Despite ongoing efforts, the relationship between groin strength and injury remains unclear. The challenge of accurately predicting injuries presents an opportunity for researchers to develop pre-vention strategies to reduce the occurrence of such injuries. Consequently, this issue requires further investigation to obtain insights into effective mitigation strategies. In 120 male soccer players the maximum isometric strength of the hip muscle groups was measured, and the strength ratios were calculated. Previous injury and anthropometric data were registered. Injury data were collected following the FIFA/UEFA consensus. The K- Nearest Neighbour (k-NN), was used to predict the incidence of injury, while the significant predictive variables of the k-NN algorithm were fitted into a multivariate logistic regression model (LR) to analyze the likelihood of players sustaining a groin injury. The LR model determined two variables as significant predictors of groin injury. Players were less likely to sustain a groin injury by 76% for each decrease of the Adductors/Abductors isometric strength ratio in the non-dominant limb (OR = 0.238, CI 95%= [(0.098-0.572]). Players with a history of previous injury had a 67% greater risk of sustaining an injury (OR = 0.333, CI 95%= [(0.1068-1.038]). Isometric hip adductor and abductor strength im-balances of the non-dominant lower limb and a history of previous injury were risk factors for groin injury in soccer players.

Dynamic sparse training is an effective strategy to alleviate the training and inference demands of artificial neural networks. However, current sparse training methods face a challenge in achieving high levels of sparsity while maintaining performance comparable to that of their fully connected counterparts. The Cannistraci-Hebb training (CHT) method produces an ultra-sparse advantage compared to fully connected training in various tasks by using a gradient-free link regrowth method, which relies solely on the network topology. However, its rigid selection based on link prediction scores may lead to epitopological local minima, especially at the beginning of the training process when the network topology might be noisy and unreliable. In this article, we introduce the Cannistraci-Hebb training soft rule (CHTs), which applies a flexible approach to both the removal and regrowth of links during training, fostering a balance between exploring and exploiting network topology. Additionally, we investigate the network topology initialization using several approaches, including the bipartite scale-free and bipartite small-world network models. Empirical results show that CHTs can surpass the performance of fully connected networks with MLP architecture by using only 1% of the connections (99% sparsity) on the MNIST, EMNIST, and Fashion MNIST datasets and can provide remarkable results with only 0.1% of the links (99.9% sparsity). In some MLPs for image classification tasks, CHTs can reduce the active neuron network size to 20% of the original nodes (neurons), demonstrating a remarkable ability to generalize better than fully connected architectures, reducing the entire model size. This represents a relevant result for dynamic sparse training. Finally, we present evidence from larger network models such as Transformers, with 10% of the connections (90% sparsity), where CHTs outperform other prevalent dynamic sparse training methods in machine translation tasks.

Lipids have not traditionally been considered likely candidates for catalyzing reactions in biological systems. However, there is significant evidence that aggregates of amphiphilic compounds are capable of catalyzing reactions in synthetic organic chemistry. Here we demonstrate the potential for the hydrophobic region of a lipid bilayer to provide an environment suitable for catalysis by means of a lipozyme, or lipid aggregate capable of speeding up a chemical reaction. By bringing organic molecules into the non-polar or hydrophobic region of a lipid bilayer, reactions can be catalyzed by collections of small, nonpolar or amphiphilic molecules. We demonstrate this concept by the ester hydrolysis of calcein-AM to produce a fluorescent product, which is a widely used assay for esterase activity in cells. The reaction was first carried out in a two phase octanol-water system with the organic phase containing the cationic amphiphiles cetyltrimethylammonium bromide (CTAB) or octadecylamine. The octanol was then replaced with DOPC added to the water in the form of vesicles, where the reaction was also found to be carried out. The reaction was monitored using quantitative fluorescence which revealed catalytic turnover numbers on a scale of 10−4s−1 for each system, which is comparable to some slow enzymes. The reaction product was characterized by 1H-NMR measurements which were consistent with ester hydrolysis. The implications of thinking about lipid aggregates as catalytic entities are discussed in the context of biochemistry, pharmacology and synthetic biology.

Background: The effectiveness of the anti-COVID-19 vaccine remains a matter to be clarified. Methods: The humoral and cellular immunity after the administration of three doses of the Pfizer–BioNTech and Oxford AstraZeneca vaccines against SARS-CoV-2 over one year and the appearance of post-vaccination COVID-19 have been studied. Results: Anti-SARS-CoV-2 IgG and IgA antibodies showed a progressive increase throughout the vaccination period. This increase was greatest after the third dose. The highest levels were observed in subjects who had anti-SARS-CoV-2 antibodies prior to vaccination. There was an increase in CD4+ αβ, CD8+ γδ and TEM CD8+ γδ T cells, and a decrease in apoptosis in CD4+CD8+ and CD56+ αβ and γδ T cells. Post-vaccination SARS-CoV-2 infection was greater than 60%. The symptoms of COVID-19 were very mild and were related to γδ T cell deficit, specifically CD8+ TEMRA and CD56+ γδ TEM, as well as lower pre-vaccine apoptosis levels. Conclusions: Those results demonstrate the important role that γδ T cells play in SARS-CoV-2 vaccine immunization.

The liver diseases are posing serious threat to human health associated with abusive use of allopathy medicines, especially in developing economies like Pakistan. The strengthening of detoxification system using natural products might be a suitable option to minimize the liver problems. In this current research, Zingiber officinale and Azadirachta indica were evaluated for their hepatoprotective role. For the purpose, 20 Sprague Dawley rats were equally divided into four groups i.e., negative control, paracetamol positive control, 2.5% ginger and 2% neem powder, respectively. During 42 days study, the levels of bilirubin and liver enzymes significantly elevated due to liver damage. Although, the values dropped (20-25%) in treatment group. Serum glucose and serum lipid profile increased in positive control group, but reduced (5-10%) in both ginger and neem groups. The serum protein profile declined in liver damage group, however, improved (~5%) in treatment groups. The hematological parameters slightly declined in liver damage group, but increased in ginger and neem groups. Moreover, the white blood cells differential count and renal parameters showed abnormal values in liver damage group, but improved after treatment. This study is promising and highlighted the hepato-protective role of neem and ginger that may open several avenues of research.

Acute and chronic respiratory diseases impose a significant economic and health burden. Distal small airway assessment requires invasive procedures such as a bronchoscopy and bronchoalveolar lavage. The Particles in Exhaled Air (PExA) device provides a non-invasive means of assessing small airways; it captures distal airway particles sized around 0.5-7m and contains particles of respiratory tract lining fluid (RTLF) that originate during airway closure and opening. The PExA device can measure particle count and mass according to particle size. Subsequent capture of particles in a thin membrane enables application of various analytical methods to assess a broad range of biomolecules including phospholipids, proteins, inflammatory profile, and other metabolites to characterise inflammation and diseases processes such as asthma, chronic obstructive pulmonary disease, acute respiratory distress syndrome, lung cancer, and more recently acute infections such as COVID-19. PExA analysis provides a promising alternative to traditional investigative methods in the assessment, diagnosis, and management of respiratory conditions. By evaluating specific biomarkers in the RTLF associated with airway inflammation, PExA may offer a more accurate and comprehensive understanding of the molecular-level changes in the small airways of patients with acute and chronic lung diseases.

The domestic ducks (Anas platyrhynchos domesticus) are resistant to most of the highly pathogenic avian influenza virus (HPAIV) infections. In this study, we characterized the lung proteome and phosphoproteome of ducks infected with HPAI H5N1 virus (A/duck/India/02CA10/2011/Agartala) at 12 hr, 48 hr and 5 days post infection condition. Total 2082 proteins were differentially expressed and 320 phosphorylation sites mapping to 199 phosphopeptides corresponding to 129 proteins were identified. Functional annotation of proteome data analysis reveals activation of RIG-I-like receptor and Jak-STAT signaling pathways, that lead to induction of interferon stimulated genes (ISGs) expression. The pathway analysis of phosphoproteome datasets also confirms the activation of RIG I, Jak-STAT signaling, NF-kappa B signaling and MAPK signaling pathways in the lung tissues. The induction of ISGs proteins (STAT1, STAT3, STAT5B, STAT6, IFIT5 and PKR) establishes protective antiviral immune response in duck lung tissue. Further, the protein-protein interaction network analysis identified proteins like AKT1, STAT3, JAK2, RAC1, STAT1, PTPN11, RPS27A, NFKB1 and MAPK1 as main hub proteins that might play important roles in disease progression in ducks. Together, functional annotation of proteome and phosphoproteome datasets reveals the molecular basis of the disease progression and disease resistance mechanism in ducks infected with HPAI H5N1 virus.

Fibroin-chitosan composites, especially those containing nanohydroxyapatite, show potential for bone tissue regeneration. The physicochemical properties of these biocomposites depend on the compatibility between their components. In this study, the intermolecular interactions of fibroin and chitosan were analyzed using a molecular dynamics approach. Two types of systems were investigated: one containing acetic acid and the other containing calcium (Ca²⁺) and hydrogen phosphate (HPO₄²⁻) ions mimicking hydroxyapatite conditions. After obtaining the optimal equilibrium structures, the distributions of several types of interactions including hydrogen bonds, ionic contacts, and hydrophobic contacts along with the structural and energetical features were examined. The calculated binding energy values for the fibroin-chitosan complexes confirm their remarkable stability. The high affinity of fibroin for chitosan can be explained by the formation of a dense network of interactions between considered biopolymers. These interactions were found to be primarily hydrogen bonds and ionic contacts involving ALA, ARG, ASN, ASP, GLN, GLU, GLY, LEU, PRO, SER, THR, TYR, and VAL residues. As it was established, the complexation of fibroin with chitosan maintains the β-sheet conformation of the peptide. β-Sheet fragments in fibroin are involved in the formation of significant amount of hydrogen bonds and ionic contacts with chitosan.

Background: One challenge in implant dentistry is to reduce marginal bone resorption to avoid long-term esthetic and biological complications. Sub-gingival implant placement has been suggested as a suitable strategy. Methods: 38 healthy patients were enrolled to receive bone level (BL – Control group) or 2 mm sub-crestal (SC - Test group) conical connection, platform-switched implants. An immediate tissue level abutment was used in the Test group by following a One Time Abutment (OTA) restorative procedure. Marginal Bone Modification (MBM) was calcu-latied on standardized radiographs at surgery (T0), loading (T1), and 6 months (T2) and 12 months after loading (T3), and cathegorised in Bone Loss (BL) if the resorption occurred below the implant neck and Bone Remodeling (BR) if above. Pocket probing depth (PPD), Bleeding on probing (BoP) and Plaque Index (PI) were also collected. Results: The mean MBM in the test group after 12 months was 0.61mm, compared to 0.52mm in the control group. However, no BL was observed in the test group, as the MBM completely occurred above the implant neck as BR, whilst in the control group MBM corresponded in total to BL. The average PPD was 2.38mm in the test group and 3.04mm in the control group after 12 months, BoP 50% and 43%, PI 33% and 19.44% respectively. Conclusions: Sub-crestal conical connection, platform-switched implants could be a suitable clinical choice to avoid BL with exposure of the treated implants surfaces.

The p53 tumor suppressor protein is an activator of transcription. Diverse stress factors lead to various sets of posttranslational modifications of p53 what results in different sets of upregulat-ed genes. We noticed that actinomycin D and nutlin-3a (A+N) synergize in inducing activating phosphorylations of p53 and upregulation of selected p53-target genes. Here we found that one of these genes is DUSP13, which codes for poorly-studied, dual-specificity phosphatase having at least two isoforms, one expressed in testis and the other in skeletal muscles. In cancer cells ex-posed to A+N, DUSP13 is expressed from an alternative promoter in intron, what results in ex-pression of isoform named TMDP-L1. The luciferase reporter tests demonstrated that this pro-moter is activated by both endogenous and ectopically expressed p53. We showed for the first time that mRNA expressed from this promoter actually produces the protein, which can be de-tected by Western blotting in all examined cancer cell lines with wild-type p53 exposed to A+N. In some cell lines it is also induced by clinically relevant camptothecin or by nutlin-3a acting alone. This isoform, fused with green fluorescent protein localizes in perinuclear region of cells. Thus, TMDP-L1 isoform may be an important element of p53-regulated stress response system.

Background and Objectives: In recent years Electronic scooters (E-Scooters) have gained popularity, whether for private use or as a publicly available transportation method. With introduction of these vehicles, reports of E-Scooter related accidents have surged, sparking a public debate and concern. Aim of this study was to analyse epidemiological data, characteristics and severity of traumatic brain injury (TBI) related to E-Scooter accidents. Materials and Methods: This retrospective case series evaluated 28 patients who were admitted to three largest neurosurgery clinics in Riga, Latvia between time period from April to October in two separate years – 2022 and 2023 after an E-Scooter related accident. Data were collected on patient demographics, time of the accident, alcohol consumption, helmet use, type of TBI, other related injuries, treatment and assessment at discharge. Results: A total of 28 patients were admitted with TBI related to E-Scooter use, with median age 30 years (Q1-Q3, 20.25-37.25), four individuals under age of 18, majority (64%) were male. In 23 cases the injury mechanism was fall, in 5 cases collision. None were wearing a helmet at time of injury. Alcohol intoxication was evident in over half of the patients (51.5%), with severe intoxication (>1.2ppm) in 75% cases among them. Neurological symptoms upon admission were noted in 50% of cases. All patients had intracranial trauma - 50% brain contusions, 43% traumatic subdural hematoma, almost 30% - epidural hematoma. Craniofacial fractures were evident in 71% of cases, fractures in other parts of body in 3 patients. 6 patients required emergency neurosurgical intervention. Neurological complications were noted in 2 patients, 1 patient died. Conclusions: E-Scooter related accidents result in a significant number of brain and other associated injuries, with notable frequency linked to alcohol influence and lack of helmet use. Prevention campaigns to raise awareness of potential risks and implementation of more strict regulations should be done.

Vascular anomalies are a diverse group of abnormal blood vessel developments that can occur at birth or shortly afterward. Embolization and sclerotherapy have been utilized as a treatment option for these malformations but may cause moderate to severe pain. This study aims to evaluate the utilization of peripheral nerve blocks in opioid consumption, pain scores, and length of stay. A retrospective chart review was conducted at the UPMC Children's Hospital of Pittsburgh for all patients who underwent embolization and sclerotherapy between 2011 and 2020. Patient data was collected to compare opioid consumption, pain scores, and length of stay. Eight hundred fifty-four procedures were performed on 347 patients. The morphine milligram equivalent per kilogram mean ratio between groups was 0.9 (0.86, 0.95) with a p-value of <0.001. The pain score mean ratio was –1.17 (–2.2, -0.1) and a p-value of 0.027. Length of stay had a mean ratio of 0.94 (0.4, 2) and a p-value of 0.875. By decreasing opioid consumption and postoperative pain scores, peripheral nerve blocks may have utility in patients undergoing embolization and sclerotherapy while not clinically increasing the length of stay for patients. Their use should be individualized and carefully discussed with the interventional radiologist.

