In this work, the Dirac operator in case where one of nonseparated boundary conditions involves a linear function of spectral parameter, has been introduced. We found necessary and sufficient conditions for solving the inverse spectral problem for this operator are found. Also are proved here, auxiliary assertions used in obtaining necessary and sufficient conditions .

In this paper, we prove the reverse Hardy inequality for Hardy operator in weighted variable Lebesgue spaces with exponent less than one. In particular, we establish necessary and sufficient conditions on weight functions for the validity of the reverse Hardy inequality for Hardy operator in weighted variable Lebesgue spaces with negative exponents. It should be noted that in the case of variable Lebesgue space L p ( x ) ( 0 , ∞ ) for 0 ( x) <1 , the obtained necessary and sufficient conditions on the weight functions are different and coincide for some classes of variable exponents. Also, we prove similar results for the dual Hardy operator. The results are illustrated by an example.

Empréstimos linguísticos: conceitos centrais e o caso dowasei eigo 11Resumo: Este ensaio se propõe a delinear, em linhas gerais, o fenômeno conhecido por “empréstimo linguístico” e apontar os principais procedimentos por meio dos quais itens estrangeiros são integrados a outro sistema linguístico. Ademais, como um caso em estudo, a questão do wasei eigo e de sua tipologia serão tratados a fim de enquadrar os empréstimos como fatos da cultura e da língua de chegada.Palavras-chave : Empréstimo linguístico, wasei eigo , inglês do Japão.Abstract: This essay aims to define the linguistic phenomenon known as ”loanwords” and identify the main processes through which foreign elements are integrated into a different linguistic system. Additionally, as a case study, the linguistic typology of wasei eigo will be discussed to contextualize loanwords within the receiving culture and language.Keywords: Loanwords, wasei eigo, Japanese-English;

Note: It should be mentioned that Rectna  has been studied in recent years, especially in the matter of power transmission in the microwave band. For example, in theory,  for a single frequency of 9.2 GHz, more than 10% efficiency is predicted  .Of course, this is the fact that the practical efficiency of making these materials may  be slightly different and should be determined in practice. The dipole antenna with  linear polarization and 2/λ length, which has a relative bandwidth of 11%,  will be able to collect about pW 75.2. For this reason, if  using an antenna with double polarization, the power of pW 5.5 will be obtained. Due  to the low reception power of each independent antenna, it is customary to use antenna arrays  in this cell, which has its own rules and methods .

Indoor localization within buildings is paramount due to its diverse applications, including the Internet of Things (IoT), healthcare, and personnel monitoring. To improve the performance of indoor localization, this study proposes an algorithm combining Deep Neural Networks (DNNs) and Convolutional Neural Networks (CNNs) used within a hybrid model that uses both cellular technology, i.e, base station (BS) and Wi-Fi access point (AP). Within a realistic environment, we evaluate the performance of our approach across four scenarios: (1) (2 APs + 2 BSs), (2) (1 AP + 2 BSs), (3) (2 APs), and (4) (2 BSs). Additionally, we consider both stationary and seated user positions. Our results demonstrate significant improvements over existing methods. Specifically, in the 2 APs + 2 BSs scenario, we achieve an average Euclidean distance error of 1.04 meters, with a maximum error of 2.51 meters, and the Root Mean Square Error (RMSE) of 1.15 meters. We also obtain the corresponding Cumulative Distribution Function (CDF) for the error which indicates that 90% of the time, the error is less than 1.69 meters. Our hybrid model achieves over 99% accuracy in classifying different building floors and over 88% accuracy in identifying user states (e.g., standing or sitting). We validate our approach using smartphone-based indoor localization in a two story residential building with robust construction materials and double-layered walls.

