In machine learning, feature selection is of utmost importance for augmenting the predictive capabilities of ensemble models. This paper presents an innovative hybrid framework for selecting features in ensemble models, which combines Rough Set Theory (RST) with Recursive Feature Elimination (RFE), complemented by Association Rule Mining, to enhance interpretability. The suggested method considerably improves ensemble models’ prognostic accuracy and comprehensibility, particularly Random Forests and Gradient Boosting Machines. The framework starts with the RFE process, meticulously eliminating less influential features, and then applies RST to refine the feature set further by eliminating redundancies. This two-phase approach results in a feature set that is optimally reduced yet highly influential. By implementing this hybrid method on ensemble models, significant improvements in predictive accuracy are demonstrated across three diverse datasets: cancer, Pima Indians Diabetes, and a weather dataset from Underground. The accomplished accuracies for these datasets were 0.9663, 0.8793, and 0.8427, respectively, highlighting the proposed approach’s effectiveness. This article also proposes the incorporation of association rule mining to analyze the outcomes of the models. This technique improves the understandability of the models, offering more profound insights into the connections and patterns, thus tackling the difficulty of interpretability in intricate ensemble models. Our empirical analysis confirms the effectiveness of the proposed hybrid feature selection model, representing a significant advancement in the field. The integration of RFE and RST optimizes the feature selection process and bridges the gap in interpretability, offering robust solutions for applications where accuracy and understanding of model decisions are crucial.

This tutorial focuses on standardised mean differences (SMD) as effect measures in meta-analyses. We will explain what they are, when they should be used, how to correctly compute and interpret them, and some of the most common error made within evidence synthesis

Water availability regulates plant community dynamics but the drought response of seedlings remains poorly known despite their vulnerability, especially for the Asian tropics. In particular, discerning how functional traits of seedlings mediate drought response can aid generalizable predictions of tree responses to global environmental change. We assessed interspecific variation in drought response explained by above- and below-ground seedling traits. We conducted a dry-down experiment in the greenhouse using 16 tree species from the humid forests of Western Ghats in southern India, chosen to represent differences in seasonality affiliations–sites of high and low seasonal drought. We compared seedling survival, growth, and photosynthetic performance under drought and well-watered conditions, and assessed the extent to which species responses were explained by seasonality affiliation and 12 traits of root, stem and leaf. We found that the species from seasonally dry forest reduced photosynthetic rate in drought compared to well-watered conditions, but seasonality affiliation did not explain differences in growth and survival. Performance changes in drought vs well-watered conditions were best explained by anatomical traits of xylem, veins and stomata. Species with larger xylem reduced their growth and photosynthesis to tolerate desiccation. In drought, species with smaller stomata showed reduced survival even though photosynthetic activity decreased by a larger extent with larger stomata. Our study shows that anatomical traits related to xylem and stomata, directly related to water transport and gas-exchange, played a more prominent role than commonly used soft traits (e.g., specific leaf area, wood density) in explaining species response to drought, and may offer a better proxy for physiological traits related to drought tolerance of seedlings.

Time to standardise terminology in the ultrasound study of the pelvic floor of pregnant women Joelene Murdoch-Ward, Irmina Nahon, Sally De-Vitry Smith, Eliza Bernardi, Tamara WoodsUniversity of Canberra, Faculty of Health, Canberra ACT, Australia. The Physiotherapy Clinic, Sydney NSW, AustraliaUniversity of Canberra, Faculty of Health, Canberra ACT, Australia 2610University of Canberra, Faculty of Health, Canberra ACT, Australia 2610The Physiotherapy Clinic, Sydney NSW, AustraliaThe Physiotherapy Clinic, Sydney NSW, Australia

Attached algae are important primary producers in river ecosystems that are foraged by benthic macroinvertebrates and grazing fishes. The ayu Plecoglossus altivelis, which is an algae-feeding fish that feeds on attached algae. Fine particulate organic matter (FPOM) is generated when P. altivelis use their comb-like teeth to graze algae off the surface of stones, and dislodge them into streams. Therefore, in the present study, we investigated how P. altivelis feeding on algae contributes to the production of algae-derived FPOM. We subsequently evaluated the produced FPOM to determine whether it affected the origin of the macroinvertebrate food supply. To investigate P. altivelis density, the biomass of primary producers, and the food use fraction of consumers, field surveys were conducted in the Kamo-gawa River, Japan, in the summer season from 2018 to 2020. Carbon and nitrogen stable isotope ratios of macroinvertebrates and food sources were measured to estimate the composition of FPOM and the contribution of different food sources to primary consumers. Our results showed that algal biomass decreased at sites with a high density of P. altivelis, where the proportion of algae-derived FPOM increased. The algal contribution to macroinvertebrates increased at sites with high algae-derived FPOM. Furthermore, structural equation modelling revealed that the feeding behaviour of P. altivelis contributed to macroinvertebrate food utilisation via the production of algae-derived FPOM. These results suggest that P. altivelis is a keystone species that not only produces algae-derived FPOM but also improves the food supply to macroinvertebrates and promotes river ecosystem dynamics.