Primary ciliary dyskinesia (PCD) is an inherited disorder that impairs motile cilia, essential for respiratory health, with a reported prevalence of 1 in 16,309 within Hispanic populations. Despite having the RSPH4A [c.921+3_921+6del (intronic)] founder mutation in 70% of Puerto Rican patients, the characterization of the ciliary dysfunction remains unidentified due to the unavailability of advanced diagnostic modalities like High-Speed Video Microscopy Analysis (HSVA). Our study implemented HSVA for the first time on the island as a tool to better diagnose and characterize the RSPH4A [c.921+3_921+6del (intronic)] founder mutation in Puerto Rican patients. By applying HSVA, we analyzed the ciliary beat frequency (CBF) and pattern (CBP) in native Puerto Rican patients with PCD. Our results showed decreased CBF and a rotational CBP linked to the RSPH4A founder mutation in Puerto Ricans, presenting a novel diagnostic marker that could be implemented as an axillary test into the PCD diagnosis algorithm in Puerto Rico. The integration of HSVA technology in Puerto Rico substantially enhances the framework for PCD evaluation and diagnosis, facilitating prompt detection and early intervention for improved disease management. This initiative, demonstrating the potential of HSVA as an adjunctive test within the PCD diagnostic algorithm, could serve as a blueprint for analogous developments throughout Latin America.

This article utilizes the Canny edge extraction algorithm based on contour curvature and the cross-correlation template matching algorithm to extensively study the impact of high-repetition-rate CO2 pulsed Laser on the target extraction and tracking performance of the infrared imaging detector. It establishes a quantified dazzling pattern for lasers on infrared imaging systems. By conducting laser dazzling and damage experiments, a detailed analysis of the normalized correlation between target and dazzling images is performed to quantitatively describe laser dazzling effects. Simultaneously, an evaluation system, including target distance and laser power evaluation factors, is established to determine the dazzling level and whether the target is recognizable. The research results reveal that laser power and target position are crucial factors affecting the detection performance of infrared imaging-guided weapon systems under laser dazzling. Different laser powers are required to successfully interfere with the recognition algorithm of infrared imaging-guided weapons at different distances. And laser dazzling will produce a lot of false edge information, which seriously affects the performance of pattern recognition algorithm. In laser damage experiments, the detector experienced functional damage, with a quarter of the image displaying as completely black. The energy density threshold required for functional damage to the detector is approximately 3 J/cm2. The dazzling assessment conclusions also apply to evaluating damage results. Finally, the proposed evaluation formula aligns with experimental results, objectively reflecting the actual impact of laser dazzling on the target extraction and tracking performance of infrared imaging systems. This study provides an in-depth and accurate analysis for understanding the influence of lasers on the performance of infrared imaging-guided weapons.

Natural polluted insulator surfaces are always coated with various kinds of soluble constituents, and those constituents affect flashover performance differentially. Currently this fact is not considered either in laboratory experiments or field pollution degree measurements, causing the existing insulation selection method to be deficient. In this paper a systematical research on insulator flashover voltage gradient correction involving types of soluble pollution constituents was presented. Taking typical type glass insulator as the sample, its flashover tests polluted by typical soluble chemicals NaCl, NaNO₃, KNO₃, NH₄NO₃, MgSO₄, Ca(NO₃)₂ and CaSO₄ were carried out. Then the flashover gradient correction was made combining the flashover performance of each soluble constituent, the ESDD contribution of the seven constituents, as well as the saturation performance of CaSO₄. The correction was well verified with the flashover test results of insulator polluted by three types of soluble mixture. Research results indicate that the flashover gradient correction method proposed by this paper performs well in reducing the calculating error. It is recommended to carry out component measurements and flashover gradient correction to better select outdoor insulation configuration.

Background: Capsaicinoid are a group of compounds and widely used in the food, medical, and pharmaceutical industries. Capsaicinoid are unique synthesized and accumulated in the pepper fruits. MeJA can enhance the capsaicinoid production. Temporal and spatial expression of capsaicinoid biosynthetic genes are helpful to understand the molecular mechnism of capsaicinoid biosynthesis in the fruits of pepper. Although some of the capsaicinoid biosynthetic genes in pepper have been identified, the expression of these genes at different developing stages of fruit has not been systemically investigated, and little is known about the molecular basis of MeJA inducing capsaicinoid biosynthesis. Results: HPLC study revealed that the capsaicinoid accumulation in the developing fruit of pepper initially appeared at 24 DAP (day after pollination), was actively development at 36 DAP and peaked at 48 DAP. 11 genes that encoded enzymes involved in capsaicinoid biosynthesis were isolated and characterized. Gene expression with quantitative reverse-transcription polymerase chain reaction analysis demonstrated that the CaCS was unique expressed in placenta and the other 10 genes were expressed in all selected tissues and 9 of 11 genes (except CaCa4H and CaCa3H) were strongly expressed in placenta tissue. Spatial expression analysis demostrated that the 11 gene could be collectively grouped into four categories based on the patterns of relative expression of the genes during fruit development. Category I has 2 and they displayed a bell-shaped expression pattern with the peak expression at 24 DAP, Category II contains 5 genes and expression of the 5 genes was constantly increased from 0 to 36 DAP and peaked at 36 DAP. Category III comprises of 2 genes and both genes reached the peak at 48 DAP. Category IV consists of 2 genes and they showed a high expression at 36 and 48 DAF, but unexpressed from 0 to 12 DAP. The gene expressions of the 11 genes were up-regulated by MeJA. 3 genes showed a high expression at 24 h; 4 genes reached the peak at 12 h; the top expression were observed at 18 h; The last one, CaACYase, achieved the highest level at 8 h. Conclusion: The biosynthesis of capsaicinoid in pepper fruit is developmentally regulated. The expression of the majority of capsaicinoid biosynthetic genes is highly consistent with the development accumulation of capsaicinoid in pepper fruit. These results not only provide the initial information on spatial and temporal expression of capsaicinoid biosynthetic genes in pepper developing fruit, but are also valuable to identify the MeJA-induced genes for capsaicinoid biosynthesis and accumulation during pepper fruit development.

Oncological therapy is a very complex process. Accurate diagnosis is the first and most important stage of therapy for the patient, because it allows the medical staff to determine what treatment is nec-essary and how to plan it. Oncological treatment is currently widely considered to be holistic, in which the body is perceived as one, interconnected system. Oncological therapy should not focus only on one area of care, but should also include treatment support, such as appropriate nutrition or pain management. Aims: The aim of the article was to confirm the level of hydration, limit excessive water loss and regulate the pH value of the skin of patients after oncological treatment, who were adminis-tered fish collagen. Methods: The study used a set of probes that were used to examine the biophysical parameters of the skin of patients after oncological treatment. Conclusions: It was confirmed that the tested product restores the appropriate level of skin hydration in oncological patients, supports the reconstruction of the skin and its energy barrier by reducing transepidermal water loss and restoring appropriate pH values. Thanks to this, it is possible to eliminate the effects of pathological changes or accelerate their elimination.

A game problem of structural design is defined as a problem of playing against external circumstances. The scalar criterion serves the function of the payoff function. There are two classes of players, the “ordinal” and “cardinal” players. The ordinal players, designated as the "operator" and "nature," endeavor to respectively minimize or maximize the payoff function, operating within the constraints of limited resources. The fundamental premise of this study is that the probability distribution governing nature's "choice" of states remains unknown. Statistical decision theory addresses decision-making scenarios where these probabilities, whether or not they are known, must be considered. The solution to the substratum game is expressed as a value of the game. The value of the game is contingent upon the design parameters. The cardinal players, "designers", oversee the design parameters. For the se single cardinal player, the pursuit of the maximum and minimum values of the game reduces to the problem of optimal design. In the event that there are multiple cardinal players with conflicting objectives, a superstratum game emerges, which addresses the interests of the superstratum players. The optimal design problems for games with closed forms are presented. The game formulations could be applied for optimal design with uncertain loading.

Dengue fever remains one of the most significant public health challenges globally, particularly in tropical and subtropical regions. Traditional early warning systems (EWS) for dengue outbreaks, based on retrospective epidemiological data, suffer from delays and limited predictive accuracy. Modern systems, leveraging real-time data, artificial intelligence (AI), and machine learning (ML), improve accuracy but can be costly and difficult to implement in resource-constrained settings. This paper proposes a novel hybrid model that integrates the strengths of both traditional and modern EWS, with real-world examples from Brazil, and Malaysia. The hybrid model balances accuracy, scalability, and cost-effectiveness, making it a feasible option for low- and middle-income countries.

Automatic and blind parameter estimation based on the inherent features of wireless signals is a major research area due to the fact that these techniques lead to the simplification of receivers, especially in terms of coarse synchronization, more importantly reduce down the signaling load at the control channels. Thus, in the literature many techniques are proposed to estimate a vast set of parameters including modulation types and orders, data and chip rates, phase and frequency offsets and so on. In this paper, a cyclostationary feature detection based method is proposed to estimate the carrier numbers and carrier spacing of carrier-aggregated direct sequence spread spectrum cellular signals blindly. The particular chip rate of the signal is also estimated through the process jointly. In the paper, after the proposed method is formulated, the measurement setup which is developed to collect the data for the validation of the proposed method is introduced. The measurement results are post-processed for performance analysis purposes. To that end, the method is investigated in terms of SNR values, different channel conditions, and measurement durations. Furthermore, the performance of the proposed method is compared with that of energy detection. Measurement results indicate superior performance of the proposed method under significant wireless channel impairments and in low-SNR regions.

The resilience of towns and cities refers to their ability to adapt and recover when confronted with pressures or challenges. This study employs ten variables as indicators to assess the resilience of urban areas by analyzing official data and constructing a multilevel mixed-effects structural equation model. The empirical findings demonstrate that enhancing resilience significantly influ-ences urban service functions, such as strengthening healthcare systems, stabilizing the real estate market, and addressing socio-economic challenges. Specifically, factors such as healthcare re-sources, housing demand, population structure, and social security exhibit varying levels of resil-ience, which profoundly impact the spatial distribution of these factors and socio-economic de-velopment. Disparities in healthcare resource allocation, demographic aging trends, and shifts in the housing market closely correlate with resilience levels in different regions. Additionally, the study emphasizes that improving resilience not only boosts the reliability and security of urban services but also ensures that communities receive necessary support and protection during times of adversity. Consequently, policymakers should recognize the pivotal role of urban resilience in resource allocation and social equity, devising corresponding strategies to enhance the resilience of these areas.

The maritime industry contributes to over 80% of global trade and ranks as the sixth-largest emitter of greenhouse gases. The International Maritime Organization has taken strides to reduce these emissions, while the European Union spearheads efforts to establish sustainable maritime transport. However, meeting decarbonisation targets poses significant challenges, with the potential implications of adopting an EU Emission Trading System (ETS) on shipping allowances, particularly at specific borders. If not managed effectively, this could result in diversifying regular container shipping routes away from EU ports, potentially leading to increased shipping emissions and disrupting the logistics trade and security chain. These challenges are exacerbated by the International Maritime Organization's lack of a carbon fee on bunkering, which creates an imbalance. The ETS Directive has fostered unfair competition between EU and non-EU ports due to discrepancies in applying emission unit allowances. It is imperative to implement preventive measures to contain and prevent the shift of operations from EU ports to nearby ports, ensure equitable treatment of EU transhipment ports and their competitors, and thwart carbon leakage. Additionally, the recent Houthis attacks on the Red Sea have significantly impacted shipping costs on the Cape of Good Hope route to Europe, necessitating increased allowances to and from Europe.

Anxiety in older adults is a prevalent yet under-recognized condition associated with significant societal and individual burdens. This study used a machine learning approach to compare the relative importance of 57 risk and protective factors for anxiety symptoms in a population-representative sample of middle-aged and older European adults (N = 65,684; ages 45–103 years; 55.7% women; 15 countries represented). Results revealed loneliness and self-rated poor health as primary risk factors (Nagelkerke R2 = .272), with additional predictive contributions from country of residence, functional limitations, financial distress, and family care burden. Notably, follow-up analysis showed that none of 16 social network variables were associated with loneliness; rather, cohabitating with a partner/spouse was most strongly associated with reduced loneliness. Further research is needed to elucidate directional associations between loneliness and anxiety (both general and sub-types). These findings underscore the imperative of addressing loneliness for mitigating anxiety and related mental health conditions among aging populations.

It is shown that if there exists in nature a pair of heavy elementary particles each with a charge equal to that of the proton and with mass energy , then their direct interaction gives rise to a spontaneous fractionation of the two charges into three pairs of elementary particles according to two equiprobable channels, one hadronic and one leptonic. The leptons and quarks produced are in agreement with the first generation of the Standard Model of matter. Fractionation suggests the relative abundances of the elementary particles, introducing some questions about the possibility of the real existence of a currently unknown particle and its role in the formation of an apparent matter-antimatter asymmetry in the universe.

The lack of quality formulated feeds as supplements or replacements for live feeds has negatively impacted the growth performance and survival rates in the larvae of many fish species, notably African catfish (C. gariepinus). Successful larval rearing relies on the availability of suitable diets that are readily consumed, easily digested, and provide the essential nutrients necessary for optimal growth and health of the fish. This study evaluated the growth performance and survival rates of C. gariepinus larvae when fed locally formulated diets. The experiment was conducted using 12 basins, each with a capacity of 20 liters. Each basin was stocked with 60 larvae in four replicates, averaging 0.03 g in weight. The experimental diets were formulated to contain three different levels of crude protein: 40%, 45%, and 50%. The larvae were fed these diets at a rate of 10-20% of their body weight over 70 days. Initially, the larvae were fed artemia at the onset of feeding in hatchling basins immediately after yolk sac absorption for the first seven days. This was followed by a blend of artemia and formulated feeds for 14 days. After 28 days, the larvae were transitioned to be exclusively fed the formulated dry feeds. The results indicated that the larvae fed on diets containing 45% and 50% crude protein exhibited significantly better overall growth performance compared to those fed on a 40% crude protein diet. Specifically, the larvae that received the 45% and 50% crude protein diets showed higher final mean weight, increased daily weight gain, and improved survival rates, which ranged from 80% to 81.5%. Notably, there was no significant difference in growth performance and survival rates between the larvae fed on 45% and 50% crude protein diets, suggesting that a 45% crude protein-formulated diet is sufficient to achieve the best growth performance and survival rates for C. gariepinus larvae. This study supports the recommendation of feeding C. gariepinus larvae with a dry diet containing 45% crude protein starting from 14 days post-hatching to enhance their growth and survival rates. However, further research is recommended to explore the effects of this feeding regimen across different agroecological zones and aquaculture systems to validate and potentially refine these findings.

