless, their clinical application encounters challenges, particularly in overcoming biological barriers and addressing the complexities involved in engineering transmembrane permeability. This study is dedicated to the development of a multifunctional nanoentity in which a model therapeutic protein is covalently linked to a cell-penetrating peptide, NickFect 55, with the objective of enhancing its intracellular delivery. Successful binding of the nanoentity fragments was achieved through the utilization of an intein-mediated protein-trans splicing reaction. Our research demonstrates that the fully assembled nanoentity-containing protein was effectively internalized by the cells, underscoring the potential of this approach in overcoming barriers associated with protein-based therapeutics for the treatment of genetic disorders. Full article

Plasma technology is increasing its applications in the textile industry for conferring surface functionalities through greener processes. In this study, plasma treatments are studied to improve the wettability of mycelium-based material, an emerging material with a lot of potential in the near future. The plasma effect was characterized by assessing the added functionality (wettability) and inspecting surface modifications with different techniques, such as scanning electron microscopy (SEM) and X-Ray photoelectron spectroscopy (XPS). Low pressure plasma (LPP) treatments were successfully applied into the mycelium-based material and optimal power of discharge and treatment time were set for this material (750 W, 17.5 min). With the optimized LPP treatments, the water absorption capacity of mycelium-based material was improved by 2000% and some surface morphological modifications were observed by SEM analysis. On the other hand, XPS analysis demonstrated how the plasma treatment changes the surface composition. Full article

Adversarial attacks are more prevalent in Consumer Internet of Things (CIoT) devices (i.e., smart home devices, cameras, actuators, sensors, and micro-controllers) because of their growing integration into daily activities, which brings attention to their possible shortcomings and usefulness. Keeping protection in the CIoT and countering emerging risks require constant updates and monitoring of these devices. Machine learning (ML), in combination with Explainable Artificial Intelligence (XAI), has become an essential component of the CIoT ecosystem due to its rapid advancement and impressive results across several application domains for attack detection, prevention, mitigation, and providing explanations of such decisions. These attacks exploit and steal sensitive data, disrupt the devices’ functionality, or gain unauthorized access to connected networks. This research generates a novel dataset by injecting adversarial attacks into the CICIoT2023 dataset. It presents an adversarial attack detection approach named TXAI-ADV that utilizes deep learning (Mutli-Layer Perceptron (MLP) and Deep Neural Network (DNN)) and machine learning classifiers (K-Nearest Neighbor (KNN), Support Vector Classifier (SVC), Gaussian Naive Bayes (GNB), ensemble voting, and Meta Classifier) to detect attacks and avert such situations rapidly in a CIoT. This study utilized Shapley Additive Explanations (SHAP) techniques, an XAI technique, to analyze the average impact of each class feature on the proposed models and select optimal features for the adversarial attacks dataset. The results revealed that, with a 96% accuracy rate, the proposed approach effectively detects adversarial attacks in a CIoT. Full article

Multiple myeloma (MM), the second most common hematologic malignancy, remains incurable, and its incidence is rising. Chimeric Antigen Receptor T-cell (CAR-T cell) therapy has emerged as a novel treatment, with the potential to improve the survival and quality of life of patients with relapsed/refractory multiple myeloma (rrMM). In this systematic review and meta-analysis, conducted in accordance with PRISMA guidelines, we aim to provide a concise overview of the latest developments in CAR-T therapy, assess their potential implications for clinical practice, and evaluate their efficacy and safety outcomes based on the most up-to-date evidence. A literature search conducted from 1 January 2019 to 12 July 2023 on Medline/PubMed, Scopus, and Web of Science identified 2273 articles, of which 29 fulfilled the specified criteria for inclusion. Our results offer robust evidence supporting CAR-T cell therapy’s efficacy in rrMM patients, with an encouraging 83.21% overall response rate (ORR). A generally safe profile was observed, with grade ≥ 3 cytokine release syndrome (CRS) at 7.12% and grade ≥ 3 neurotoxicity at 1.37%. A subgroup analysis revealed a significantly increased ORR in patients with fewer antimyeloma regimens, while grade ≥ 3 CRS was more common in those with a higher proportion of high-risk cytogenetics and prior exposure to BCMA therapy. Full article

