The underutilization of electrodiagnostic and electrotherapeutic tools has far-reaching consequences, impacting diagnostic accuracy, treatment outcomes, healthcare costs, and patient satisfaction. These issues are often rooted in inadequate training, insufficient physician awareness, and challenges in integrating complex technologies. Underuse compromises diagnostic precision, delays treatment, and limits the potential benefits of advanced therapies, leading to suboptimal management of a wide range of conditions. Additionally, the financial burden of underutilized equipment manifests through reduced facility return on investment, operational inefficiencies, and a decline in healthcare services overall quality and sustainability. Addressing this issue requires a multifaceted approach, emphasizing improved training, physician education, and seamless integration of technologies across specialties. Increased utilization can enhance patient outcomes, streamline operations, and ensure the financial viability of healthcare facilities. The purpose of this review is to highlight implications of underutilization while providing a detailed overview of available electrodiagnostic and electrotherapeutic tools across medical specialties, emphasizing the need for enhanced awareness, training, and integration to optimize their use in clinical practice.

The reference evapotranspiration (ET 0) is a crucial indicator for characterizing the potential water consumption of an ecosystem, and the vapor pressure deficit (VPD) serves as a significant measure to assess atmospheric water deficiency. Both indicators are highly correlated with air temperature. However, the response time of ET 0 to VPD and temperature, as well as the influencing factors, remain unclear. In this study, we employed 21 years of meteorological data from 107 sites in Inner Mongolia, China to analyze the lag response time of ET 0 to VPD, extreme temperatures (Tmax and Tmin), and vegetation index (NDVI), along with their interactions. The results show that: (1) Between 2000 and 2020, ET 0, VPD, temperature, and NDVI all exhibited increasing trends; (2) The lagged response time of ET 0 to VPD was significantly longer than that to temperature (Tmean), with a particularly pronounced effect in high-altitude areas under low-temperature conditions; (3) The potential impact of VPD on ET 0 was greater than the direct effect of temperature, with ET 0 responding more to low temperatures than to high temperatures and VPD; (4) An increase in NDVI indirectly extended the lag days of ET 0 and VPD through extreme temperatures, while the lag days of ET 0 to extreme temperatures decreased; (5) The lag time of ET 0 to VPD and temperature was shorter in high-altitude regions, while the lag effect was more prominent in low-altitude areas in the eastern part of the study region. This study reveals the lagged response of ET 0 to VPD and temperature variations in arid and semi-arid regions, providing new insights into the lagged effects of environmental variables on water and heat fluxes in ecosystems under climate change.

Deep digital flexor tendinopathy is a significant cause of lameness and poor performance in equine athletes with substantial implications for their return to athletic performance. Magnetic resonance imaging (MRI) is increasingly integrated into the diagnostic workup of horses with foot pain and has revolutionized the diagnosis and management of these injuries. This review discusses the principles of MRI in the context of DDFT injury, comparing high-field and low-field systems, and highlighting the clinical relevance of technical parameters including field strength and sequence selection in achieving an accurate diagnosis and prognosis. It also evaluates the complementary role of computed tomography and ultrasonography in cases where MRI may not be feasible and discusses emerging imaging techniques, including PET-MRI and quantitative MRI. This paper underscores the importance of serial imaging to monitor lesion progression and guide rehabilitation, while identifying knowledge gaps and proposing future research directions. Ultimately, a multidisciplinary approach incorporating advanced imaging modalities and tailored rehabilitation is essential to improving clinical outcomes in horses with DDFT injuries.

The local active memristor with an Edge of Chaos Kernel represents a significant advancement in the simulation of neuromorphic dynamics. Initially, we designed and analyzed a memristor circuit that demonstrates local activity and stability within defined voltage and inductance parameters. By varying the input voltage and inductance, this memristor effectively emulates diverse neural activities, including inhibitory postsynaptic potentials and chaotic waveforms. Subsequently, by integrating the EOCK memristor into the Hopfield neural network (HNN) framework, we substituted the self-coupling weight and observed a rich spectrum of dynamic behaviors. Finally, we implemented hardware circuits to realize these generated dynamic phenomena. This research introduces a novel hardware approach to brain-like computing, providing both theoretical insights and empirical foundations for developing circuits and systems that replicate the complexity of human brain function. The integration of EOCK is anticipated to inspire innovative methodologies for simulating the varied neural activities inherent in human cognition.