Simple Summary: 200 words Will biology, including humans, benefit or harm from new developments in information such as artificial intelligence (AI). First, are biology and information different? Life is an ordered form that can reproduce, maybe with variation; and any ordered arrangement, biological or not, potentially contains information. There have been ordered forms since earth was just a ball of chemicals, and some such chemicals can reproduce. So biological and non-biological information might be components of a unified process, ‘PanEvolution’ or ‘Pan-Evo’, based on the same four operations for living or non-living entities - Innovation; Transmission and replication; Adaptation; and Movement. This can produce separate groups called ‘species’. In a current Panspeciation event, information held in biology - especially our brains - is moving into its own environment. Harm to biology might be minimal if humans and AI both behave intelligently, because vastly different environments are optimal for humans and machines containing AI. This would be the first speciation-like event involving humans for millennia, but will not be particularly hostile to humans, if humans learn how to evaluate information and cooperate, to minimize the effect of both human stupidity and artificial simulated stupidity (ASS – a failure of AI). Abstract: 200 words Many people wonder whether biology, including humans, will benefit or harm from new developments in information such as artificial intelligence (AI). Biological and non-biological information might be components of a unified process, ‘Pan-Evolution’ or ‘Pan-Evo’, based on four basic operations – Innovation, Transmission, Adaptation, and Movement. Pan-Evo contains many types of variable objects, from molecules to ecosystems. Biological innovation includes mutations and behavioural changes; non-biological innovation includes naturally-occuring physical innovations, and innovation in software. Replication is commonplace in and outside biology, including autocatalytic chemicals, and autonomous software replication. Adaptation includes biological selection, autocatalytic chemicals and ‘evolutionary programming’ used in AI. Extension of biological speciation to non-biological information, creates a concept called ‘Panspeciation’. Panevolution might benefit or harm biology, but harm might be minimal if AI and the humans behave intelligently, because humans, and the machines in which AI resides, might split to the vastly different environments that suit them. That is a possible example of panspeciation, and would be the first speciation event involving humans for thousands of years. This event will not be particularly hostile to humans, if humans learn to evaluate information and cooperate better, to minimize both human stupidity and artificial simulated stupidity (ASS – a failure of AI).

In the global carbon cycle, atmospheric carbon emissions, both ‘natural’ and anthropogenic, are balanced by carbon uptake (i.e. sequestration) that mostly occurs via photosynthesis, plus a much smaller proportion via geological processes. Since the formation of the Earth about 4.54 billion years ago the ratio between emitted and sequestered carbon has varied considerably with atmospheric CO₂ levels ranging from 100,000 ppm to a mere 100 ppm. Over this time, a huge amount of carbon has been sequestered due to photosynthesis and essentially removed from the cycle, being buried as fossil deposits of coal, oil and gas. Relatively low atmospheric CO₂ levels were the norm for the past 10 million years, and during the past million years they averaged about 220 ppm. More recently, the Holocene epoch, starting ~11,700 years ago, has been a period of unusual climatic stability with relatively warm, moist conditions and low atmospheric CO₂ levels of between 260 and 280 ppm. During the Holocene, stable conditions facilitated a social revolution with domestication of crops and livestock leading to urbanisation and development of complex technologies. As part of the latter process, immense quantities of sequestered fossil carbon have recently been used as energy sources, resulting in a particularly rapid increase in CO₂ emissions after 1950 CE to the current value of 424 ppm, with further rises to >800 ppm predicted by 2100. This is already perturbing the previously stable Holocene climate and threatening future food production and social stability. Today, the global carbon cycle has been shifted such that carbon sequestration is no longer keeping up with recent anthropogenic emissions. In order to address this imbalance it is important to understand the roles of high-capacity carbon sequestration systems, such as natural forests and tropical croplands, and to devise strategies to facilitate net CO₂ uptake.

The fish found in the Tibetan Plateau and the Himalayas are referred to as schizothoracids, and they have evolved unique biological adaptations to high elevations. These adaptations include changes in the shape of the mouth, size, and length of gill rakers according to the prey size, sucking attachment organs to cope with fast currents, and genetic differences due to hypoxia and UV light. Nevertheless, there are recent threats like destruction of natural habitats, pollution, overfishing, and global warming that have posed serious conservation issues for numerous species. Conservation measures have been initiated even though well-articulated management techniques or other protective measures are absent from several protected areas for freshwater fisheries located in India. To resolve these issues, Schizothoracid population rescue, rehabilitation and restocking in safe water bodies should be implemented. For achieving their sustainability, scientists, conservationists, and legislators need to coordinate with each other.

Background: Across the world, antibiotic resistance is a grave problem. To address this issue, it is necessary to investigate new antibiotic sources. Aim of the study: Egypt's diverse soil habitats were used to produce bacterial Myxopyronin B, which was then tested for antimicrobial activity in preclinical animal studies and randomized human clinical trials stages 1/2. Type of the study: Screening experimental study. Methodology: Egypt's various soil conditions were examined for the development of bacterial isolates that produced the antibiotic compound Myxopyronin B. Reversed phase HPLC was used to purify Myxopyronin B. To determine the test antibiotic's minimum inhibitory concentration( MIC) and invitro antibacterial activity, the Broth microdilution method and the Paper disc diffusion assay were utilized. Moreover, in vivo antibacterial spectrum, adverse medication responses, and pharmacokinetics were found in preclinical animal testing stages and phases 1/2 of randomized clinical studies involving volunteer humans. Results: Myxopyronin B was generated from the culture supernatant of Myxococcus SDU36, the main soil bacterial isolate cultured on a Casein yeast peptone plate. With MICs less than 100 mcg/ml, the test antibiotic prevented the growth of several Gram +ve bacteria, whereas, at MICs higher than 100 mcg/ml, it inhibited the development of a small number of Gram -ve bacteria, including Escherichia coli. However, eukaryotic cells—such as those found in fungi and humans—were unaffected. The test antibiotic was seen to inhibit prokaryotic DNA-dependent RNA polymerase( RNLP), indicating its bactericidal activity. Mean Cmax was 9-10 mcg/ ml at mean Tmax 1 hour when 600 mg dose was orally administered in randomized human clinical trials phases 1/2, and T1/2 reached 2.25 hours following first-order kinetics of elimination. Duration of its action was nearly 8 hours after oral administration. Rare toxicity was detected during preclinical and randomized human clinical trials phases 1/2 in the form of mild diarrhea and GI upset in less than 7 % of experimental candidates. It exhibited approximately 90% plasma protein binding, especially with albumin which resulted in prolonged therapeutic action. It showed a concentration dependant antibiotic killing effect. With the concentration-dependent killing pattern, the higher the drug concentration relative to the pathogen minimum inhibitory concentration( MIC), the greater the rate and extent of antimicrobial activity. Conclusion: The present study was promising due to the production of the bactericidal antibiotic Myxopyronin B from Myxococcus sp. SDU36 isolated from different soil environments in Egypt.

Global public health systems have continuously faced challenges from the advent of novel infectious illnesses, necessitating quick and efficient actions to stop their spread.First discovered in Saudi Arabia in 2012, Middle East respiratory syndrome (MERS) is a viral respiratory disorder caused by the Middle East respiratory syndrome coronavirus (MERS-CoV). Since then, the nation has reported most cases and fatalities related to this sickness, with occasional outbreaks happening in other nations and regions. Severe sickness and high mortality are caused by MERS-CoV, especially in older persons and those with underlying chronic conditions. Through intimate contact, the virus can spread from people to dromedary camels and vice versa. It has sparked multiple epidemics both domestically and abroad in the Middle East, raising the possibility of fatalities and widespread transmission, especially in susceptible groups. The Riyadh region was the main target of the most current MERS-CoV outbreak in Saudi Arabia, which began in 2023 and ended on September 1, 2023, with 312 confirmed cases and ninety-seven fatalities. With the use of published studies and their contributions to the field, we hope to present a thorough overview of the MERS-CoV outbreak in Saudi Arabia in this review of the literature, including its epidemiological investigation, public health response, impact, and lessons learned. In addition to highlighting the importance and continued relevance of this problem, our work suggests ways to lower the risk of MERS-CoV transmission and avert further outbreaks.

This communication explores the transition from Cognitive Behavioural Therapy (CBT) to a more holistic model, named Complex Therapy, developed by Tullio Scrimali for explaining and treating mental disorders. The Author delves into the limitations of traditional CBT and introduces an innovative framework that integrates multiple therapeutic modalities. While CBT is based on the study and modification of behaviour and cognition, Complex Therapy includes, in its focus, the theory of human relationships, the attachment theory, neuroscience, applied neuroscience, complex systems theory and ecology.Complex Therapy addresses the multifaceted nature of mental health issues by combining evidence-based techniques with personalized care strategies. The goal is to enhance patient outcomes through a tailored, comprehensive treatment plan that adapts to the evolving needs of individuals facing mental health challenges.Two innovative and original items which Scrimali has developed, which are a device for Applied Neuroscience MindLAB Set and a new botanical drug, NegEnt, are presented and discussed.The topic also describes, an original and integrated protocol, named Negative Entropy, the author has developed for treating a challenging disorder, such as schizophrenia, he renamed Entropy of Mind.

Hox gene clusters are crucial in Embryogenesis. It was observed that some Hox genes are located in order along the telomeric to centromeric direction of the DNA sequence: Hox1, Hox2, Hox3…. These genes are expressed in the same order in the ontogenetic units of the Drosophila embryo along the Anterior-Posterior axis. The two entities (genome and embryo) differ significantly in linear size and in-between distance. This strange phenomenon was named Spatial Collinearity (SP). Later, it was observed that, particularly in the Vertebrates, a Temporal Collinearity (TC) coexists: first is Hox1 expressed, later Hox2 and even later Hox3,…,. According to a Biophysical Model (BM), pulling forces act at the anterior end of the cluster while a cluster fastening applies at the posterior end. Hox clusters are irreversibly elongated along the force direction. During Evolution, the elongated Hox clusters are broken at variable lengths thus split clusters may be created. An Empirical Rule was formulated distinguishing development due to a complete Hox cluster from development due to split Hox clusters. BM can ‘explain’ this Empirical Rule. In a spontaneous mutation where the cluster fastening is dismantled, a weak pulling force automatically shifts the cluster inside the Hox activation domain. This cluster translocation can probably explain the absence of Temporal Collinearity in Drosophila.

When dealing with limited sample sizes or missing values in time series data, achieving high accuracy in forecasting becomes challenging. This challenge is particularly common in wind energy forecasting, where many wind farms lack complete data. In this paper, we employ the widely-used ARIMA (Autoregressive Integrated Moving Average) model for time series forecasting. To address the difficulties posed by limited sample sizes and missing values, we adopt a unique approach by utilizing multiple ARIMA models for different datasets. A key distinction from other multiple models methods for time series forecasting lies in each model within our approach using its own dataset, making the fusion process more intricate. To overcome this, we incorporate neural networks and two techniques for model fusion: direct fusion with a learning mechanism and compensation for missing data through training. For each ARIMA model, we introduce a noise estimation method to circumvent the white noise assumptions inherent in ARIMA models. Finally, we apply these methods to wind energy prediction, and our experimental results showcase a significant enhancement in forecasting accuracy.

Many fields of human activity benefit from the ability to create images of obscured objects placed behind walls and to map their displacement in a noninvasive way. Usually, imaging devices like Synthetic Aperture Radars (SAR) and Ground Penetrating Radars (GPR) use expensive dedicated electronics which results in prohibitive prices. This paper presents the experimental implementation and the results obtained from an imaging system capable of performing SAR imaging and interferometric displacement mapping of targets located behind walls, as well as 3D GPR imaging using a low-cost general-purpose radar sensor. The proposed solution uses for the RF section of the system a K-band microwave radar sensor module implementing Frequency Modulated Continuous Wave operation. The low-cost sensor was originally intended for simple presence detection and ranging for domestic applications. The proposed system was tested in several scenarios and proved to operate as intended for a fraction of the cost of a commercial imaging device.

Colombia is the world's leading producer of mild washed arabica coffee and produces 12.6 million bags of green coffee, but at the same time 784,000 tons of waste biomass are dumped in open fields, of which only 5% is recovered or used. The objective of this project was to evaluate the production of platform chemicals from these coffee wastes. To achieve this, biomass characterization was carried out using proximate analysis, ultimate analysis and structural analysis. Hydrothermal valorization was carried out at a temperature range of 120-180 °C (LHW) and 180-260 °C (HTC) for one hour, the platform chemicals obtained were quantified by HPLC-IR, monitored by pH and conductivity, and the solid fraction was characterized by monitoring the functional groups in IR spectroscopy, and elemental analysis. Hydrolysis processes were obtained from 150 °C, production of platform chemicals from 180 °C and maximum concentration at 180 °C-4h, over 200 °C degradation of the products in the liquid fraction starts to take place. Homogeneous basic and acid catalysts were used to improve the yields of the reaction. The kinetics of the hydrolysis of lignocellulosic structures to sugars were also analyzed and described, and reaction orders of 1 (LHW), 3 (HTC) and their respective reaction rate equations were reported.

The coffee industry loses millions of dollars annually worldwide due to the Coffee Berry Borer (CBB); these losses imply a decrease in quality and production. Traps are used to monitor their flight and for pest control. The main objective was to determine the flight pattern and trap capture percentages of the CBB population over time using column traps (CTs) in two independent field experiments. CTs were composed of four traps installed at four different heights 0.5, 1.5, 2.5, and 3.5m above ground. Our results demonstrated a significant difference in CBB capture by traps placed at different heights above the ground. The CT capture maintained a pattern throughout this study's lag; the lower the height, the greater the percentage of CBBs captured. In Experiments A and B, the traps placed at 0.5m caught 67% and 85% of the CBBs captured, respectively. Furthermore, the trap set at 1.5m above the ground in the multi-level CT showed a higher capture percentage than the individually placed trap (also at 1.5m). The pattern of the capture and proportion of the CBB in the CTs were maintained throughout the study despite the season, changes in temperature, and relative air humidity. We suggested that CTs could be explored as a useful tool for capturing the CBB, considering its monitoring and management.