In this paper, an assessment is provided on the influence of lightning peak amplitude distributions on wind turbines (WTs) in the Adriatic hinterland. It investigates the impact of various probability distributions (including Gaussian, Poisson, and logarithmic distributions) on the equivalent exposure area using a fixed radius. Additionally, the study evaluates how different radiuses affect the equivalent exposure area under a fixed probability distribution. By comparing the actual number of lightning strikes with the theoretical number of lightning strikes, the area struck by lightning each year can be estimated. In addition, the bypass events in the area can be calculated based on the efficiency of the lightning protection system (LPS) to protect the wind turbines. The lightning protection area is also calculated according to the International Electrotechnical Commission standard (IEC) 62305-3.

Fertilisation is based on the tight interaction between sperm and egg and both sperm and egg proteomes are known to evolve and diverge rapidly even between closely related species. Understanding the sperm proteome therefore provides key insights into the mechanisms involved during fertilisation and the fusion between sperm and egg. Despite being a commonly used model organism for reproductive research, very little is currently understood about the zebrafish Danio rerio sperm proteome. We performed in depth proteomics analysis with six pooled samples containing ejaculates from ten males each. We confidently identified 5410 proteins, from which a total of 3900 GeneIDs were generated leading to 1720 Gene Ontology terms. This number of proteins is larger than the number of proteins described in sperm proteomes of other species.

Teleost fishes are a highly diverse and ecologically essential group of aquatic vertebrates and include coho salmon, Onchorhynchus kisutch. Coho are semelparous and all ovarian follicles develop synchronously. Owing to their ubiquitous distribution, teleost provide critical sources of food worldwide through subsistence, commercial fisheries, and aquaculture. Enhancement of commercial hatchery practices requires a detailed knowledge of teleost reproductive physiology. Despite decades of research on teleost reproductive processes, an in-depth proteome of teleost ovarian development has yet to be generated. We describe a coho salmon ovarian proteome of over 5700 proteins, generated with data independent acquisition, revealing the suite of detectable proteins that change through the transition from primary to secondary ovarian follicle development. This transition is critical for puberty onset, egg quality, and further embryonic development. Primary ovarian follicle development was marked by differential abundances of proteins involved in carbohydrate metabolism, protein turnover, and the complement pathway, suggesting elevated metabolism as the oocytes enter maturation. The greatest proteomic shift occurred during the transition from primary to secondary follicle growth, with increased abundance of proteins underlying cortical alveoli formation, extracellular matrix reorganization, iron binding, and cell-cell signaling. This work provides a foundation for identifying biomarkers of salmon oocyte stage and quality.

This study focuses on developing an intelligent vest to improve posture by integrating Marginal Absolute Relative Gradient (MARG) sensors. The vest, designed with lightweight and flexible materials, provides real-time visual and tactile feedback to enhance posture while ensuring comfort. Utilizing compact Arduino technology from Flora Adafruit, the vest tracks roll and pitch angles at the neck and shoulders. Experimental data showed that when the neck was tilted forward, the average pitch angle was-61.80°, while a rightward lean of the body resulted in a neck pitch angle of-60.34° and a right shoulder roll angle of 13.54°. The correlation matrix revealed a negative correlation of-0.29 between the neck and shoulder roll towards the right and a positive correlation of 0.46 between their pitch movements. The neck and shoulder exhibited synchronized movement, simultaneously flexing forward and tilting right. When the body tilted left, the neck had a pitch angle of-57.48° and the left shoulder a roll angle of-18.24°. A weak correlation coefficient of 0.07 was found for roll movements between the neck and shoulder and-0.18 for pitch, indicating independent movement patterns. User feedback rated LED feedback highly (mean = 4.3), while haptic feedback received low rates (mean = 3.6). Comfort (mean = 4.40) and posture correction (mean = 4.30) were also positively received. The results suggest that the vest effectively provides detailed feedback and continuous monitoring, highlighting its potential in health-related intelligent Garments for posture correction.