Owing to agricultural expansion worldwide, agricultural crops can have major effects on the life history traits of wildlife. However, the functional role of crop consumption on the life history traits of long-lived mammals is seldom evaluated quantitatively. Body size is an important life history trait because it is directly related to fitness. In this study, we investigated the functional role of long-term crop consumption on body growth of sika deer (Cervus nippon). Crop consumption accelerated body growth of not only the consumer but also the next generation, and its effect differed by sex. In females and males, the degree of crop consumption produced maximum differences of about 2 and 1 years in the ages at which 98% asymptotic size was attained, respectively. However, this difference did not always occur in males. The degree of crop consumption by mothers generated a maximum difference of about 15% in the hind-foot length of their fetus. This study revealed that the degree of long-term crop consumption affects the body growth of deer at an individual level, even within the same population. The crop consumption had a positive effect on the consumer and the next generation. Further examination of the effects of accelerated body growth on population growth rates will elucidate more accurately the effects of crop consumption on population dynamics in the landscape, including agricultural crop lands.

A document by Parker Emmerson. Click on the document to view its contents.

A document by Parker Emmerson. Click on the document to view its contents.

A document by Parker Emmerson. Click on the document to view its contents.

Insect pollinators are essential for the health and resilience of terrestrial ecosystems, delivering key ecosystem services in the face of anthropogenic disturbance. Urbanisation may be a key threat to pollinator diversity and abundance. However, the scale of the threat remains unknown due to an overwhelming research emphasis on bees and a lack of comparative studies of hyper-diverse taxa such as nocturnal moths. Consequently, the question of which pollinator groups will be more affected by urbanisation remains unknown, and the habitat features that support key taxa remain controversial. We conducted the first large-scale assessment of the negative effects of increasing urbanisation on the diversity of bee, hoverfly and nocturnal moths across three cities. We report up to a 43% reduction in species richness along replicated urbanisation gradients, suggesting that a wide range of pollinators are limited due to abiotic stresses and limited resources in urban environments. Landscape mapping indicated that these effects are driven by the reduction of tree cover and semi-natural habitat; however, the specific landscape drivers were taxon-specific, suggesting that urban insect conservation depends on the preservation or expansion of habitat features specific to different threatened taxa. In the first empirical comparison of three major pollinator taxa, we show that, relative to bees, moths and hoverflies are particularly sensitive to urbanisation, and we highlight the importance of including these frequently overlooked pollinator groups when assessing the biodiversity impacts of environmental change.

Aphids are observed on various plant species, with most aphids feeding downward on stems. In this study, I studied the variations in feeding postures of aphids and their mechanisms. My field observations revealed that the majority of individuals from most species fed facing downward, or more precisely, towards the roots. Exceptions included Indomegoura indica on the scapes of Hemerocallis spp., which were aligned with their head facing the sky. Next, I investigated how plant orientation affects three aphid species, Macrosiphoniella yomogifoliae, Megoura crassicauda, and I. indica with different body alignments on upright immature stems. On the stems of the inverted plants, the number of Ma. yomogifoliae and Me. crassicauda in the upward position (head facing the root of the plant) was significantly greater than that in the downward position (head facing the shoot apex of the plant). If their posture is affected by gravity or by certain advantages of the headstand posture, Ma. yomogifoliae and Me. crassicauda are expected to align in a consistent direction, regardless of the orientation of the plant. This suggests that plant cues influence their posture. In contrast, the majority of I. indica were aligned with the head facing the sky on the scape, regardless of Hemerocallis’s direction. This result indicates that the feeding posture of I. indica is affected by gravity and/or aphid’s intrinsic factors. Therefore, this study provides a new perspective on the factors influencing aphid feeding posture preferences.