Many fundamental molecular techniques (PCR, Microarray, Southern and northern hybridization, siRNA, CRISPR/Cas9 etc.) developed so far shows errors. I wish to highlight these molecular techniques are developed on basis of Watson-Crick DNA model, ignoring the concept of parallel stranded DNA. Through this opinion article, I wish to highlight specificity and accuracy of these molecular techniques can be enhanced by considering both parallel and anti parallel hybridization of DNA. Hopefully my views will also solve issue of irreproducibility in life science research.

Transmission of values and religious concepts to children is one of the most important issues in the third millennium and it has drawn varied and different views among experts and scholars in the world. Research specialized in religious literature for children and adolescents create new capacities in the presentation of religious concepts to the group. Plans have been considered to transfer values and religious concepts in the curricula of primary school children in the group in Iran. It is one of the topics that the authors note to the introduction of the minutiae of religion in the first three elementary grades. In this study, the collection and analysis methods providing content related to the minutiae of religion in reading books the first till third sections of the years 2013-2015. In addition, the plan includes aspects of other branches of religion in these books on information collected from text books that collected and classified. The result is that "definitely good and forbidding the evil" and "prayer" have the highest frequency of applications in the selected books. Further branches made of branches of religion in these books, represents the values of religious, moral and social as well.

Among the many Lysosomal Storage Disorders (LSDs) that would benefit from the establish-ment of novel cell models, either patient-derived or genetically engineered, is Mucopolysaccha-ridosis type II (MPS II). In fact, even though a specific therapeutic approach does exist for this disorder (Enzyme Replacement Therapy, ERT, with recombinant human IDS) and haematopoiet-ic stem cell transplantation (HSCT) may also hold promise whenever the disorder is diagnosed soon enough, both approaches have their own drawbacks. Here we present our results on the establishment and characterization of two MPS II pa-tient-derived stem cell line(s) from deciduous baby teeth. To the best of our knowledge, this is the first time a stem cell population is isolated from LSD patient samples obtained from the oral cavity. Taking into account our results on the molecular and biochemical characterization of those cells and our first insights on their subcellular MPS phenotype, we consider these cells will be a valuable tool for both pathophysiological assessments and drugs screenings. Ultimately, we believe patient-derived dental pulp stem cells (DPSC) may represent a feasible alternative to induced pluripotent stem cells (iPSC) in many labs with standard cell culture con-ditions and limited (human and economic) resources.

Underreporting is the main limitation of the spontaneous reporting systems. This study aims to reduce underreporting enhancing public participation in vaccinovigilance through an SMS-based reporting system integrated with electronic immunization registries (IRs). Using the VigiVax software, parents of vaccinated children aged 2 years or younger received a single SMS inquiry about adverse events following immunization (AEFI). Responses were collected, validated by health operators and integrated with the information on IRs. AEFI reports were automatically submitted to the Italian Pharmacovigilance system. Among 254,160 SMS messages sent, corre-sponding to 451,656 administered doses (AD), 71,643 responses were collected (28.2% response rate), 21,231of them (8.3%) reporting an AEFI. After seriousness assessment based on clinical criteria, 50 reports (0,24%) were classified as serious. Among these, causality assessment identi-fied 31 reports at least potentially related to the vaccination (RR: 6.86/100,000 AD). Febrile seizures following MMRV vaccination accounted for 11 of these 31 cases, with an incidence of 32 per 100,000 AD. No fatal outcomes were reported. Our findings support the highly favorable risk profile of pediatric vaccinations and the possibility to improve spontaneous reporting through the integration of digital technologies.

In this paper, we consider the sensitivity of the controllable subspaces of single-input linear control systems to small perturbations of the system matrices. The analysis is based on the strict componentwise asymptotic bounds for the matrix of the orthogonal transformation to canonical form, derived by the method of the splitting operators. The asymptotic bounds are used to obtain probabilistic bounds on the angles between perturbed and unperturbed controllable subspaces implementing the Markoff inequality. It is demonstrated that the probability bounds allow to obtain sensitivity estimates which are much tighter than the usual deterministic bounds. The analysis is illustrated by a high order example.

Water pollution is a major global problem and the deterioration of water quality in rivers in many situations is becoming more widespread day by day, this causes a serious threat to all living beings and is eventually leading to the extinction of many aquatic species and others that depend on them. Therefore, with the advancement of Internet of Things (IoT) and Wireless Sensor Networks (WSN), monitoring the state of river water, for taking quick action to safeguard rivers becomes a pressing need, and is the main objective. An investigation was made into some existing IoT technologies and other related work to help achieve the objective of this project. In this paper we develop a low-cost solution based on Long Range (LoRa) to check in real-time, with specific sensors, some water parameters such as temperature, pH, conductivity, and turbidity. The data collected in a sensor node is sent via LoRa modulation to a gateway, where it is processed, forwarded to a local Message Queuing Telemetry Transport (MQTT) server, displayed on a local Node-RED dashboard, and alternatively it can be sent to the Internet. The developed prototype system is tested in a real scenario and proves that it can reliably monitor the water quality of a river in a reasonably sized area.

Sodium valproate is a established antiepileptic drug of first choice, primarily used to treat epilepsy, but also bipolar disorder and prevent migraine headaches. Valproate increases concentrations of gamma-aminobutyric acid in the brain, due to inhibition of enzymes responsible for the catabolism of gamma-aminobutyric acid. Main goal of this research consisted in the optimization and development for a new sensitive spectrophotometric quantitative analysis method of sodium valproate from tablets in the Visible field. Following the quantitative color reaction of sodium valproate with diazonium salt of alpha naphthylamine in alkaline medium, a light yellow azo dye was formed and spectrophotometrically analyzed at the wavelength of 386 nanometers. The amount of pure sodium valproate found on pharmaceutical extended-release tablet was 492.578 milligrams compared to the official declared pure amount of 500 milligrams on prolonged-release tablet. Amount found was assigned to a percentage content of 98.5156 percent pure sodium valproate in a pharmaceutical tablet. Mean average percentage error (deviation) from the officially stated value was about 1.4844 percent, which was included within normal limits, below five percent maximum limit allowed by European and Romanian Pharmacopoeias rules (5 percent). Spectrophotometric method was subjected to the statistical validation procedure and was successfully validated. Linear regression was analyzed. Method presented a very good linearity over the entire concentrations range 0.16 – 2.08 microgram on milliliter. Linear regression coefficient R square was 0.999330 and the correlation coefficient R was represented by 0.999665, were within the normal ranges of values.

In this study, a stepper driver, which is suitable for use in the automotive industry, designed for general use, capable of adaptive learning in the system in which it will be used, with CAN and Universal Asynchronous Receiver-Transmitter (UART) communication options, has been designed. This design is made with PIC18F25K22 Micro Controller Unit (MCU). Rotor speed, armature current, and terminal voltage can be measured on the proposed brushed DC motor drive system. It gives the desired response by evaluating the obstacle and high current situations. The speed measurement of the vehicle and the open and closed status of the automatic door can be monitored. Main contribution of the designed PCB is Adaptive Learning Algorithm (ALA) which uses pulses of the encoder and estimates position of the step and manage operation process to prevent mechanical damage at final point of the motor. On the other hand, unexpected hitting and pinching can be kept under control by watching current value. Beneficial side of this method is that life of the mechanical step increases due to management of the forward and backward operation of the step and prevents potential accidents.

Hybrid nanocomposites have emerged as a groundbreaking class of materials in the aerospace industry, offering exceptional mechanical, thermal, and functional properties. These materials, composed of a combination of metallic matrices reinforced with a mixture of nanoscale particles, such as carbon nanotubes (CNTs), graphene, and ceramic nanoparticles (SiC, Al2O3), provide a unique balance of high strength, low weight, and enhanced durability. Recent advances in developing these nanocomposites have focused on optimizing the dispersion and integration of nanoparticles within the matrix to achieve superior material performance. Innovative fabrication techniques have ensured uniform distribution and strong bonding between the matrix and the reinforcements, including advanced powder metallurgy, stir casting, in-situ chemical vapor deposition (CVD), and additive manufacturing. These methods have enabled the production of hybrid nanocomposites with improved mechanical properties, such as increased tensile strength, fracture toughness, wear resistance, and enhanced thermal stability and electrical conductivity. Despite these advancements, challenges remain in preventing nanoparticle agglomeration and ensuring consistent quality and repeatability in large-scale production. Addressing these issues is critical for fully leveraging the potential of hybrid nanocomposites in aerospace applications, where materials are subjected to extreme conditions and rigorous performance standards. Ongoing research is focused on developing novel processing techniques and understanding the underlying mechanisms that govern the behavior of these materials under various operational conditions. This review highlights the recent progress in the design, fabrication, and application of hybrid nanocomposites for aerospace applications. It underscores their potential to revolutionize the industry by providing materials that meet the demanding requirements for lightweight, high-strength, and multifunctional components.

Accumulated data indicate that epigenetic regulations, including histone modifications and DNA methylation, are important means for adjusting genes’ expression in response to various stimuli. In contrast to the success in studying the role of DNA methylation in laboratory rodents, the role of DNA methylation in terrestrial snail Helix lucorum has been studied only in behavioral experiments. This prompted us to further investigate the role of DNA methylation and the interaction between DNA methylation and histone acetylation in the mechanisms of neuroplasticity in terrestrial snails using in vitro experiments. Dysregulation of DNA methylation by DNMT inhibitor RG108 suppressed significantly the long-term potentiation (LTP) of synaptic inputs in identified neurons. We then tested whether the RG108-induced weakening of potentiation will be rescued under co-application of histone deacetylase inhibitors sodium butyrate or trichostatin A. RG108-induced LTP deficiency was significantly compensated by increased histone acetylation. These data bring important insight to the functional role of DNA methylation as an important regulatory mechanism and a necessary condition for the development and maintenance of long-term synaptic changes in withdrawal interneurons of terrestrial snails. Moreover, these results support the idea of the interaction of DNA methylation and histone acetylation in the epigenetic regulation of synaptic plasticity.

Starting from the objectives of the Nature Restoration Law and the concept of Forest Landscape Restoration, the objective of the following study is to present a methodological approach aimed at identifying areas that are best suited for the implementation of NbS for the improvement of landscape and habitat status in the study area identified by the Urban Atlas of the city of Campobasso (1028.64 km2). Using open data (ISPRA ecosystem services and Regional land use capability), an expert based approach (questionnaire) and a multi-criteria analysis (AHP), the Total Ecosystem Services Value (TESV) index was determined as a weighted additive sum of the criteria (Data) considered. The index was then classified into 8 clusters and the land use “Cropland” was extracted, matching Cluster 1 (740.09 Ha) with agricultural areas with less ES provision to be allocated to NbS and Cluster 8 (482.88 Ha) with valuable areas to be preserved, for a total of 2.34% of the study area. It was then possible to compare the “Forest” areas currently present in the study area with those of a possible future scenario, represented by the areas occupied today by forest with the addition of cluster 1 croplands. A landscape analysis was then conducted: it showed greater dispersion and fragmentation of forest patches in the future scenario but also greater connectivity and thus greater ecological functionality of the patches.

In 1935, Einstein and Rosen (ER), in their seminal paper "Particle Problem in General Relativity" proposed that "a particle in the physical Universe has to be described by mathematical bridges connecting two sheets of spacetime" in order to achieve a consistent understanding of quantum fields in curved spacetime. We discuss similar conclusions independently arrived at by Schr\"{o}dinger in 1956 and 't Hooft in 2016 in the context of cosmological and black hole spacetimes. Quantum effects at gravitational horizons involve inverse harmonic oscillators. We demonstrate that an analogous ER proposal of a mathematical bridge is envisioned by Berry and Keating for the description of a quantum inverse harmonic oscillator that has horizons in its phase space. Recently proposed direct-sum quantum theory reconciles the ER's vision by expressing a single quantum state in the physical space as a direct-sum of two components in the parity conjugate regions with opposite arrows of time. We discuss the implications of this framework for offering a new understanding of the ER bridges, promising a unitarity description of quantum fields in curved spacetime along with observer complementarity. Furthermore, we present compelling evidence for our new understanding of ER bridges in the form of large-scale parity asymmetric features in the cosmic microwave background. We finally discuss the implications of this new understanding for our endeavors in combining gravity and quantum mechanics.

Background/Objectives: Informed consent for anesthesia poses both legal challenges and problems of understandable communication. Fulfilling all requirements through anesthesiologists directly interacting with patients is a time- and staff-consuming strategy. Given today's smart technologies, notably including virtual reality (VR), we explored in a prospective randomized study whether 'VR-assisted informed consent' could improve this situation. Methods: Fifty patients scheduled for orthopedic surgery were randomized. In the control group, informed consent was obtained via patient-specialist dialogs only. The patients in the study group, wearing a head-mount display, watched an 8-minute immersive 3D movie with standard explanations of general anesthesia, followed by a patient-specialist dialog to address open question. The time spent on the dialogs in both groups was evaluated as primary outcome variable. As secondary variables, we analyzed both a three-item Likert scale on patient satisfaction with the VR experience and cost differences between both groups. Results: Patient-specialist dialogs were carried on for median (IQR) durations of 93 (20–182) seconds in the study group versus 665 (261–829) seconds in the control group (P<0.001). All patients exposed to VR rated this experience as favorable (87.5%) or neutral (12.5%). Based on anesthesiologists' incomes in the US and UK, our approach would reduce the staff expenditure for each patient-specialist dialog by median amounts of ≈40 or ≈11 US dollars, respectively (2× P<0.001). Conclusions: 'VR-assisted informed consent' for anesthesia is well accepted by patients and reduces the time requirements for patient-specialist dialogs, thus pointing out a potential avenue towards increasing the work-time efficiency of anesthesiologists.

This paper compares Demand Response algorithms suitable for Short-term Forecasting based on Advanced Metering Infrastructure (AMI). It selects ARIMA (AutoRegressive Integrated Moving Average), SARIMA (Seasonal ARIMA), LSTM (Long Short-Term Memory), and SVM (Support Vector Machine) as the primary research algorithms and delves into their theoretical foundations and functional characteristics. The theoretical background section explores each algorithm’s applicability in analyzing time-series data, recognizing nonlinear patterns, and solving optimization and classification problems. The methodology section will detail the methods of AMI data collection, the implementation of the algorithms, and the experimental setup. In the experiments and results section, the performance of each algorithm will be assessed by applying AMI data and presenting the outcomes of comparative analyses, with a focus on evaluating the predictive accuracy of the algorithms. The discussion will interpret the experimental results, analyzing the advantages and disadvantages of each algorithm and their applicability in the AMI system. It will also explore the limitations of the current research and directions for future research. The conclusion will summarize the key findings of the study and affirm how this research contributes to understanding and improving short-term forecasting and demand response systems based on AMI.