Background and Purpose Antibody-drug conjugates (ADCs) represent a therapeutic modality that guides chemotherapies to tumoral cells by using antibodies against tumor associated antigens (TAAs). The antibody and the chemotherapy or payload are attached by a chemical structure called the linker. The strategy for the development of this type of drugs was based on several rational pillars, including the use of a very potent payload and the use of specific antibodies acting only on antigens expressed on tumoral cells. Experimental Approach In this article, by using data from all approved ADCs that have received regulatory approval, we explore the contribution of each ADC component to clinical activity. Key Results We have identified that the potency of the payload and its amount -evaluated by the drug to antibody ratio (DAR)- do not relate to clinical efficacy. Additionally, some ADCs have been developed against antigens expressed in non-transformed tissues producing clinical activity, suggesting that TAA specificity is not a mandatory requirement. Finally, we observed that ADCs with payloads harboring more favorable physicochemical characteristics showed the greater activity, and indeed were those that used linkers with site-specific conjugation. Conclusion and Implications Based on currently available data, our study provides insights as to the best way to develop novel ADCs in the future.

Aim When introduced species invade new environments, they often overlap with native species currently occupying those spaces, either spatially through suitable habitat or environmentally through their realized niches. The goal of this research is to determine the overlap between native New England cottontail (Sylvilagus transitionalis) and introduced eastern cottontail (Sylvilagus floridanus) to identify potential areas of invasion by the eastern cottontail and potential areas of refuge for New England cottontail from eastern cottontail. Location Connecticut, USA Methods Using presence data from a regional, standardized monitoring protocol, we developed habitat suitability models using Maxent and conducted niche overlap analyses using Principal Component Analysis. We used several covariates that reflected proximity to habitat characteristics, such as young forest, shrubland, and understory, as well as proximity to threats, such as development. We also included topographic and climatic covariates. We used the Guidos software to categorize the spatial arrangement of young forest, shrubland, and understory vegetation. Results We found that the overlap in both niches and suitable habitat was high for two species. Only areas of low precipitation and high elevation shifted niches in favor of New England cottontail. We also found that habitat suitability for New England cottontail was higher when patches of mature forest without understory were within complexes of young forest, shrubland, and mature forest with understory. Main Conclusions Increasing habitat heterogeneity could improve the habitat suitability of existing patches or create new patches for New England cottontail. However, habitat management alone is likely not enough to discourage eastern cottontail, thus direct species management such as removal of eastern cottontail and augmentation of New England cottontail populations should be explored.

β-amyloid cleaving enzyme 1 (BACE1) is the principal target of drug design towards the remedy of Alzheimer’s disease. A recent report outlines that amidine based oxazine derivative compound (C1) strongly halt the activity of BACE1. Though, detail at the atomic level of C1 binding mechanism towards BACE1 is unknown. Therefore, docking, molecular dynamics (MD) simulations and binding free energy (MM−PBSA) of apo−BACE1 and BACE1–C1 were performed to shed light on the binding mechanism of C1 against activity of BACE1. The MD simulations result indicates that C1 exhibits a strong interaction with Asp protease (Asp32 and Asp228) and dynamic subpockets of BACE1. The hydrogen−bonding and hydrophobic interactions of C1 towards flap (Val67−Glu77) of BACE1 limit the flap motion thereby achieved a close (inactive) position. The mean distance (d 1) of flap tip residues (Thr72 and Ser325) of apo−BACE1 (~1.3 nm) showed more flexibility and open conformation whereas BACE1−C1 adapted a close conformation with decrease in average distance d 1 (~1.1 nm) during the simulation. The slight twisting (curl) observed in apo−BACE1 with dihedral angle ( ϕ) value (−47.33°) as compare to BACE1−C1 (−39.83°) which shows more flexibility between flap tip residues with Asp protease in apo−BACE1. The values of θ 1 (Thr72−Asp32−Ser325) has ∼43.15° where θ 2 (Thr72−Asp228−Ser325) has ∼61.61° quite higher in apo−BACE1 highlights the opening of the flap in contrast to BACE1−C1 having low θ 1 and θ 2 values (∼33.6° and ∼51.48°) showed flap is in closed position. MM−PBSA results highlights that C1 binds to BACE1 with suitable binding free energy (Δ G binding= –51.5 ± 4.4 kcal/mol) and per-residue binding free energy showed that Asp protease, 10s loop residue Gln12, active subpockets (S1, S3- S4 and S1´-S3′) and flap (Pro70, Tyr71, Thr72, Gln73) of BACE1 play a significant role in the binding of C1 to BACE1. The findings of this study provide inhibitory mechanism of C1 to block BACE1 activity which in future will aid the development of new BACE1 inhibitors with greater efficacy.