IntroductionTuberculosis is a chronic granulomatous infection caused by Mycobacterium tuberculosis (MTB). It is a common disease in low- and middle-income countries of the world. Tuberculosis (TB) primarily affects the lungs but can also affect other organs (extra-pulmonary) such as the lymph nodes, genitourinary system, bones and joints, gastrointestinal system, central nervous system, and spine.Breast tuberculosis (BTB) was first described by Sir Astley Cooper in 1829 [1, 2]. It’s characterized by granulomatous inflammation of the breast parenchyma, which may present with cutaneous manifestations including skin changes and ulceration. The breast is a rare site of manifestation of extra-pulmonary tuberculosis, especially as a primary manifestation, even in tuberculosis-endemic countries [3-6]. It generally affects women of reproductive age, commonly between 21 and 30 years old [3, 4, 6, 8, 10].The incidence of BTB is estimated to account for 0.1% of breast diseases in developed countries but reaches 3% to 4.5% in endemic countries [3, 6, 7, 9, 10]. The factors thought to be responsible for the higher incidence of the disease in the developing world include HIV/AIDS, an increase in the prevalence of multi-drug-resistant tuberculosis, and the increasing age of lactating women [5, 11].The clinical presentation of BTB is often insidious and non-specific, mimicking the signs of breast carcinoma. It can present as a breast abscess, a unilateral painless mass, or a sinus and it may sometimes mimic breast cancer [10]. Clinically and radiologically, BTB can resemble a pyogenic breast abscess, fibroadenoma, or carcinoma. The most concerning differential diagnosis is carcinoma of the breast because of the inherent consequences of the treatment, including chemotherapy. The role of microbiology tests in the diagnosis of BTB is, therefore, paramount. Histologic confirmation requires demonstration of acid and alcohol fast bacilli (AAFB), GeneXpert, culture, or polymerase chain reaction (PCR) as means of identifying the causative mycobacterial organism.This report illustrates a case of GeneXpert-confirmed BTB encountered in a tertiary hospital in Ethiopia and highlights the salient features that may aid in diagnosis.

not-yet-known not-yet-known not-yet-known unknown Aim: Drug interactions are a significant healthcare concern frequently encountered in intensive care units. Our study aims to acquire more up-to-date data and raise awareness of drug interactions. Methods: A retrospective analysis was performed on the data of 163 patients admitted to the intensive care unit in 2019. The patients’ medication lists were evaluated on a daily basis, and drug information was analyzed using three different online databases: Micromedex, Lexicomp, and Drugs.com. Results: The length of hospital stay ranged from 1 to 50 days, and a total of 1,834 medication orders were analyzed. The most common admission diagnoses were pneumonia, acute renal failure, and gastrointestinal bleeding. Comorbidities were present in 81.6% of patients. The number of interactions increased significantly with increasing comorbidities and number of drugs. This association was particularly evident for cardiovascular diseases. The number of interactions was higher in men. Interactions were identified in 82.9% of orders in Micromedex, 92.5% in Lexicomp, and 95.5% in Drugs.com. The most common contraindicated interaction was between linezolid and tramadol, while the most common major interaction was between aspirin and enoxaparin. Linezolid, fluconazole, and metoclopramide were the most common drugs contributing to contraindicated interactions, while enoxaparin, aspirin, and clopidogrel were the main contributors to major interactions. Albuterol, norepinephrine, and pantoprazole were associated with more moderate interactions. Conclusion: Assessment of drug interactions can lead to improved patient outcomes and avoidance of unnecessary economic burden. Clinicians should use several sources when performing such assessments. There are significant differences between databases.

The complexity and scale of contemporary language models require innovative methodologies to enhance their adaptability and efficiency. Introducing Synthetic Knowledge Cascading (SKC), a novel mechanism enabling autonomous, iterative self-refinement within large language models (LLMs), this study explores its impact on data representation quality, model refinement efficiency, and performance across various downstream tasks. Experimental evaluations demonstrate that SKC significantly improves semantic coherence, accelerates convergence rates during training, and enhances robustness to adversarial inputs. These findings suggest that SKC offers a promising avenue for developing more adaptable and intelligent language models capable of continuous self-improvement.

The detection of distant small ship targets in the marine environment is a critical and challenging issue that urgently needs to be addressed in the realization of accurate marine information control in the complex environment. It is of great significance for monitoring Marine environment and safeguarding maritime sovereignty In the process of acquiring target information on ships at sea, the images captured typically contain information of moving targets within dynamic scenes. Traditional, singular methods are inadequate for obtaining complete information on these moving targets. Based on this, the article proposes an integrated method combining motion target detection algorithms, edge detection operators, and deep learning-based target detection algorithms. This method constructs an improved motion target detection algorithm to achieve comprehensive information acquisition and detection of the position, size, and type of moving ship targets in complex marine environments. Experimental simulation has validated the network performance and practical value. The network has been deployed on an Nvidia Jetson TX2 development board for real-world testing, confirming its performance in detecting dynamic ship targets in actual marine environments, and providing a viable technical approach and theoretical support for enhancing the refined target selection capability.