At the moment, there are two neutron star X-ray binaries with massive red supergiants as donors. Recently, De et al. (2023) proposed that the system SWIFT J0850.8-4219 contains a neutron star at the propeller stage. We study this possibility by applying various models of propeller spin-down. We demonstrate that the duration of the propeller stage is very sensitive to the regime of rotational losses. Only in the case of a relatively slow propeller model proposed by Davies and Pringle in 1981, the duration of the propeller is long enough to provide a significant probability to observe the system at this stage. Future determination of the system parameters (orbital and spin periods, magnetic field of the compact object, etc.) will allow putting strong constraints on the propeller behavior. Full article

In mechanical equipment, rolling bearing components are constantly exposed to intricate and diverse environmental conditions, rendering them vulnerable to wear, performance degradation, and potential malfunctions. To precisely extract and discern rolling bearing vibration signals amidst intricate noise interference, this paper introduces a fault feature extraction and diagnosis methodology that seamlessly integrates an improved Fourier decomposition method (FDM), singular value decomposition (SVD), and maximum second-order cyclostationary blind convolution (CYCBD). Initially, the FDM is employed to meticulously decompose the bearing fault signals into numerous signal components. Subsequently, a comprehensive weighted screening criterion is formulated, aiming to strike a balance between multiple indicators, thereby enabling the selective screening and reconstruction of pertinent signal components. Furthermore, SVD and CYCBD techniques are introduced to carry out intricate processing and envelope demodulation analysis of the reconstructed signals. Through rigorous simulation experiments and practical rolling bearing fault diagnosis tests, the method’s noteworthy effectiveness in suppressing noise interference, enhancing fault feature information, and efficiently extracting fault features is unequivocally demonstrated. Furthermore, compared to traditional time–frequency analysis methods such as EMD, EEMD, ITD, and VMD, as well as traditional deconvolution methods like MED, OMEDA, and MCKD, this method exhibits significant advantages, providing an effective solution for diagnosing rolling bearing faults in environments with strong background noise. Full article

Heart failure (HF) is a complex clinical syndrome associated with significant morbidity, mortality, and healthcare costs. It is characterized by various structural and/or functional abnormalities of the heart, resulting in elevated intracardiac pressure and/or inadequate cardiac output at rest and/or during exercise. These dysfunctions can originate from a variety of conditions, including coronary artery disease, hypertension, cardiomyopathies, heart valve disorders, arrhythmias, and other lifestyle or systemic factors. Identifying the underlying cause is crucial for detecting reversible or treatable forms of HF. Recent epidemiological studies indicate that there has not been an increase in the incidence of the disease. Instead, patients seem to experience a chronic trajectory marked by frequent hospitalizations and stagnant mortality rates. Managing these patients requires a multidisciplinary approach that focuses on preventing disease progression, controlling symptoms, and preventing acute decompensations. In the outpatient setting, patient self-care plays a vital role in achieving these goals. This involves implementing necessary lifestyle changes and promptly recognizing symptoms/signs such as dyspnea, lower limb edema, or unexpected weight gain over a few days, to alert the healthcare team for evaluation of medication adjustments. Traditional methods of HF monitoring, such as symptom assessment and periodic clinic visits, may not capture subtle changes in hemodynamics. Sensor-based technologies offer a promising solution for remote monitoring of HF patients, enabling early detection of fluid overload and optimization of medical therapy. In this review, we provide an overview of the CardioMEMS device, a novel sensor-based system for pulmonary artery pressure monitoring in HF patients. We discuss the technical aspects, clinical evidence, and future directions of CardioMEMS in HF management. Full article

In the moist environment of soil-water-air, there is a problem of low accuracy in monitoring volatile organic compounds (VOCs) using a photoionization detector (PID). This study is based on the PID water-soil-gas VOC online monitor developed by this group, online monitoring of the concentration of different constituents of VOCs in different production enterprises of the petroleum and chemical industries in Shandong Province, with the concentration of the laboratory test, to build a relevant model. The correlation coefficient about the PID test concentration and the actual concentration correlation coefficient was obtained through the collection of a large number of data trainings. Based on the application of PID in VOC monitoring, the establishment of a PID high-precision calibration model is important for the precise monitoring of VOCs. In this paper, multiple quantitative analyses were conducted, based on SVM regression of PID response to VOC signals, to study the high-precision VOC monitoring method. To select the response signals of PID under different concentrations of environmental VOCs measured by the research group, first, the PID response to VOC signals was modeled using the support vector machine principle to verify the effect of traditional SVM regression. For the problem of raw data redundancy, calculate the time-domain and frequency-domain characteristics of the PID signal, and conduct the principal component analysis of the time-domain of the PID signal. In order to make the SVM regression more generalized and robust, the selection of kernel function parameters and penalty factor of SVM is optimized by genetic algorithm. By comparing the accuracy of PID calibration models such as PID signal feature extraction, SVM regression, and principal component analysis SVM regression, the superiority of photoionization detector using the signal feature extraction PCA-GA-SVM method to monitor VOCs is verified. Full article