Background/Objectives: Parental internalizing issues, particularly maternal mental health, can significantly influence adolescents' mental health by altering parenting behaviors and roles. This study aims to explore how parental rejection, a dimension of both maternal and paternal behavior, moderates the relationship between parental depression, anxiety, and stress with adolescents' mental health and quality of life. We hypothesized that parental rejection would have a significant moderating effect on these relationships; Methods: This cross-sectional, non-interventional study involved 206 parents (138 mothers) of adolescents aged 12-18 years from the general population. Participants were recruited online via convenience sampling and completed the Depression Anxiety Stress Scale (DASS), the Parental Acceptance-Rejection Questionnaire, the KIDSCREEN-27 to evaluate adolescents' quality of life, and the Strengths and Difficulties Questionnaire to assess adolescents' mental health; Results: Parental rejection was found to moderate the relationship between maternal anxiety and adolescents' quality of life, as well as between maternal anxiety and adolescents' mental health problems. Paternal rejection moderated the relationship between paternal stress and adolescents' mental health. However, parental rejection did not moderate the relationship between parental depression and adolescents' quality of life or mental health; Conclusions: These findings emphasize the significant role of maternal rejection in the association between maternal mental health, particularly anxiety, and adolescents' mental health outcomes. Paternal rejection also showed some moderating effects, though to a lesser extent. These results underscore the importance of considering both maternal and paternal influences in adolescent mental health and quality of life. Further research is necessary to fully understand the gender-specific dynamics of these relationships.

This narrative review provides an in-depth analysis of attachment during adolescence, empha-sizing how early attachment experiences shape emotional, social, and psychological development. Drawing from the foundational work of Bowlby and Ainsworth, it revisits attachment theories and explores how the attachment system evolves as adolescents seek greater autonomy while maintaining bonds with caregivers. The review discusses the prevalence and developmental con-sequences of attachment-related disorders, such as reactive attachment disorder and disinhibited social engagement disorder, particularly in relation to adverse caregiving environments. Key themes include the intergenerational transmission of attachment, where parental reflective func-tioning and early caregiving behaviors influence attachment security across generations. The evolving role of fathers, peer relationships, and romantic bonds in adolescence are explored as significant factors shaping attachment patterns during this developmental period. Methodologi-cal considerations highlight the value of qualitative approaches, including interviews and obser-vational methods, for capturing the complexity of adolescent attachment dynamics. Additionally, the review addresses the processes that contribute to both continuity and change in attachment classifications over time, emphasizing the impact of life events, parental behaviors, and develop-mental transitions. The implications of attachment for developmental psychopathology, particu-larly in relation to emotional regulation and psychosocial functioning, are discussed. Finally, the review calls for further interdisciplinary research to deepen understanding of attachment mecha-nisms, using advanced technologies and culturally sensitive approaches to improve mental health and developmental outcomes across the lifespan.

Extreme Ultraviolet (EUV) photolithography process, is a cornerstone of semiconductor manufacturing and operates under demanding precision standards realized via nanometer-level overlay (OVL) error modeling. This procedure allows the machine to anticipate and correct OVL errors before impacting the wafer, thereby facilitating near-optimal image exposure while simultaneously minimizing the overall OVL error. Such models are usually high dimensional and exhibit rigorous statistical phenomena such as collinearities that play a crucial role in the process of tuning their parameters. Ordinary Least Squares (OLS) is the most widely used method for parameters tuning of Overlay models but in most cases it fails to compensate for such phenomena. In this paper we propose the usage of Ridge Regression, a widely known Machine Learning (ML) algorithm especially suitable for datasets that exhibit high multicollinearity. The proposed method has been applied in perturbed data from a 300 mm wafer fab and the results show reduced residuals when ridge regression is applied instead of OLS.

Gastrointestinal parasites (GIP) are diverse parasitic organisms known to have coevolved with bacterial populations inside the gut of mammalian hosts. These helminths produce small molecules, peptides and proteins to evade or fight their hosts' immune systems. Small molecules include polar compounds, amino acids, lipids and carbohydrates. Metabolomics is an emerging field of research recently applied to study helminth infections and host-parasite interactions. This review comprehensively discusses metabolomics studies of small molecules of GIP in animals, providing insights into the available tools and techniques, databases, and analytical software. Most metabolomics investigations employed LC-MS, MS or MS/MS, NMR, or a combination thereof. Recent advancements in metabolomics platforms, including artificial intelligence (AI)-assisted software tools and databases, have propelled helminth metabolomics forward, offering new avenues to explore host-parasite interactions, immunomodulation, and the intricacies of parasitism. As our understanding of helminth metabolomics continues to expand, it promises to unveil novel perspectives and enrich the knowledge of these complex host-parasite relationships.

This study analyzed methodologies for identifying β-casein genotypes in dairy cows and the purity of A2 fermented milk. The research was justified by the need for quick and accurate techniques for herd screening and A2 milk quality control. The methodology included the development of an ELISA test to detect β-casein A1 in fermented milk and the evaluation of a commercial Lateral Flow Immuno Assay (LFIA) to identify A2A2 genotypes and the purity of A2 milk. The results showed that the ELISA test had high sensitivity and specificity (100%) in detecting β-casein A1. The LFIA test was 100% effective in identifying A2A2 genotypes and verifying the purity of A2 milk with a minimum detectable contamination of 5% for raw milk and 10% for fermented milk. Compared to traditional genotyping, these methods proved to be highly reliable and more practical for large-scale screening. It was concluded that the ELISA and LFIA were valuable tools for ensuring the quality and authenticity of A2 milk, meeting the demands of producers and consumers for safe and healthy dairy products.

Electrolyte disturbances are common in patients with traumatic brain injury (TBI), particularly affecting sodium, potassium, chloride and calcium levels. This study aims to provide insights into these disturbances within the first 24 hours post-injury. We conducted a cross-sectional analysis of 50 TBI patients, excluding those with conditions affecting electrolyte balance. Electrolyte levels were measured, and correlations with demographic data, trauma mechanisms, imaging findings, and Glasgow Coma Scale (GCS) scores were analyzed. Results indicated that chloride levels inversely correlated with GCS scores (ρ = -0.515; p = 0.002), suggesting that elevated chloride may indicate severe neurological impairment. Potassium levels were significantly associated with subdural hematoma (p = 0.032) and subarachnoid hemorrhage (p = 0.043), highlighting their potential as markers for severe brain injuries. No significant associations were found between sodium or calcium levels and the studied variables. These findings underscore the importance of early monitoring of chloride and potassium levels in TBI patients to improve management and outcomes. Future research should focus on larger, multi-center studies to validate these findings and develop comprehensive guidelines for managing electrolyte imbalances in TBI patients.

Increasing efforts have been devoted to promoting sustainable demolition waste management (DWM) from a life cycle-thinking perspective. To this end, facilitating sustainability-oriented de-cision-making for DWM planning requires a sustainability assessment framework for assessing multifaceted criteria. This study develops a BIM-based DWM sustainability assessment ap-proach to facilitate the life cycle assessment (LCA) and decision-making by coupling the enriched IFC model with hybrid Multi-Criteria Decision-Aiding (MCDA) methods using Dynamo visual scripting. To streamline the data-intensive LCA process, this study enriched the BIM properties and accommodated them into the LCA data template to enhance data interoperability, thus achieving seamless data transfer. Moreover, hybrid MCDA methods are integrated into the deci-sion-making workflow for DWM scenario ranking. A pilot study is employed to verify the ap-plicability of the decision-aiding framework. The results unveil that the sustainability score ascended with the recycling rate. The optimal DWM alternative with the highest recycling rate yields the highest sustainability score at 91.63. Conversely, a DWM alternative reflecting the ‘status quo’ in China’s recycling industry has the lowest score at 8.37, significantly lower than the baseline scenario with a 50% recycling rate. It is worth noting that the ‘growth curve’ of the sustainability score continuously flattens as the target recycling rate escalates. The increment in recycling rate from the “Australian standard” scenario to the optimal scenario is 18.4%, while the sustainability score merely increases by 2.3%, signal-ling that the former scenario arrived at an optimum point for maximising the cost-efficiency of DWM under the predefined framework and contexts.

Background: Escalating climate change concerns have prompted the healthcare sector, particularly anaesthesia, to reassess its practices to align with environmental sustainability. Anesthetic gases like desflurane, sevoflurane, and isoflurane significantly impact the environment due to their high Global Warming Potentials (GWPs) and prolonged atmospheric lifetimes. This manuscript investigates these impacts and advocates for strategies to reduce the carbon footprint of anesthetic care while maintaining patient safety. Methods: We reviewed the environmental impacts of anesthetic gases and explored various strategies for sustainable anaesthesia. These strategies include adopting anesthetics with lower GWPs, enhancing recycling and waste reduction techniques, transitioning to intravenous anaesthesia, and implementing low-flow anaesthesia methods. We also examined barriers to these strategies, such as educational gaps, technological challenges, resistance to change, and policy limitations. Results: Adopting anesthetics with lower GWPs, such as sevoflurane over desflurane, and implementing low-flow anaesthesia can significantly reduce greenhouse gas emissions. Recycling and waste reduction techniques, though challenging, offer additional environmental benefits. Transitioning to intravenous anaesthesia can eliminate the direct GWP contributions from volatile anesthetic gases. However, these strategies require comprehensive education, advocacy for research and innovation, strategic change management, and supportive policies. Conclusions: Continuous monitoring and evaluation are crucial to ensure the effectiveness of sustainable practices in anaesthesia. Establishing robust Key Performance Indicators (KPIs) and utilizing advanced analytical tools will enable the anaesthesia community to adapt and refine practices. Collaborative efforts among clinicians, policymakers, and stakeholders are essential to significantly reduce the environmental impact of anaesthesia and promote ecological responsibility within healthcare.

In order to help the transportation industry achieve the goal of carbon peak and carbon neutrality, this study is based on the selection of eight variables, such as population size, per ca pita GDP, personal vehicle ownership, passenger and freight turnover, and green space coverage, as the factors influencing the carbon emissions of the transportation industry in Jiangsu Province, and the prediction and analysis of the transportation carbon emission trends from 2000 to 2021, and the prediction and analysis of the carbon emissions of the transportation industry and the time of the peak of the carbon emissions in Jiangsu Province. The trend of transportation carbon emissions from 2000 to 2021 was predicted and analyzed, and the carbon emissions and peak time of carbon emissions in the transportation industry in Jiangsu Province were predicted and analyzed. Comparing the predicted results with other models to verify the accuracy of the results, it was found that the WOA-SVM model had the smallest error among several models. On this basis, targeted measures are proposed to accelerate the process of carbon peak and ensure the smooth achievement of carbon neutrality goals in Jiangsu Province. The results indicate that under the current policy measures, the peak carbon emissions in Jiangsu Province will occur in 2038, with a peak of 48.72 million tons. Jiangsu Province should actively adopt energy-saving and emission-reduction measures, build a green and low-carbon transportation development model, and achieve the carbon peak target ahead of schedule.

Gravity forward modeling as a basic tool has been wildly used to topography correction and 3D density inversion. The source region is usually discretized into tesseroid (i.e., spherical prism) to consider the influence of the curvature of planets in global or large-scale problems. Traditional gravity forward modeling methods in spherical coordinates, including the Taylor expansion and Gaussian-Legendre quadrature, are all based on spatial domain, which are mostly low computational efficiency. This study proposes a high-efficient forward modeling method of gravitational fields in spherical harmonic domain, in which the gravity anomalies and gradient tensors can be expressed as spherical harmonic synthesis form of spherical harmonic coefficients of 3D density distribution. A homogeneous spherical shell model has been used to test its effectiveness compared with traditional spatial domain methods. It demonstrates that the computational efficiency of the proposed spherical harmonic domain method has improved by four orders of magnitude and with a similar level of computational accuracy compared with the optimized 3D GLQ method. Finally, the proposed forward method is applied to topography correction of the Moon. The results show that the gravity response of the topography by our method is close to that of the optimized 3D GLQ method, and is also consistent with previous results.

The aim of the study was to identify limiting factors for reusing wood through the recycling of window frames by conducting research under fully controlled conditions. The research involved manufacturing new window frames, seasoning them, and then shredding them into wood particles to prepare a three-layer particleboard. The proportion of wood particles in recycling was 0, 5, 10, 25, 50, and 100 parts by weight of the manufactured particleboard. Mechanical property tests were conducted: modulus of elasticity (MOE) and modulus of rupture (MOR), internal bond (IB), screw withdrawal resistance (SWR), and physical properties: density profile (DP), thickness swelling (TS) after water immersion, water absorption (WA), as well as formaldehyde emission and total volatile organic compounds (TVOC) tests. The conducted research indicates a significant potential for utilising wood from this sector of the wood industry, particularly considering variants with a higher proportion of recycled wood. MOR and MOE results are most promising for variants above 50 parts by weight of recycled wood. Based on the results obtained, it is clear that the production process should be improved or the raw material modified to enhance the internal bonding of particleboard, as these results were the weakest. Thus, recycled wood from window joinery has the potential to be reincarnated as particleboard, which continues to be widely used in their production.

This article aims to analyze household energy data to predict electricity self-sufficiency and identify the key features that impact it. For this purpose, we use SHAP (Shapley Additive Explanations), LightGBM (Light Gradient Boosting Machine), and a correlation heatmap-based framework to analyze 12 months of energy and questionnaire survey data collected from over 200 smart houses in Kitakyushu, Japan. We use the SHAP summary plot to identify the impact-wise order of key features influencing the electricity self-sufficiency rate (ESSR). Using SHAP, we demonstrated that key features are; housing types, average monthly electricity bill, floor heating, electric capacity, number of washing and drying machines, fee plans, occupation of household head, total floor area, average monthly gas bill, cooking equipment, etc. Furthermore, we adopted the LightGBM classifier with $\ell^1$ regularization to extract the most significant features and predict the electricity self-sufficiency rate of households. This LightGBM-based model can also predict the electricity self-sufficiency rate of households that did not participate in the questionnaire survey. A heat map is also used to analyze the correlation among household variables. The findings discussed in this article offer valuable insights for energy policymakers to achieve the targets of energy self-sufficient houses.