The prediction of bearing faults in electric motors is crucial for preventive maintenance and enhancing system reliability. This study evaluates three Machine Learning algorithms—K-Nearest Neighbors ( KNN), Support Vector Machine ( SVM), and Decision Tree—along with ensemble methods such as Bagging, Boosting, and Stacking, focusing on their effectiveness in predicting faults. The models were tested on the Paderborn dataset, which includes vibration and electrical current signals from motors. Preprocessing involved filtering, normalization, and feature extraction through Wavelet transforms and statistical methods. The Wavelet was choose due to its ability to analyze signals at different scales and resolutions, which is ideal for identifying temporal and frequency characteristics simultaneously. These processed signals were then used to train and test the models. The comparative analysis of the algorithms reveals that the Stacking technique achieves the best overall prediction performance, using the vibration signal in the Time domain and also in the frequency domain with the Wavelet transform with the filter Symlet 8). This analysis underscores the importance of selecting the most appropriate algorithm depending on the specific problem characteristics and system requirements. Overall, the study contributes to the field of bearing fault detection, offering insights into the comparative effectiveness of vibration versus electrical current signals for predictive maintenance.

Successful management of a pericardial cyst in a 22-year-old

A software fault refers to a mistake or imperfection in the coding of a program that results in malfunctions or inaccurate output. It usually results from development errors and might cause problems with the system or other problems. Software fault localization requires identifying the precise location of defects within a program’s code to facilitate efficient debugging. It involves techniques such as automated testing, debugging tools, and fault isolation methods. By using algorithms to evaluate code, find trends, and rank potentially problematic locations, machine learning helps localise software faults more quickly and more accurately. This paper employs the Siemens program suite from SIR to evaluate our proposed model effectively. Benchmark programs are executed with varied test cases, resulting in pass or fail outcomes. Machine learning models are trained using the coverage matrix, generating suspiciousness scores for statements to expedite fault identification and minimize debugging time. We evaluated the accuracy of our proposed model using the EXAM metric. Based on the results, the CNN model demonstrates superior performance, surpassing the RNN by 3% and the ANN by 6%. Due to its enhanced performance, the CNN model is recommended for reducing fault detection time.

not-yet-known not-yet-known not-yet-known unknown Avian insectivores have experienced population declines worldwide, with intensification of agricultural practices as a major contributing factor. To understand how species react to such human-driven environmental changes, it is necessary to obtain detailed information on their survival, reproduction and dispersal. This is particularly important for declining species and populations, where immigration contributed by dispersers from neighboring populations can influence local population growth. We used multi-state Capture-Mark-Recapture (CMR) models and 14 years of data (2004-2019) on individually marked Tree Swallows (Tachycineta bicolor) breeding on farmlands in southern Québec, Canada, to quantify the effects of agricultural intensity, local weather, and interspecific competition on the vital rates and population growth. Yearly population growth rates were highly dependent on both immigration and adult return rates. Nest site competition by House sparrows (Passer domesticus), mostly found within intensively cultivated landscapes, had a strong negative effect on reproductive success and adult return rates. Nevertheless, 43% of the variance in lambda was attributed to unexplained differences between farms, suggesting that microhabitat or other unmeasured environmental variables also drive population growth rate. Our results clearly show that the studied population would not persist without immigration, suggesting that intensively cultivated farmlands may act as sinks. Our sampling design may partly explain this result as nest boxes were installed in low quality habitats. Understanding the ecology and demography of declining aerial insectivore species therefore requires studying multiple populations of the same species in a wide range of habitats and geographic locations, as well as several species with contrasting life histories.

The present study examines the impact of fixed versus moving graphite crucibles on the germanium crystal growth process in an inductive CZ furnace. In particular, the aim is to perform a computational study of the impacts on the temperature and flow characteristics within the system, the form of the interface between crystal and melt, and stress and dislocation density in the ingot. Results show that as the crucible moves upward during the crystal formation phase, while a portion of the molten material solidifies where its open surface contacts the crucible wall, the solidified portion at the bottem of the crucible is effectively eliminated. Additionally, the upward movement of the crucible results in a more convex crystal-melt interface with greater penetration into the melt than when a stationary crucible is used. Furthermore, the crucible's relative motion alters the stress distribution and dislocation density.