Pain is a complex and multifaceted experience. Recent research has increasingly focused on the role of endoplasmic reticulum (ER) stress in the induction and modulation of pain. The ER is an essential organelle for cells and plays a key role in protein folding and calcium dynamics. Various pathological conditions, such as ischemia, hypoxia, toxic substances, and increased protein production, may disturb protein folding, causing an increase in misfolding proteins in the ER. Such an overload of the folding process leads to ER stress and causes the unfolded protein response (UPR), which increases folding capacity in the ER. Uncompensated ER stress impairs intracellular signaling and cell function, resulting in various diseases, such as diabetes and degenerative neurological diseases. ER stress may be a critical universal mechanism underlying human diseases. Pain sensations involve the central as well as peripheral nervous systems. Several preclinical studies indicate that ER stress in the nervous system is enhanced in various painful states, especially in neuropathic pain conditions. The purpose of this narrative review is to uncover the intricate relationship between ER stress and pain, exploring molecular pathways, implications for various pain conditions, and potential therapeutic strategies. Full article

The traditional design method for terahertz metasurface biosensors is cumbersome and time-consuming, requires expertise, and often leads to significant discrepancies between expected and actual values. This paper presents a novel approach for the fast, efficient, and convenient inverse design of THz metasurface sensors, leveraging convolutional neural network techniques based on deep learning. During the model training process, the magnitude data of the scattering parameters collected from the numerical simulation of the THz metasurface served as features, paired with corresponding surface structure matrices as labels to form the training dataset. During the validation process, the thoroughly trained model precisely predicted the expected surface structure matrix of a THz metasurface. The results demonstrate that the proposed algorithm realizes time-saving, high-efficiency, and high-precision inversion methods without complicated data preprocessing and additional optimization algorithms. Therefore, deep learning algorithms offer a novel approach for swiftly designing and optimizing THz metasurface sensors in biomedical detection, bypassing the complex and specialized design process of electromagnetic devices, and promising extensive prospects for their application in the biomedical field. Full article

Recent increases in gas-fired power generation have engendered increased interdependencies between natural gas and power transmission systems. These interdependencies have amplified existing vulnerabilities in gas and power grids, where disruptions can require the curtailment of load in one or both systems. Although typically operated independently, coordination of these systems during severe disruptions can allow for targeted delivery to lifeline services, including gas delivery for residential heating and power delivery for critical facilities. To address the challenge of estimating maximum joint network capacities under such disruptions, we consider the task of determining feasible steady-state operating points for severely damaged systems while ensuring the maximal delivery of gas and power loads simultaneously, represented mathematically as the nonconvex joint Maximal Load Delivery (MLD) problem. To increase its tractability, we present a mixed-integer convex relaxation of the MLD problem. Then, to demonstrate the relaxation’s effectiveness in determining bounds on network capacities, exact and relaxed MLD formulations are compared across various multi-contingency scenarios on nine joint networks ranging in size from 25 to 1191 nodes. The relaxation-based methodology is observed to accurately and efficiently estimate the impacts of severe joint network disruptions, often converging to the relaxed MLD problem’s globally optimal solution within ten seconds. Full article

Alberta’s forest industry is predicted to be impacted by a medium-term decline in timber supply. Intensive silviculture tools, such as pre-commercial thinning, have been shown to increase individual tree growth, shorten rotation lengths, and improve stand merchantability in important commercial species such as lodgepole pine. However, lodgepole pine stands are susceptible to western gall rust infections, and thinning at an early stage may increase infection rates. This study collected tree and stand level data from 33 operational harvest origin lodgepole pine stands consisting of 11 stands thinned at age 17–19 years (PCT_18), 11 stands thinned at age 23–25 (PCT_24), and 11 unthinned stands. Approximately 40 years after pre-commercial thinning, merchantable volume is similar in all stands but thinned stands, regardless of timing, had greater individual tree size (~15% higher) compared to unthinned stands. Pre-commercially thinned stands also had a higher potential for commercial thinning since they have lower variability in tree size and longer live crown lengths. In addition, delayed thinning (PCT_24) reduced western gall rust infections and the severity of infections compared to both PCT_18 and unthinned stands. In conclusion, pre-commercial thinning should be considered for lodgepole pine stands in order to address timber supply issues in Alberta. Full article