Urbanisation alters the environment of organisms, creating new challenges and opportunities. In ants, urbanisation has been shown to increase resistance to temperature and to pollutants. Ant queens are expected to be more protected from environmental variation compared to workers thanks to social buffering effects. We assessed how urbanisation and social buffering affect gene expression in workers and queens of the ant Temnothorax nylanderi, a species that inhabits both environments. We tested whether whole body gene expression differed between urban and forest colonies and whether this differential expression was more pronounced in workers compared to queens due to social buffering. We further examined whether differential expression held after rearing colonies under a common garden laboratory setup. We found that habitat had no clear influence on gene expression in queens and workers, whereas, as expected, the number of differentially expressed genes between workers and queens was large (2830 genes). We also found 661 genes differentially expressed between the colonies that remained in the field and those that were reared in the laboratory for eight months. The effect of rearing conditions on gene activity was greater in workers than in queens, supporting the idea that queens are partially protected from environmental variation. We found minimal transcriptional differences between habitats which is intriguing because of the previously observed phenotypic differences. We provide, for the first time, support at the level of gene expression that laboratory rearing conditions induce major changes in gene expression and that queens undergo social buffering during such environmental change.

This article proposes a class of asymmetric 2 ×n resistor network model which contains multiple independent resistors, the study of asymmetric resistor network models is a challenge. We conducted in-depth research on this issue using the RT-V theory (Chinese Physics B, 2017, 26(9): 090503) and achieved new theoretical breakthroughs. This paper derived five original equivalent resistance formulae for this asymmetric 2 ×n circuit network, and also discusses the analytical expressions for equivalent resistance in different special cases, and several interesting results have been derived, indicating that the original resistance formula has powerful functionality. Finally, visual graphics of two types of equivalent resistances are provided using MATLAB drawing tools, which reveals the law of equivalent resistance changing with resistance variables. The research theory and technology in this article will provide a new theoretical basis for related scientific, engineering, and simulation research.

The chip industry is essential for national security and economic development, with integrated circuit (IC) reverse engineering playing a vital role in analyzing chip structures. This process involves several steps, including layer-by-layer image acquisition using scanning electron microscopy (SEM), device identification, gate net extraction, and function inference. Segmenting electrical components and metal lines from IC images is crucial for these analyses. However, traditional image segmentation methods often fail to handle the complex and variable conditions of IC images due to insufficient expert knowledge. This study introduces an improved approach, using the UNet ++ architecture and effentnet-b7 as the encoder, called the E- UNet++ model. A post-processing denoising stage is added that contains Hough circle detection and median filtering for extracting metal lines and perforations in IC images. The primary contributions of this method are: (1) it enables fully automatic detection of metal lines and vias without manual intervention, and (2) it combines E-UNet++, Hough circle detection, and median filtering in a hybrid approach to accurately locate metal lines and vias. Experimental results on over ten thousand IC images, each measuring 1024×1024 and provided by a company, show that training with just 393 images allows the E-UNet++ model to effectively segment metal lines and vias. The average intersection over union (mIoU) is 98.09% and the mean pixel accuracy (MPA) is 99.06%, surpassing the performance of existing methods.