This study introduces a novel method for early prediction of Kimchi cabbage (Brassica rapa subsp. pekinensis (Lour.) Hanelt) height, utilizing drone imagery and a long short-term memory (LSTM) model. The research was conducted on a testbed at the National Institute of Agricultural Sciences (NAS) in South Korea, encompassing two distinct soil types (loam and sandy loam) to investigate their impact on growth. High-resolution drone images were captured throughout the growing season to generate a canopy height model (CHM) for estimating plant height at various stages. Missing height data were interpolated using a logistic growth curve, and an LSTM model was trained on this data to predict the final height of Kimchi cabbage at harvest. Three LSTM models were developed using time-series data collected at 29, 36, and 44 days after planting (DAP). The model trained on data from DAP 44 demonstrated the highest accuracy with a coefficient of determination (R²) of 0.83, a mean absolute error (MAE) of 2.48 cm, and a root mean square error (RMSE) of 3.26 cm, outperforming models trained on earlier data. Color-coded maps were generated to visualize the spatial distribution of predicted Kimchi cabbage heights, revealing variations in growth patterns across the testbed and confirming the model's potential for site-specific management. Considering the trade-off between accuracy and prediction timing, the model trained on DAP 36 data (MAE = 2.77 cm) was deemed optimal for informing cultivation management decisions. This research demonstrates the feasibility and effectiveness of integrating drone imagery, logistic growth curves, and LSTM models for early and accurate prediction of Kimchi cabbage height. The proposed technology enables data-driven decision-making for farmers, facilitating timely interventions based on predicted growth patterns. This could lead to improved crop yields, resource optimization, and a more sustainable agricultural future. Future research will focus on refining the model's accuracy and exploring its applicability to other crops, further expanding the potential of precision agriculture technologies.

There are various modeling techniques adopted for predicting the labor productivity that incorporate the influence of various factors, but neural networks are found to have strong pattern recognition and higher accuracy to get reliable estimates. To develop a construction labor productivity (CLP) model for concreting activities, data were collected through a questionnaire. The most critical influencing parameters were ranked according to their relative importance index (RII). Then the strength of the relationship between CLP and influencing parameters was analyzed using correlation coefficient results generated in Python program. Finally, the CLP model which represents the output of the crew within a certain factor was successfully developed using artificial neural networks (ANNs). Five objectives and six subjective critical influencing parameters were selected using RII. Crew experience, age of workers, and placement technique are the top three influencing parameters that have a strong relation with CLP with correlation coefficient values of 0.5681, 0.5349, and 0.5227 respectively. The developed model within these influencing parameters has a higher capability to predict the output of labor with a 92% coefficient of determination (R2) and a mean squared error of 0.316%. Therefore, the application of such a model for the accurate estimation of labor productivity is recommended.

This article presents a buck converter in which the inductor has been replaced by a transmission line. This approach would be practically conceivable if the power supply and load have a greater spatial distance. In the time domain, this new converter can be described by a system of coupled partial and ordinary differential equations. In the frequency domain, a transcendental transfer function is obtained. For comparison with an equivalently parameterized conventional converter, Padé approximants are derived. A linear controller is designed for the converter topology under consideration.

Bearing component damage contributes significantly to rotating machinery failures. It is vital for the rotor-bearing system to be in good condition to ensure proper functioning of the machine. Over recent decades, extensive research has been devoted to the condition monitoring of rotational machinery, with a particular focus on bearing health. This paper provides a comprehensive literature review of recent advancements in intelligent condition monitoring technologies for rolling element bearings. Fundamental monitoring strategies are introduced, covering various sensing, signal processing, and feature extraction techniques for detecting defects in rolling element bearings. While vibration-based monitoring remains prevalent, alternative sensor types are also explored, offering complementary diagnostic capabilities or detecting different defect types compared to accelerometers alone. Signal processing and feature extraction techniques, including time domain, frequency domain, and time-frequency domain analysis, are discussed for their ability to provide diverse perspectives for signal representation, revealing unique insights relevant to condition monitoring. Special attention is given to information fusion methodologies and the application of intelligent algorithms. Multisensor systems, whether homogeneous or heterogeneous, integrated with information fusion techniques, hold promise in enhancing accuracy and reliability by overcoming limitations associated with single sensor monitoring. Furthermore, the adoption of AI techniques, such as machine learning and metaheuristic optimisation, has led to significant advancements in condition monitoring, yielding successful outcomes in various studies. Finally, avenues for further advancements to improve monitoring accuracy and reliability are identified, offering insights into future research directions.

This study introduces an integrated method for managing process risks in a Business Process Reengineering (BPR) project, using Robust Data Envelopment Analysis (RDEA) and machine learning (ML). The goal is to prioritize risks based on three standard factors of PFMEA: Severity, Occurrence, and Detection (S-O-D), and incorporating two additional factors (Breakdown Cost and Breakdown Duration) seen as undesirable outputs. The model also accounts for the effect of uncertainty on expert-estimated values by applying disturbance percentages in the linear PFMEA-RDEA model. A machine learning model is proposed to predict new values if partial or total modifications have been made to the processes. The approach was implemented in an au-tomotive sector company, and the results showed the impact of uncertainty on values by com-paring different approaches such as RPN, PFMEA-DEA, and PFMEA-RDEA. A new reduced risk categorization was achieved, who allowed for decision-makers to focus on necessary actions for reengineering.

The allosteric SERCA (Sarcoplasmic/Endoplasmic Reticulum Ca2+-ATPase) activator CDN1163 has been recently added to the group of pharmacological tools for probing SERCA function. We chose to investigate the effects of the compound on T lymphocyte Ca2+ stores, using the well-described Jurkat T lymphocyte as a reliable cell system for Ca2+ signaling pathways. Our study identified the lowest concentrations of the SERCA inhibitors thapsigargin (TG) and 2,5-di-(tert butyl)-1,4-benzohydroquinone (tBHQ) capable of releasing Ca2+, permitting the differentiation of the TG-sensitive SERCA 2b Ca2+ store from the tBHQ-sensitive SERCA 3 Ca2+ store. We proceeded to test the effects of CDN1163 on Ca2+ stores, examining specific actions on the SERCA 2b and SERCA 3 Ca2+ pools using our low dose SERCA blocker regimen. In contrast to previous work, we find CDN1163 exerts complex time-sensitive and SERCA isoform-specific actions on Ca2+ stores. Surprisingly, short-term exposure (0-30 minutes) to CDN1163 perturbs T cell Ca2+ stores by suppressing Ca2+ uptake with diminished Ca2+ release from the SERCA 2b-controlled store. Concomitantly, we find evidence for a SERCA-activating effect of CDN1163 on the SERCA 3 regulated store, given the observation of increased Ca2+ release inducible by low dose tBHQ. Intriguingly, longer-term (>12 hours) CDN1163 exposure reversed this pattern, with increased Ca2+ release from SERCA 2b-regulated pools, yet decreased Ca2+ release responses from tBHQ-sensitive SERCA 3 pool. Our results reveal differential effects of CDN1163 on Ca2+ stores regulated by distinct SERCA isoforms, prompting the need for careful interpretation of the compound’s effects, particularly in cells expressing multiple SERCA isoforms.

In this paper, the ratio of gross agricultural production (GAP) and agricultural carbon emission is defined as agricultural carbon emission efficiency (ACEE). Considering rural labor transfer (RLT) increases the agricultural machinery intensity (AMI), the two are substitutes for each other and may interact with agricultural carbon emission efficiency (ACEE), we constructed a Simultaneous Equations Model (SEM) of ACEE, RLT and AMI, and analyzed the interaction mechanism of these three variables by using the Three-Stage Least Squares (3SLS) method to solve the endogeneity of the model. The following conclusions are drawn. First, RLT and AMI significantly promote the improvement of ACEE, while the improvement of ACEE and AMI further promotes RLT. Secondly, the causal relationship and influence mechanism of ACEE, RLT and AMI are interactive and multi-directional. An increase in AMI promotes ACEE, but an increase in ACEE inhibits an increase in AMI, suggesting that the marginal rate of substitution of machinery for labor is decreasing. Finally, China has significant regional heterogeneity. Labor transfer and machinery are only direct factors in increasing ACEE, while factors such as economic base, technology level and farmers' attitudes provide environmental support for the effective improvement of ACEE.

Areas covered with vegetation play a key role for life on Earth and should be inventoried in a clear and complete manner in order to improve the process of its protection and development. Data showing the amount of greenery in areas most deformed by humans, i.e. urbanized areas, are particularly important. Local governments need to know how to invest theirs limited sources in the quality of life of residents by supplementing the urban fabric with additional vegetation. The article presents a proposal for how to calculate the degree of greenness of cities based on remote sensing data. Additionally, a novel method was proposed to help in planning the development of areas covered with vegetation, taking into account the spatial distribution of the local population. The result was a comprehensive method presenting the actual natural situation in a specific city.

The augmenting commitment in the entrepreneurial learning process, both at academic and industry level, has led to new mechanisms and methodologies. Entrepreneurship literature has shown evidence of raising interest in the problem-based learning (PBL) methodology with regard to upcoming events from the surrounding learning context. This paper presents a Systematic Bibliographic Literature Review (SBLR) with respect to the application of PBL throughout distinct entrepreneurial processes either in higher education, or in industry. It aimed to identify relevant entrepreneurial opportunities for PBL. Bibliographic databases were searched for documents published between 2002 and May 2024 to categorize key topics discussed in the literature on PBL and entrepreneurship. The review process identified 142 empirical and non-empirical papers on entrepreneurship related PBL. Data analysis revealed diverse subthemes for PBL uses in entrepreneurship in both higher education institutions and industry. The research questions “What is the interplay of problem-based learning methodology with entrepreneurship?” guided the study. The central output of the research is the discovery of the varying uses of PBL to cope with diverse events arising within entrepreneurship context. Future research directions are suggested.

Although composting has many advantages in the treatment of organic waste, there are still many problems and challenges associated with emissions, like NH3, VOCs, and H2S, as well as greenhouse gases such as CO2, CH4, and N2O. One promising approach to enhancing composting conditions is used of novel analytical methods bad on artificial intelligence. To predict and optimize the emissions (CO, CO2, H2S, NH3) during composting process kinetics thought mathematical models (MM) and machine learning (ML) models were utilized. Data about everyday emissions from laboratory composting with compost’s biochar with different incubation (50, 60, 70 °C) and biochar doses (0, 3, 6, 9, 12, 15% d.m.) were used for MM and ML models selections and training. MM has not been very effective in predicting emissions, (R2 0.1 - 0.9), while ML models such as acritical neural network (ANN, Bayesian Regularized Neural Network; R2 accuracy CO:0,71, CO2:0,81, NH3:0,95, H2S:0,72)) and decision tree (DT, RPART; R2 accuracy CO:0,693, CO2:0,80, NH3:0,93, H2S:0,65) have demonstrated satisfactory results. For the first time the ML models to predict CO and H2S during composting were demonstrated. Further research in a semi-scale and field study composting with biochar is needed to improve the accuracy of developments models.

Proteins have the ability to adsorb on the surface of materials, such as soft contact lenses (SCLs), and can affect the hydrophobicity, roughness and surface properties of the contact lenses (CLs), which, in turn, can influence the friction between the lenses and the ocular surface. Excessive friction between contact lenses and the ocular surface can lead to discomfort for the wearer and may cause irritation or inflammation of the cornea, better known as corneal ulcers (keratitis). Bovine serum albumin (BSA) is often used as a standard protein in biocompatibility testing of materials, including contact lenses. One standard commercial contact lenses was tested under lubricated conditions to access the coefficient of friction (CoF), being the contact lubricated with a tear like fluid (TLF) solution containing six different concentrations of BSA. In all cases, a good linearity of the results of the friction force was verified, so the first friction law can be applied to determine the value of the coefficient of friction. It was found that friction increases with increasing protein concentration.

Diesel is consistently a very popular fuel for internal combustion engines. Its consumption in the European Union has been rising over recent years, as has the number of engines increasingly sensitive to fuel contamination. One of the most important parameters affecting diesel quality is water content. Although its exceedances of the standard’s permissible amount are not common, they carry the risk of serious damage to expensive, modern fuel injection systems. Current methods of measuring water content require both specialised personnel and equipment, as well as transporting the sample to a suitable laboratory. The research presented in this paper was aimed at verifying whether it would be possible to test the moisture content of diesel using impedance spectroscopy. Once refined, such measurement method could be used in situ. Analysing the properties of diesel is challenging, mainly because many types of the fuel are sold, the chemical composition of which is always a well-guarded manufacturer’s secret. The experimental results obtained on many types of commercially available diesel show that it is possible to use impedance spectroscopy to estimate the water content of different types of diesel fuel. The measurement accuracy achieved makes it possible to detect approaching or exceeding the permissible water content.

Background: Several kinds of research say that adjuvant blood glucose and blood pressure are usual, but an efficient solution for medical application count remains. This review analyzes the pandemic blood pressure and blood glucose to identify the publications which tell about the clinical practices and research gaps in systematic research.Methods: A study guides to identify the research of Blood Pressure (BP) and Blood Glucose. In order to analyze the recent innovations and research on BP and Blood glucose, the relevant publications and literature from journals were identified.Results: Co-morbidity of BP and Blood glucose is reported as very high. The commonness of blood pressure is thrice as high in type I diabetes patients and almost two times higher in type II diabetes patients when compared to others without Diabetes. The pervasiveness of getting depression is more in the female when compared with men. A detailed study about the linkage of BP and blood glucose tells that the relationship between them is not exactly clear.Limitations: Nearly all reviews providing the linkage of BP and blood glucose are with some limitations and they are not providing any clear conclusion.Conclusions: Present research tells that people having high blood glucose will have a greater chance of getting high blood pressure. More research is needed to state the linkage between BP, blood glucose, and the growth of diabetes mellitus issues and to provide support for managing Diabetes.

Cities are complex systems requiring urban design models that balance order and disorder. Collective creativity initiatives engage citizens in these processes, empowering bottom-up approaches that prioritize people and social well-being within urban development. This paper investigates an 'Urban Laboratory' as a case study, examining the potential of collective creativity to address urban complexity. The successful and ongoing project 'El Campo de Cebada' in Madrid, Spain, demonstrates how a community transformed a vacant lot into a vibrant social hub. The phases of this study include case selection, data collection, data analysis, and presentation of the results. This study identifies key enabling factors, including agents, management, social dynamics, infrastructure, and actions. These insights offer a methodological framework for designing future collaborative, resilient, and inclusive urban spaces, addressing the complex needs of communities within our cities.

The Internet of Things (IoT) is a concept based on the integration of various devices and methods of communication to exchange information in order to contribute to the improvement of everyday life, business and environment. This paper focuses on the establishment of a modern Internet of Things platform to ensure secure collection, processing and storage of data, under unexpected events. This platform establishes reliable connectivity which enhance system uptime; the key to success when implementing an IoT strategy. For this purpose, we proposed a hybrid approach combining different connectivity technologies to ensure the availability and smooth operation of the system and the prevention of data loss in unforeseen cases.