Background Yellow fever (YF) is a zoonotic arboviral disease that is mainly transmitted by Aedes aegypti and Ae. albopictus mosquitoes. It mainly infect both, human and non-human primates including the endangered mountain gorillas. Despite that Yellow fever is a vaccine preventable disease, according to the World Health Organization, it is still endemic in 47 countries; 72% of those countries are in Africa and 28% in Central and South America. Methodology We deployed several transdisciplinary research methods for the implementation of this risk assessment and situation analysis as well as developing national preparedness, prevention, and response strategy for YF in Rwanda. These methods included epidemiological and entomological surveys, health system analysis, and stakeholders and expert consultations. This was supported with in-depth desk and literature review analysis. Results We have identified high risk of Yellow fever emergence and outbreaks in Rwanda. The main underpinning sources of this risk are including the confirmed presence of the main vector of the disease; Aedes aegypti. More importantly, the lack of vector surveillance for Aedes mosquitoes, surveillance for the disease among human or animals at risk in the country despite the ongoing transmission in the region including countries with open-borders and free movements with Rwanda. Additional important sources of risk include limited vaccination coverage and requirement for travelers to and from endemic countries. Accordingly, we have developed a preparedness, prevention, and response (PPR) framework for Yellow fever in Rwanda. Conclusion In addition to strengthen the implementation of the developed preparedness, prevention, and control measures, the One Health authority should invest in the establishment and operation of integrated surveillance and response system that comprehensively monitors the indicators of humans, animals, and environmental health. Additional support should be given to operational research to generate evidence that informs policymaking, and guide the strategic planning and implementation of cost-effective interventions.

In this study examining the effectiveness of Metacognitive Therapy in Generalized Anxiety Disorder, a nine-session therapy process was conducted with a client, and the Worry Beliefs Scale and Beck Anxiety Scale were used as measurement tools. According to the findings, Metacognitive Therapy was found to be effective in the treatment of Generalized Anxiety Disorder. The study is a case report and there is a need for further studies to be conducted with more than one client and to test the effectiveness of Metacognitive Therapy comparatively.

Background and Purpose: EGFR targeted therapy has pioneered a new era of NSCLC treatment. However, drug resistance is the major challenge of such therapy. Osimertinib is the latest generation of EGFR inhibitor and is clinically used for the treatment of NSCLC patients harboring EGFRT790M gatekeeper mutations. Unfortunately, the patients treated with Osimertinib also developes resistance and no follow-up drugs are currently available in clinic. EGFRC797S triple mutations have been identified as the pivotal causes contributing to Osimertinib resistance. This study aims to identify novel EGFR inhibitors that can target EGFRC797S triple mutations and conquer Osimertinib resistance through drug repurposing. Experimental Approach: Osimertinib-resistant NSCLC cell models were constructed by lentiviral transfection in PC-9 cell line and used for drug repurposing screen. The hit compound was further confirmed by kinase inhibition assay, immunoblot, and molecular docking. Then cell cycle, proliferation, and apoptosis were detected after hit treatment. The in vivo anti-NSCLC effect of the hit was also evaluated in the resistant xenografts. Key Results: We successfully established Osimertinib-resistant NSCLC cell lines harboring EGFRdel19/T790M/C797S or EGFRL858R/T790M/C797S mutation and identified the LRRK2 inhibitor CZC54252 to be an effective inhibitor against EGFRC797S triple mutations. CZC54252 could potently restrain the growth of NSCLC cells resistant to Osimertinib both in vitro and in vivo by directly targeting EGFR resistant mutations instead of its original targets. Conclusion and Implications: Overall, the repurposing of CZC54252 in inhibiting EGFRC797S triple mutations and conquering Osimertinib resistance lays a chemical foundation for the research and development of novel next-generation EGFR inhibitors.

Article category: Case ReportManagement of impacted premolar with root dilaceration caused by radicular cyst in deciduous molar: A case reportShuhao Xu1, Xiaolong Li2, Yu Zhang1, Wei Li1*1Department of Stomatology, Deyang People’s Hospital, Deyang, China2Department of Respiratory and Critical Care Medicine, Deyang People’s Hospital, Deyang, China*Correspondence: Wei Li, Department of Stomatology, Deyang People’s Hospital, 173 North Taishan Road, Deyang, 618000, China (E-mail: manuang@qq.com)

Case reportTITLE : Lactic acidosis type B: un uncommon presentation in solid tumors and rare complication of sarcoma