Introduction: Benzodiazepines (BZDs) are a widely prescribed class of psychoactive drugs used in the treatment of various neuropsychiatric disorders, including insomnia and anxiety. In addition to their anxiolytic and hypnotic properties, BZDs possess anticonvulsant and muscle relaxant effects, expanding their therapeutic range. Their primary mechanism of action involves the potentiation of γ-amino butyric acid (GABA), an inhibitory neurotransmitter, leading to reduced neuronal excitability and alleviation of stress and anxiety. Although BZDs are generally considered safe for short-term use, extended or frequent administration can lead to tolerance, dependence, and significant adverse drug reactions (ADRs). This comprehensive review delves into the ADRs associated with both traditional benzodiazepines and newer benzodiazepine receptor agonists such as zopiclone, zolpidem, abecarnil, and bretazenil. Drawing on extensive pharmacological, clinical, and epidemiological research, we aim to elucidate the link between BZD use and adverse outcomes, highlighting both short-term effects such as over-sedation and paradoxical reactions, and long-term risks including memory impairment, depressive symptoms, tolerance, and physical dependence. Moreover, the rising trend of recreational BZD abuse, often in the context of polydrug use, presents additional health risks, particularly for individuals with a history of substance abuse or personality disorders. This review underscores the importance of careful prescribing, vigilant monitoring, and individualized risk assessment to mitigate the adverse effects of BZDs and their analogs in clinical practice.

Background It remains unclear if pediatric patients with acute or chronic lung diseases benefit from chest physiotherapy (CPT) during spontaneous breathing. The electrical impedance tomography (EIT) offers the opportunity to assess treatment effects of CPT on regional ventilation distributions. Methods We conducted a prospective feasibility study between 10/2023 to 05/2024. Pediatric patients with need for active or passive CPT were screened. EIT measurements were performed at (T1) immediately prior to CPT intervention, and (T2) within 30 minutes after CPT intervention. Results Overall, 25 patients were enrolled, with two patients enrolled twice at different admissions, resulting in 54 EIT-measurements. The mean horizontal center of ventilation (CoVx) and the mean vertical CoVy were equally distributed at T1 and T2, without any difference seen when subdividing for mode of CPT. The mean global inhomogeneity index (GI) decreased from 0.38 to 0.36 (∆GI: -6%, p=0.939) in the overall cohort, with a significant decrease between T1 and T2 in patients with active (∆GI: -10%, p=0.015), but not in patients with passive CPT (∆GI: +6%, p=0.199). In patients with a localized pulmonary finding in the radiologic assessment (n=10) we observed a markedly increase of the proportional ventilation distribution of the affected lung side after CPT (T1:44% vs. T2: 48%, p=0.057). Conclusion EIT seems feasible to monitor changes in regional ventilation distribution after CPT in pediatric patients. Patients with localized pulmonary radiological findings and patients after active CPT seems to benefit most from CPT, whereas there is a subset of individuals with no response to CPT.

Lung cancer is prevalent worldwide. Antiangiogenic therapy is an important treatment strategy for patients with advanced or recurrent non-small cell lung cancer (NSCLC). Currently, there is still a lack of reliable markers for efficacy testing and evaluation of antiangiogenic efficacy. We used label-free quantitative proteomics technology to read a total of 516 proteins in the plasma proteome of advanced NSCLC and the control group. Compared with the control group, 83 proteins were significantly differentially expressed in NSCLC. Bioinformatics analysis methods were used to analyze the biological significance of differentially expressed proteins. In conjunction with clinical data, the efficacy of antiangiogenic inhibitors was analyzed. There were 20 protein expression differences in the effective antiangiogenic treatment group compared with the control group. It was found that SERPINF1 was downregulated in newly diagnosed NSCLC compared with the control group, but upregulated in the effective antiangiogenic treatment group, and the NSCLC single cell atlas showed that SERPINF1 was highly expressed in fibroblasts. The study revealed the serum proteomic profile of Advanced NSCLC and explored efficacy markers of antiangiogenic drugs.