The skin wound healing process consists of hemostatic, inflammatory, proliferative, and maturation phases, with a complex cellular response by multiple cell types in the epidermis, dermis, and immune system. Magnesium is a mineral essential for life, and although magnesium treatment promotes cutaneous wound healing, the molecular mechanism and timing of action of the healing process are unknown. This study, using human epidermal-derived HaCaT cells and human normal epidermal keratinocyte cells, was performed to investigate the mechanism involved in the effect of magnesium on wound healing. The expression levels of epidermal differentiation-promoting factors were reduced by MgCl₂, suggesting an inhibitory effect on epidermal differentiation in the remodeling stage of the late wound healing process. On the other hand, MgCl₂ treatment increased the expression of matrix metalloproteinase-7 (MMP7), a cell migration-promoting factor, and enhanced cell migration via the MEK/ERK pathway activation. The enhancement of cell migration by MgCl₂ was inhibited by MMP7 knockdown, suggesting that MgCl₂ enhances cell migration which is mediated by increased MMP7 expression. Our results revealed that MgCl₂ inhibits epidermal differentiation but promotes cell migration, suggesting that applying magnesium to the early wound healing process could be beneficial. Full article

The global issue for proton exchange membrane fuel cell market development is a reduction in the device cost through an increase in efficiency of the oxygen reduction reaction occurring at the cathode and an extension of the service life of the electrochemical device. Losses in the fuel cell performance are due to various degradation mechanisms in the catalytic layers taking place under conditions of high electric potential, temperature, and humidity. This review is devoted to recent advances in the field of increasing the efficiency and durability of electrocatalysts and other electrode materials by introducing structured carbon components into their composition. The main synthesis methods, physicochemical and electrochemical properties of materials, and performance of devices on their basis are presented. The main correlations between the composition and properties of structured carbon electrode materials, which can provide successful solutions to the highlighted issues, are revealed. Full article

Investigating the role of podocytes in proteinuric disease is imperative to address the increasing global burden of chronic kidney disease (CKD). Studies strongly implicate increased levels of monocyte chemoattractant protein-1 (MCP-1/CCL2) in proteinuric CKD. Since podocytes express the receptor for MCP-1 (i.e., CCR2), we hypothesized that podocyte-specific MCP-1 production in response to stimuli could activate its receptor in an autocrine manner, leading to further podocyte injury. To test this hypothesis, we generated podocyte-specific MCP-1 knockout mice (Podo-Mcp-1^fl/fl) and exposed them to proteinuric injury induced by either angiotensin II (Ang II; 1.5 mg/kg/d, osmotic minipump) or Adriamycin (Adr; 18 mg/kg, intravenous bolus). At baseline, there were no between-group differences in body weight, histology, albuminuria, and podocyte markers. After 28 days, there were no between-group differences in survival, change in body weight, albuminuria, kidney function, glomerular injury, and tubulointerstitial fibrosis. The lack of protection in the knockout mice suggests that podocyte-specific MCP-1 production is not a major contributor to either Ang II- or Adr-induced glomerular disease, implicating that another cell type is the source of pathogenic MCP-1 production in CKD. Full article

Water scarcity is an important threat to food security in the Tigris–Euphrates river system. Water scarcity is a huge worldwide problem that results from the rapid increase in water demand, which exceeds the amount of available water. The most significant problems currently affecting countries are food insecurity water scarcity. The Tigris–Euphrates river system countries suffer from different political issues, such as the Syrian war and internal civil conflicts in Iraq. In addition, this area consists of only three countries: Iraq, Syria, and Turkey, but it affects the entire Middle East. Turkey has established many irrigation projects compared to Iraq, which still suffers from the previous American invasion. Therefore, this study examines the Tigris–Euphrates river system (using two countries) to examine the relationship between water scarcity and food security from 1992 to 2020. This study will be conducted using a fixed and random regression approach over 18 years. The results show a negative relationship between water scarcity and food security in the short run, at a 10% significance level, and a long-term positive relationship of 1%. Thus, the use of research and development and the encouragement of investments will help policymakers to develop a nexus between water scarcity and food security. Full article