Recent studies have elucidated the diversity of genes encoding venom in sea anemones. However, most of those genes are yet to be explored in an evolutionary context. Insulin is a common peptide across metazoans and has been coopted into a predatory venom in many venomous lineages. In this study, we focus on the diversity of insulin-derived venoms in sea anemones and on elucidating their evolutionary history. We sourced data for 34 species of sea anemones and found sequences belonging to two venom families that have Insulin PFAM annotations (Cono-Insulin, VP302). Our findings show that both families have undergone duplication events. Members of each of the independently evolving clades have consistent predicted protein structures and distinct dN/dS values. Our work also shows that VP302 is part of a multidomain venom contig and has experienced a secondary gain into the venom system of cuticulate sea anemones.

The food system, the most important driver of planetary transformation, is in a deep crisis. Therefore, seeking a sustainable and socially-fair transition pathway becomes an issue of utmost priority for our own survival. The consideration of food as a commodity, a social construct that played a central role in driving this crisis, remains the uncontested narrative to lead the different transition pathways what seems rather contradictory. By exploring the normative values in the transition landscape, this paper seeks to understand how relevant is the hegemonic narrative of “food as commodity” and its alternative of “food as commons” to determine transition trajectories and food policy beliefs. Applying the Multi-level Perspective framework and developing the ill-studied “agency in transition”, this research enquired food-related professionals that belong to an online community of practice (N=95) on valuation of food dimensions and agency in food transitions to check whether the valuation of food is relevant to explain personal stances in transition. Results suggest the socially-constructed view of food as commodity is positively correlated to the gradual reforming attitude, whereas food as commons is positively correlated to the counter-hegemonic transformers regardless the self-defined position in the transition landscape (regime or niches). At personal level, there are multiple loci of resistance with counter-hegemonic attitudes in varied institutions of the regime and the innovative niches, many of them holding this discourse of food as commons. Conversely, alter-hegemonic attitudes are not positively correlated to this alternative discourse and they may inadvertently or purportedly reinforce the ‘‘neoliberal narrative’’. Food as commons, a different narrative whose rationale is explained in the paper, seems to be a relevant framework that could enrich the multiple transformative constituencies that challenge the industrial food system and therefore facilitate the convergence of movements that reject the commodification of food.

A space charge density wireless measurement system based on the idea of distributed measurement is proposed for collecting and monitoring the space charge density in an ultra-high-voltage direct-current (UHVDC) environment. The proposed system architecture is composed of a number of wireless nodes connected with space charge density sensors and a base station. The space charge density sensor based on atmospheric ion counter method is elaborated and developed, and the ARM microprocessor and Zigbee radio frequency module are applied. The wireless network communication quality and the relationship between energy consumption and transmission distance in the complicated electromagnetic environment is tested. Based on the experimental results, the proposed measurement system demonstrates that it can adapt to the complex electromagnetic environment under the UHVDC transmission lines and can accurately measure the space charge density.

Abstract. Results of research into four-membered phosphorus(V)-heterocycles, 2-halogen-1,2λ⁵-oxaphosphetanes are presented. The preparation of 2-halo-1,2λ⁵-oxaphosphetanes by reaction of P-haloylides with carbonyl compounds is described. The mechanism of asynchronous [2+2]-сycloaddition of ylides to aldehydes was proposed on the base of low-temperature NMR investigations. 2-Halogen-1,2λ⁵-oxaphosphetanes were isolated as individual compounds and their structures were confirmed by ¹Н, ¹³C, ¹⁹F and ³¹Р NMR spectra. These compounds are convenient reagents for preparing of various organic and organophosphorus compounds hardly available by other methods. Chemical and physical properties of the 2-halo-1,2λ⁵-oxaphosphetanes are reviewed. The 2-chloro-1,2λ⁵-oxaphosphetanes depending on substituents at the α-carbon atom rearrange with formation of 2-chloroalkylphosphonates or convert into trans-phosphorylated alkenes. Prospective synthetic applications of 2-halo-1,2λ⁵-oxaphosphetanes are analyzed. The 2-halo-1,2λ⁵-oxaphosphetanes may be easily converted to various alkenylphosphonates: allyl- or vinylphosphonates, phosphorus ketenes, thioketenes, ketenimines.

We introduce the notion of generalized contraction on dualistic partial metric spaces. A fixed point theorem for mappings satisfying above mentioned contraction is obtained. Some consequences of our result are obtained. We construct an example to demonstrate the effectiveness of our result among the corresponding results in partial metric spaces. Our results provide substantial generalizations and improvements of several well known results existing in the comparable literature. We discuss an application of our fixed point results to show the existence of solution of functional equations.

The achievement of size uniformity and monodispersity in perovskite quantum dots (QDs) requires the implementation of precise temperature control and the establishment of optimal reaction conditions. Nevertheless, the accurate control of a range of reaction variables represents a considerable challenge. This study addresses the aforementioned challenge by employing manganese (Mn) doping to achieve size uniformity in CsPbBr₃ perovskite QDs without the necessity for precise control of the reaction conditions. By optimizing the Mn:Pb ratio, it is possible to successfully dope CsPbBr₃ QDs with appropriate concentrations of Mn²⁺ and achieve a uniform size distribution. The spectroscopic measurements on single QDs indicate that the appropriate Mn²⁺ concentrations can result in a narrower spectral linewidth, a longer photoluminescence (PL) lifetime, and a reduced biexciton Auger recombination rate, thus positively affecting the PL properties. This study not only simplifies the size control of perovskite QDs, but also demonstrates the potential of Mn-doped CsPbBr₃ QDs for narrow linewidth light-emitting diode applications.

Named Entity Recognition (NER) is a fundamental and pivotal stage in the development of various knowledge-based support systems, including knowledge retrieval and question-answering systems. In the domain of pig diseases, Chinese NER models encounter several challenges such as the scarcity of annotated data, domain-specific vocabulary, diverse entity categories, and ambiguous entity boundaries. To address these challenges, we propose PDCNER, a Pig Disease Chinese Named Entity Recognition method leveraging lexicon-enhanced BERT and contrastive learning. Firstly, we construct a domain-specific lexicon and pre-train word embeddings in the pig disease domain. Secondly, we integrate lexicon information of pig diseases into the lower layers of BERT using a Lexicon Adapter layer, which employs char-word pair sequences. Thirdly, to enhance feature representation, we propose a lexicon-enhanced contrastive loss layer on top of BERT. Finally, a Conditional Random Field (CRF) layer is employed as the model's decoder. Experimental results show that our proposed model demonstrates superior performance over several mainstream models, achieving a precision of 87.76%, a recall of 86.97%, and an F1-score of 87.36%. The proposed model outperforms BERT-BiLSTM-CRF and LEBERT by 14.05% and 6.8%, respectively, with only 10% of the samples available, showcasing its robustness in data scarcity scenarios. Furthermore, the model exhibits generalizability across publicly available datasets. Our work provides reliable technical support for the information extraction of pig diseases in Chinese and can be easily extended to other domains, thereby facilitating seamless adaptation for named entity identification across diverse contexts. The codes have been open-sourced at https://github.com/tufeifei923/pdcner.

The basic helix loop helix (bHLH) transcription factors play crucial roles in plant growth, development, and stress responses. However, their identification and insight understanding in rubber trees remain largely uncovered. In this study, the bHLH gene family was explored and characterized in rubber trees using systematic bioinformatics approaches. In total, 180 bHLH genes were identified in the rubber tree genome, distributed unevenly across 18 chromosomes, and phylogenetic analysis classified these genes into 23 distinct subfamilies. Promoter regions revealed a high density of cis-elements responsive to light and hormones. Enrichment analysis indicated involvement in numerous biological processes, including growth, development, hormone responses, abiotic stress resistance, and secondary metabolite biosynthesis. Protein interaction network analysis identified extensive interactions between HbbHLH genes and other functional genes, forming key clusters related to iron homeostasis, plant growth, and stomatal development. Expression profiling of HbbHLH genes have demonstrated varied responses to endogenous and environmental changes. RT-qPCR of eleven HbbHLH genes in different tissues and under ethylene, jasmonic acid, and cold treatments revealed tissue-specific expression patterns and significant responses to these stimuli, highlighting the roles of these genes in hormone and cold stress responses. These findings establish a framework for exploring the molecular functions of bHLH transcription factors in rubber trees.

This study evaluated the presence of Human Papillomavirus (HPV) and Bovine Leukemia Virus (BLV) DNA in breast cancer (BC) samples from women in Northeastern Brazil. We analyzed 186 formalin-fixed, paraffin-embedded tissue block samples using PCR and qPCR to detect HPV and BLV DNA. BLV DNA was not detected in any BC patients. However, HPV DNA was found in 46.2\% of the BC samples: 44.6\% were positive for HPV16, 3.5\% for HPV31, and 2\% were coinfected with HPV16 and HPV31. Additionally, we found an association between HPV-positive BC and Ki-67 expression (P=0.03, OR=1.85; CI=1.02-3.34), as well as between HPV31-positive BC and mitotic index (P=0.047). Although BLV was not detected in BC patients from Northeastern Brazil, the association between HPV and cell proliferation markers warrants further investigation, as HPV may contribute to the aggressiveness of BC in these patients.

GCTs are developmental tumors and likely to reflect ontogenetic and teratogenetic determinants. The objective was to identify syndromes with or without congenital anomalies and non-syndromic defects as potential risk factors. Patients with extracranial GCTs (eGCTs) registered in MAKEI 96/MAHO 98 between 1996 and 2017 were used. According to Teilum's holistic concept malignant and benign teratomas were registered. We used a case control study design with Orphanet as a reference group for syndromic defects and the Mainz birth registry (EUROCAT) for congenital anomalies at birth. Co-occurring genetic syndromes and/or congenital anomalies were assessed accordingly. Odds ratios and 95% confidence intervals were calculated and p-values for Fisher’s exact test with Bonferroni correction if needed. A strong association was confirmed for Swyer (OR 338.6, 95% CI 43.7-2623.6) and Currarino syndrome (OR 34.2, 95% CI 13.2-88.6). We additionally found 17 isolated cases of eGCT with a wide range of syndromes, however not significantly associated following Bonferroni correction. All these cases pertained to girls. Regarding non-syndromic defects, no association with eGCTs could be identified. In our study we confirmed a strong association for Swyer and Currarino syndromes with additional congenital anomalies.

Objetives/Background: Vitamin D Binding Protein (VDBP) and free vitamin D are new markers that are being studied as a possible markers of vitamin D status. The main aim of our study was to analyse the VDBP genotype and quantify the levels of VDBP and free vitamin D in a sample of cystic fibrosis (CF) patients. Methods: Multicentre, cross-sectional and prospective study including patients with CF, exocrine pancreatic insufficiency who were clinically stable. We investigated vitamin D levels (total and free) and the different VDBP haplotypes. Free vitamin D levels were measured using an electro-chemiluminescence assay. Results: A sample of 48 patients was obtained (52% male; median age 13.8 years). The most common allele of VDBP was Gc1s (72%)>Gc2 (52%)>Gc1f (27%). Median calcidiol was 21.2 ng/ml (IR 15.3 - 26.9), 81% had levels in the insufficiency range: 23 patients (48%) below 20 ng/ml, and 16 (33%) between 20 and 30 ng/ml. The median free vitamin D level was 4.2 pg/ml (IR 3.9 – 5.6). A positive correlation was observed between calcidiol and free vitamin D levels (r=0.871; p<0.0001). After adjustment for season, vitamin D supplementation, sex and CFrelated diabetes, patients with Gc1f polymorphism had a lower risk of vitamin D deficiency, OR 0.22 (95% CI 0.05 – 0.99), p=0.027. A negative linear trend was observed between the polymorphisms grouped into 3 categories (Gc1/Gc1, Gc1/Gc2, and Gc2/Gc2, in that order) and vitamin D and free vitamin D levels (p=0.025 and p=0.033, respectively). Conclusion: In CF, as in the general population, the most common VDBP haplotype in Caucasian race is Gc1s. VDBP polymorphisms influence serum vitamin D and free vitamin D levels in CF patients. There is a good correlation between free vitamin D and calcidiol levels, suggesting that measuring the latter in CF does not seem to provide any additional benefit.

Astragalus plants belong to the legume family and have obvious rhizosphere effect. The northwestern area of Yunnan China is the main distribution region of Astragalus plants with high application value, but low recognition and resource reserves. The aim of this research is to explore the species diversity of cultivable rhizosphere fungi derived from A. acaulis, A. forrestii, and A. ernestii growing in special high-cold environment of northwest Yunnan, and discover anti-infective components from these fungi. A total of 93 fungal strains belonging to 38 species in 18 genera were isolated and identified. Antibacterial and antimalarial screening yielded 10 target strains. Among them, the ethyl acetate crude extract of the fungus Aspergillus calidoustus AA12 from A. acaulis fermentation substance showed a broad antibacterial spectrum and the best antimalarial activity. Further chemical investigation led to the first discovery of seven compounds from the species of A. calidoustus, including a sesterterpine 6-epi-ophiobolin G (1), two sesquiterpenes penicisochroman A (2), pergillin (3) and 7-methyl-2-(1-methylethylethlidene)-furo[3,2-H]isoquinoline-3-one (4), and three polyketides trypacidin (5), 1,2-seco-trypacidin (6) and questin (7). Compound 1 exhibited moderate to strong antibacterial activity against six Gram-positive pathogens with the minimum inhibitory concentration (MIC) ranging from 25 to 6.25 μg/mL, and prominent inhibitory effect on the biofilm of Streptococcus agalactiae at MIC value of 3.125 μg/mL. This compound also displayed potent antimalarial activity against Plasmodium falciparum strains 3D7 and chloroquine-resistant Dd2 at the half maximal inhibitory concentration (IC50) values of 3.319 and 4.340 µmol/L at 72 h, respectively. This study contributed to our understanding of the cultivable rhizosphere fungi Astragalus-derived in special high-cold environment and further increased the library of fungi available for natural anti-infectious products screening.

The combination of several therapeutic strategies is often seen as a good way to decrease the resistance rates, since bacteria overcome better single-drug treatments than multi-drug ones. This strategy is especially attractive when several targets and subpopulations are affected, as it is the case of Klebsiella pneumoniae persister cells, a subpopulation of bacteria able to transiently survive antibiotic exposures. This work aims to evaluate the potential of a repurposed anticancer drug, mitomycin C, combined with the K. pneumoniae lytic phage vB_KpnM-VAC13 in vitro and the safety in an in vivo murine model against two clinical isolates of this pathogen, one of them exhibiting an imipenem-persister phenotype. At the same time, we verified the absence of toxicity of mitomycin C at the concentration using the human chondrocyte cell line T/C28a2. The viability of these human cells was checked both by cytotoxicity assays and flow cytometry.