AbstractThe training of clinical neurology trainees is an extensive process that requires mastery of core medical sciences alongside the integration of evidence-based clinical practice (EBCP). Despite the growing emphasis on EBCP across various medical specialties, education in neurology and neurosurgery has not kept pace with these advancements. This review explores the implementation of innovative training methods, such as the flipped classroom model and AI-based tools, to enhance the teaching and application of evidence-based neurology (EBN). The proposed EBN curriculum aims to develop trainees’ critical appraisal skills and deepen their understanding of clinical evidence. By concentrating on contemporary clinical questions and utilizing state-of-the-art technologies, the curriculum seeks to improve diagnostic accuracy and treatment outcomes in neurology. Structured topic selection, preparation, and tutorial sessions are designed to enhance practical knowledge and critical evaluation skills. The integration of AI tools further supports trainees in conducting comprehensive literature searches and critically appraising studies. This dynamic approach ensures that neurology training remains responsive to the evolving needs of the field, ultimately leading to the delivery of superior patient care based on the best available evidence. The aim of this review is to evaluate the effectiveness of these novel training methods in improving outcome-based evidence and the practice of evidence-based neurology among clinical neurology trainees.Keywords: evidence-based medicine; evidence-based neurology; outcome-based education; neurology education; neurology trainingGraphical Abstract

Pentalogy of Cantrell: An Extremely Rare Case Report.

A document by Ameer Awashra. Click on the document to view its contents.

A document by Ashwini Gurung. Click on the document to view its contents.

Objective: This study aimed to establish a delivery protocol for safely undergoing trial of labour after two Caesarean Sections and analysed predictors for a successful vaginal delivery. Design: Retrospective cohort study Setting: Single centre tertiary community hospital Population: Between the study period 385 women planned a delivery after two consecutive Caesarean Sections. According to defined prepartum criteria of the delivery protocol, 358 patients (93.0%) were scheduled as primary third Caesarean Section, while 27 (7.0%) for attempting vaginal delivery. Methods: Those women, who desired TOLA2C, were screened by a senior obstetrician and had to consent to a delivery protocol consisting of five pre- and eight peripartal criteria. Maternal demographic data, indications for previous CS and feto-maternal outcome parameters were compared between the successful TOLA2C group and the secondary Third-Caesarean section group. Main Outcome Measures: The primary outcome was the success rate of women undergoing TOLA2C who fulfilled the predefined protocol. Additionally maternal demographic data, indications for previous CS and feto-maternal outcome parameters were compared between the successful TOLA2C group and the abandoned TOLA2C group. Results: In the study period, n =385 women planned a delivery after two consecutive CS. Following the protocol, n= 358 patients (93.0%) were scheduled as primary Re-Re-CS, while n=27 (7.0%) attempted vaginal delivery. In this TOLA2C group, n=17 women (63.0%) successfully delivered vaginally. In contrast, n=10 failed vaginal attempts (37.0%) resulted in nine secondary Re-Re-CS and one in a secondary Re-Re Emergency CS. Women with prior vaginal delivery had a significantly higher chance of a successful TOLA2C (p=0.04). In comparison, women with a previous CS due to the indication of arrested labor had a significantly higher risk for a secondary Re-Re-CS (p=0.02). No fetal or maternal death occurred, and no major complications were observed. Conclusions: Under the specified conditions, TOLA2C is safe for mother and fetus, and successful vaginal delivery is feasible.

Chromosomes, which contain genetic information crucial for the human body, exhibit a thread-like structure within the cell nucleus. Analyzing chromosomes, a process known as karyotyping, is essential for identifying abnormalities within them. Despite the development of various methods for detecting abnormalities, existing approaches often suffer from inefficiencies such as being time-consuming and ineffective in feature extraction. To address these challenges, a novel Visual Geometric Transformer-based Mantis search (VGT-MS) algorithm is proposed that detect abnormal conditions of chromosomes. However, these images often contain extraneous elements that need to be removed. Subsequently, the VGG-16 model is employed to extract features and Vision Transformer is utilized to identify chromosome abnormalities. The parameters are tuned and optimized by Mantis Search Algorithm that validated the performance of the model. The effectiveness of the developed model is evaluated using metrics such as F1-score, accuracy, recall, ROC, and precision. The results reviewed that the proposed achieved superior performance boosting an accuracy, precision, recall and F1-score is 98.0%, 97.2%, 96.2%, 97.6%, all while maintaining lower execution time. Overall, the VGT-MS algorithm presents a robust solution for chromosome abnormality detection, effectively overcoming the limitations of previous approaches and providing enhanced performance metrics.