This paper aims to emphasize the need for enhancing inclusivity and accessibility within smart-city societies. It represents the first attempt to apply Amartya Sen’s capability approach by exploring the implications of digital divides for promoting inclusive and climate-friendly cities that prioritize well-being, equity, and societal participation. Sen’s framework recognizes individual variations in converting resources into valuable ‘functionings’, and herein emphasizes the importance of aligning personal, social, and environmental conversion factors for individuals to fully navigate, participate in, and enjoy the benefits provided by smart cities. Adopting the capability approach and employing a cross-disciplinary analysis of the scientific literature, the primary objective is to broaden understanding of how to improve inclusivity and accessibility within smart-city societies, with a specific focus on marginalized community members facing first- and second-level digital divides. This paper underscores the importance of adopting a systemic perspective on climate-smart city navigation and stresses the importance of establishing a unified governing body responsible for monitoring, evaluating, and enhancing smart-city functionality. The paper concludes by summarizing some policy recommendations to boost social inclusion and address climate change in smart cities, such as creating capability-enhancing institutions, safeguarding redundancy in public-choice options, empowering citizens, and leveraging academic knowledge in smart-city policy formulation. Full article

In Germany, there are over 32,000 schools, representing great potential for climate protection. On the one hand, this applies to educational work, as understanding the effects of climate change and measures to reduce GHG emissions is an important step to empower students with knowledge and skills. On the other hand, school buildings are often in bad condition, energy is wasted, and the possibilities for using renewable energies are hardly used. In our “Schools4Future” project, we enabled students and teachers to draw up their own CO₂ balances, identify weaknesses in the building, detect wasted electricity, and determine the potential for using renewable energies. Emissions from the school cafeteria, school trips, and paper consumption could also be identified. The fact that the data can be collected by the students themselves provides increased awareness of the contribution made to the climate balance by the various school areas. The most climate-friendly school emits 297 kg whilst the school with the highest emissions emits over one ton CO₂ per student and year. Our approach is suitable to qualify students in the sense of citizen science, carry out a scientific investigation, experience self-efficacy through one’s own actions, and engage politically regarding their concerns. Full article

Wounds are breaks in the continuity of the skin and underlying tissues, resulting from external causes such as cuts, blows, impacts, or surgical interventions. Countless individuals suffer minor to severe injuries, with unfortunate cases even leading to death. In today’s scenario, several commercial products are available to facilitate the healing process of wounds, although chronic wounds still present more challenges than acute wounds. Nevertheless, the huge demand for wound-care products within the healthcare sector has given rise to a rapidly growing market, fostering continuous research and development endeavors for innovative wound-healing solutions. Today, there are many commercially available products including those based on natural biopolymers, stem cells, and microRNAs that promote healing from wounds. This article explores the recent breakthroughs in wound-healing products that harness the potential of natural biopolymers, stem cells, and microRNAs. A comprehensive exploration is undertaken, covering not only commercially available products but also those still in the research phase. Additionally, we provide a thorough examination of the opportunities, obstacles, and regulatory considerations influencing the potential commercialization of wound-healing products across the diverse markets of Europe, America, and Asia. Full article

To explore how endophytic microbial compositions in amaranth roots are influenced by various fertilization methods and to determine whether these microbes are associated with amaranthin formation, we conducted an analysis of the endophytic microbial community structure. The roots of amaranth plants subjected to different fertilization treatments—conventional fertilization without potassium (NP), conventional fertilization without phosphorus (NK), conventional fertilization without nitrogen (PK), and balanced fertilization (NPK)—were examined. The results showed that the proportions of Streptomyces, Actinospica, and Burkholderia-Caballeronia-Paraburkholderia in the amaranth roots under the balanced fertilization (NPK) treatment were all greater than those in the amaranth roots under the nitrogen (PK), phosphorus (NK), and potassium (NP) deficiency fertilization treatments. In contrast, the proportions of Phenylobacterium, Acrocalymma, Neocosmospora, Fusarium, Acidovorax, Gibellulopsis, Cladosporium, Dactylonectria, and Gibberella in the amaranth roots under the nutrient deficiency fertilization (NP, NK, and PK) treatments were higher than those in the amaranth roots under the balanced fertilization treatment. Additionally, a significantly positive correlation was found between Streptomyces and the amaranthin content. Furthermore, Acrocalymma, Neocosmospora, and Fusarium exhibited significantly negative correlations with the amaranthin content. The above results suggested that endophytes could easily colonize in amaranth roots as beneficial microorganisms under balanced fertilization conditions. In other words, the balanced fertilization (N, P and K fertilizers are 188.0, 53.0 and 50.0 kg·hm⁻², respectively) could recruit more beneficial endogenous microorganisms in amaranth roots for improving their growth and quality. Full article