Background: The workplace burnout syndrome is often associated with particular aspects of certain job positions, especially those which entail working with people with special needs. The burnout syndrome in healthcare jobs is a serious problem which has grown into an epidemic among healthcare workers and associates. Objectives: The aim of this research is to assess the presence of stress and burnout syndrome at work with healthcare workers, expert workers, professional associates and associates in social service institutions in Belgrade. Material and Methods: This research has been conducted in the form of a cross-sectional study of a representative sample in social institutions in Belgrade. It has been conducted from March to the end of June of 2023. The sample of the study had 491 participants. The questionnaires used were a structured instrument with social-demographic and social-economic characteristics, workplace characteristics, life style characteristics, and the following questionnaires: DASS-21, Copenhagen, Brief Resilience Scale, and Brief Resilient Coping Scale. Results: The end results indicate the following to be significant risk factors for the occurrence of workplace burnout syndrome: overtime (OR=2.62; CI=1.50-4.56), BRS average score (OR=0.28; CI=0.17-0.44), DASS21 D heightened depression (OR=2.09; CI=1.1-4.04), DASS21 A heightened anxiety (OR=2.38; CI=1.34-4.21), DASS21 S heightened stress (OR=2.08; CI=1.11-3.89). The only protective risk factor which stood out was the self-assessment of health levels (OR=0.60; CI=0.42-0.85). Conclusion: Overtime is a significant predictor of workplace burnout. Apart from it, other significant predictors of workplace burnout were heightened depression, anxiety, and stress levels.

Oxidative stress (OS) plays a crucial role in placental pathogenesis and pregnancy-related complications. This review explores OS's impact on placental development and function, focusing on novel biomarkers for early detection of at-risk pregnancies and emerging therapeutic strategies. We analyzed recent research on OS in placental pathophysiology, examining its sources, mechanisms, and effects. While trophoblast invasion under low-oxygen conditions and hypoxia-induced OS regulate physiological placental development, excessive OS can lead to complications like miscarriage, preeclampsia, and intrauterine growth restriction. Promising OS biomarkers, including malondialdehyde, 8-isoprostane, and the sFlt-1/PlGF ratio, show potential for early detection of pregnancy complications. Therapeutic strategies targeting OS, such as mitochondria-targeted antioxidants, Nrf2 activators, and gasotransmitter therapies, demonstrate encouraging preclinical results. However, clinical translation remains challenging. Future research should focus on validating these biomarkers in large-scale studies and developing personalized therapies to modulate placental OS. Emerging approaches like extracellular vesicle-based therapies and nanomedicine warrant further investigation for both diagnostic and therapeutic applications in pregnancy-related complications. Integrating OS biomarkers with other molecular and cellular markers offers improved potential for early identification of at-risk pregnancies.

Posterior retroperitoneal laparoscopic adrenalectomy (PRLA) has emerged as a revolutionary minimally invasive technique for adrenal gland surgery, offering significant advantages over traditional open approaches. This narrative review aims to provide a comprehensive update on PRLA, focusing on its anatomical foundations, surgical technique, and clinical implications. We conducted an extensive review of the current literature and surgical practices to elucidate the key aspects of PRLA. The procedure leverages a unique "backdoor" approach, accessing the adrenal glands through the retroperitoneum, which necessitates a thorough understanding of posterior abdominal wall and retroperitoneal anatomy. Proper patient selection, meticulous surgical planning, and adherence to key technical principles are paramount for successful outcomes. The surgical technique is described step-by-step, emphasizing critical aspects such as patient positioning, trocar placement, and adrenal dissection. PRLA demonstrates reduced postoperative pain, shorter hospital stays, and faster recovery times compared to open surgery, while maintaining comparable oncological outcomes for appropriately selected cases. However, the technique presents unique challenges, including a confined working space and the need for surgeons to adapt to a posterior anatomical perspective. We conclude that PRLA, in the right clinical setting, offers a safe and effective alternative to traditional adrenalectomy approaches. Future research should focus on expanding indications and refining techniques to further improve patient outcomes.

Preeclampsia (PE) is a complex and multifaceted obstetric syndrome characterized by several distinct molecular subtypes. It complicates up to 5% of pregnancies and significantly contributes to maternal and newborn morbidity, thereby diminishing the long-term quality of life for affected women. Due to the widespread dissatisfaction with the effectiveness of existing approaches for assessing PE risk, there is a pressing need for ongoing research to identify newer, more accurate predictors. This study aimed to investigate early changes in the maternal serum proteome and associated signaling pathways. The levels of 125 maternal serum proteins at 11-13 weeks of gestation were quantified using liquid chromatography-multiple reaction monitoring mass spectrometry (LC-MRM MS) with the BAK-125 kit. Ten serum proteins emerged as potential early markers for PE: Apolipoprotein M (APOM), Complement C1q subcomponent subunit B (C1QB), Lysozyme (LYZ), Prothrombin (F2), Albumin (ALB), Zinc-alpha-2-glycoprotein (AZGP1), Tenascin-X (TNXB), Alpha-1-antitrypsin (SERPINA1), Attractin (ATRN), and Apolipoprotein A-IV (APOA4). Notably, nine of these proteins have previously been associated with PE in prior research, underscoring the consistency and reliability of our findings. These proteins play key roles in critical molecular processes, including complement and coagulation cascades, platelet activation, and insulin-like growth factor pathways. To improve the early prediction of PE, a highly effective Support Vector Machine (SVM) model was developed, analyzing 19 maternal serum proteins from the first trimester. This model achieved an Area Under the Curve (AUC) of 0.91, with 87% sensitivity and 95% specificity, and a hazard ratio (HR) of 13.5 (4.6 - 40.8) with p&lt;0.001. These findings demonstrate that serum protein-based SVM models possess significantly higher predictive power compared to the routine first-trimester screening test, highlighting their superior utility in the early detection and risk stratification of PE.

Aging-related disorders pose significant challenges due to their complex interplay of physiological and metabolic factors, including inflammation, oxidative stress, and mitochondrial dysfunction. Curcumin, a natural compound with potent antioxidant and anti-inflammatory properties, has emerged as a promising candidate for mitigating these age-related processes. However, gaps in understanding the precise mechanisms of curcumin's effects and the optimal dosages for different conditions necessitate further investigation. This systematic review synthesizes current evidence on curcumin's potential in addressing age-related disorders, emphasizing its impact on cognitive function, neurodegeneration, and muscle health in older adults. By evaluating the safety, efficacy, and mechanisms of action of curcumin supplementation, this review aims to provide insights into its therapeutic potential for promoting healthy aging. A systematic search across three databases using specific keywords yielded 2,256 documents, leading to the selection of 15 clinical trials for synthesis. Here we highlight the promising potential of curcumin as a multifaceted therapeutic agent in combating age-related disorders. The findings of this review suggest that curcumin could offer a natural and effective approach to enhancing the quality of life of aging individuals. Further research and well-designed clinical trials are essential to validate these findings and optimize the use of curcumin in personalized medicine approaches for age-related conditions.

Natural and sustainable plant-based antioxidants and antimicrobials are highly desirable for improving food quality and safety. The present investigation assessed the antimicrobial and antioxidant properties of active components from Alkanna tinctoria (herb) roots, also known as Ratanjot root. Two methods were used to extract active components: microwave-assisted hot water (MAHW) and ethanol and air-dried. MAHW extract yielded 6.29% while the ethanol yielded 18.27%, suggesting superior Ratanjot root extract powder (RRP) solubility in ethanol over water. The ethanol extract showed significantly higher antioxidant activity than the MAHW extract. Gas chromatography and mass-spec analysis revealed three major phenolic compounds: Butanoic acid, 3-hydroxy-3-methyl-; Arnebin 7, and Diisooctylpthalate. The color attributes (L*, a*, b*, hab, C*ab) for the ethanolic and MAHW extracts revealed significant differences (P < 0.05) in all the above parameters for both types of extracts, except for yellowness (b*) and chroma (C*ab) values. The ethanol extract exhibited antimicrobial activity against 14 bacterial species, with a signifi-cantly higher inhibitory effect against Gram-positive bacteria (Listeria monocytogenes and Staphylococcus aureus) than the Gram-negative bacteria (Salmonella enterica serovar Typhimurium and Escherichia coli). The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) were both 25 mg/ml for the Gram-negative bacteria, while the MIC and MBC concentrations varied for Gram-positive bacteria (0.049 - 0.098 mg/ml and 0.098 - 0.195 mg/ml) and the antimicrobial effect was bactericidal. The antimicrobial activities of RRP extract remained stable under broad temperature (37-100°C) and pH (2-6) conditions, as well as during refrigerated storage for 30 days. Application of RRP at 1% (10 mg/g) and 2.5% (25 mg/g) levels in a cooked chicken meatball model system prevented lipid oxidation and improved sensory attributes and retarded microbial growth during refrigerated (4°C) storage for 20 days. Furthermore, the RRP extract was non-toxic when tested with sheep erythrocytes and did not inhibit the growth of probiotics, Lacticaseibacillus casei, and Lactiplantibacillus plantarum. In conclusion, the study suggests that RRP possesses excellent antimicrobial and antioxidant activities, thus making it suitable for food preservation.

Background: Pancreatic neuroendocrine tumors (pNETs) represents a rare subset of pancreatic cancer. Functional tumors caused hormonal changes and clinical syndromes, while non-functional ones are often diagnosed late. Surgical management need a multidisciplinary planning, involving enucleation, distal pancreatectomy with or without spleen preserving, cen-tral pancreatectomy, pancreaticoduodectomy or total pancreatectomy. Minimally invasive ap-proach increased in the last decade compared to the open technique. The aim of this study is to analyze current diagnostic and surgical trends for pNETs, to identify better interventions and their outcomes. Methods: The study adhered to PRISMA guidelines, conducting a systematic review of literature from May 2008 to March 2022 across multiple databases. Several combinations of keywords was used ("NET", "pancreatic", "surgery", "laparoscopic", "minimally invasive", "robotic”, “enuclea-tion”,“parenchima sparing”) and relevant article references was manually checked. Manuscript quality was evaluated. Results: The study screened 3867 manuscripts, twelve studies were selected, primarily from Ita-ly, the United States, and China. A total of 7767 surgical treated patients was collected from 160 included centers. The mean age was 56,3 y.o. Enucleations (EN) and distal pancreatectomy (DP) was the most common performed surgery and represents 43.4% and 38.6% of the total interven-tions, respectively. Pancreatic fistula, post operative bleeding, re-operation and follow up was recorded and analyzed. Conclusions: Enucleation show better postoperative outcomes and lower mortality rates com-pared to pancreaticoduodenectomy (PD) or distal pancreatectomy (DP), despite similar risks of postoperative pancreatic fistula (POPF). DP was preferred over enucleation for pancreas body-tail, while laparoscopic enucleation is better for head pNETs.

Nature-Based Solutions (NBSs) can help to achieve multiple Water-Ecosystem-Food Nexus Do-main Objectives & Nexus Resilience Qualities, facilitating the transition to more resilient agrifood systems and providing an evidence base for a broader Nexus policy dialogue. This paper de-scribes the stepwise methodology developed in the EU-funded LENSES project to carry out a comprehensive analysis of NBSs in 6 pilot areas in 5 Mediterranean countries, and presents the results of NBSs implementation in 4 pilot areas, highlighting obstacles and opportunities. The methodology includes the development of an analytical evaluation framework and of a com-prehensive catalogue of Nexus-related NBSs, whose suitability needs to be assessed at the local level to achieve better use of protected/natural ecosystems, increase the sustainability and mul-tifunctionality of managed ecosystems and design and manage novel ecosystems. Subsequently, in a collective learning process which supported the operationalisation of the WEF Nexus, NBSs were identified that address specific contextual vulnerabilities, improve water distribution and enhance food security, while preserving ecosystems and supporting adaptation to climate change. The added value of the proposed methodology lies in the multi-stakeholder participatory approach to gain in-depth knowledge of local agri-food systems, including their main WEF-related challenges, and to facilitate overcoming barriers to NBS implementation.

Culex quinquefasciatus is an important target for vector control because of its ability to transmit pathogens that cause disease. Most populations are resistant to pyrethroids and often to organophosphates, the two most common classes of active ingredients used by public health agencies. A knockdown resistance (kdr) mutation, resulting in a change from a leucine to phenylalanine in the voltage gated sodium channel, is one mechanism contributing to the pyrethroid resistant phenotype. Enzymatic resistance has also been shown to play a very important role. Recent studies have shown strong resistance in populations even when kdr is relatively low which indicates factors other than kdr may be larger contributors to resistance. In this study, we examined on a statewide scale (over 70 populations), the strength of the correlation between resistance in the CDC bottle bioassay and the kdr genotypes and allele frequencies. Spearman correlation analysis showed only moderate (-0.51) and weak (-0.29) correlation between the kdr genotype and permethrin and deltamethrin respectively. The frequency of the kdr allele was an even weaker correlate. These results indicate, in contrast to Aedes aegypti, assessing kdr in populations of Culex quinquefasciatus is not a good surrogate for phenotypic resistance testing.

The chemical investigation of the anti-yeast methanol extract from the stem bark of Terminalia mantaly led to the isolation of seven compounds: 3-O-methyl-4-O-α-rhamnopyranoside ellagic acid (1), 3-O-mehylellagic acid (2), arjungenin or 2,3,19,23-tetrahydroxyolean-12-en-28-oïc acid (3), arjunglucoside or 2,3,19,23-tetrahydroxyolean-12-en-28-oïc acid glucopyranoside (4), 2α,3α,24-trihydroxyolean-11,13(18)-dien-28-oïc acid (5), stigmasterol (6), stigmasterol 3-O-β-D-glucopyranoside (7). Their structures were established by means of spectroscopic analysis and comparison with published data. Compounds 1-5 were tested in vitro for activity against three pathogenic yeast isolates, Candida albicans, Candida parapsilosis and Candida krusei. The activity of compounds 1, 2 and 4 were comparable to that of the reference compound fluconazole (MIC values below 32 µg/ml) against the three tested yeast isolates. They were also tested for inhibitory properties against four enzymes of metabolic significance: Glucose-6-Phosphate Deshydrogenase (G6PD), human erythrocyte Carbonic anhydrase I and II (hCA I and hCA II), Glutathione S-transferase (GST). Compound 4 showed highly potent inhibitory property against the four tested enzymes with overall IC₅₀ values below 4 µM and inhibitory constant (Ki) <3 µM.