ACNO Hydrogel: A Breakthrough in Diabetic Wound Care Through miR-21 Pathway Activation and DNA DemethylationJitao Chena,b, Junyu Denga,b, Huan Zhua,b,Yu’e Tangc, Jiufeng Zhaod, Penghui Yea,b,Wenjie Hea,b,Xingqian Wua,b,Xingrui Mua,b,Rifang Gue, Ming Tangf,

While the evidence supports a role for the soil microbiome to modulate the environmental tolerance of various plant species, its role in the invasion success remains seldom assessed. Here we show results from two complementary experiments aimed at understanding the role of the soil microbiome on the performance of T. officinale (dandelion) plants. Since the relative importance of soil microbiome on plant fitness can differ between native versus introduced origins, we conducted a full cross-transplant experiment to compare the plant performance from different origins (native/introduced) in their original or exotic soils, along with manipulated soil microbiome. In addition, since the relevance of soil microbiome for plant fitness can depend on the level of environmental stress, we compared the plant performance under different soil microbiome treatments in an introduced latitudinal gradient. We found positive effects of soil microbiome on performance traits for T. officinale plants from most of the evaluated populations, being particularly relevant for plants in the introduced range and under stressful conditions.

The variation of species composition among communities, commonly known as beta diversity, is at the heart of ecology because of its role in explaining community assembly. This study presents a new approach that integrates functional and phylogenetic characteristics into the traditional beta diversity framework. Drawing on the observations from a large-scale forest inventory network, our results show that functional- and phylogenetic-based metrics offer distinct insights beyond those provided by species-based metrics. Species-based metrics help to identify species with specific distribution and locations with unique composition. Functional and phylogenetic-based metrics aid in identifying species and locations with distinctive ecological and evolutionary attributes. Furthermore, upon integrating functional and phylogenetic information, the relative contribution of deterministic processes in driving biodiversity patterns become more apparent. Our expanded framework provides a new opportunity to characterize the ecological uniqueness of species and locations, helping to reveal more detailed insights into assembly processes and guide biodiversity conservation.

Objective: Pregnancy with complicated type B aortic dissection is a rare but devastating scenario. And there are no definitive guidelines for management and therapy. We report our exploration and experiences of managing five pregnant with complicated TBAD in the second or third trimesters, aiming to propose an appropriate management strategy. Design: Retrospective study. Setting: Zhongnan Hospital of Wuhan University. Population: Pregnant women with TBAD Methods: The clinical data of 5 pregnant women with TBAD who were admitted to the Zhongnan Hospital of Wuhan University from January 2022 to June 2023 were collected. The clinical features, diagnostic procedures, treatment strategies and corresponding maternal and infant outcomes were retrospectively analyzed. Main Outcome Measures: The survival of mother and fetus. Result: All five pregnant women with TBAD were diagnosed with complicated TBAD. The average age of the patients was (34.8±8.13) years, and the range of gestational weeks at admission was 27 weeks plus 3 days to 36 weeks plus 6 days. The first patient intending to receive a cesarean section and subsequent TEVAR died of rupture of aortic dissection during cesarean section. Her neonate was successfully rescued. The remaining four patients who underwent TEVAR first survived. Three underwent single-stage aortic repair and delivery, and one patient underwent cesarean section 27 days after TEVAR. Three preterm live births of these four patients were recorded. During late follow-up, no maternal and fetal deaths occurred. Neither device-related nor systemic complications post TEVAR were observed in the mother. Routine physical examinations of four live births showed no abnormalities. Conclusion: When a pregnant woman in the second or third trimester has thoracic back pain and highly suspected aortic dissection, CTA should be performed to avoid missed diagnosis, misdiagnosis and diagnostic delay. Once diagnosed, maternal survival should be prioritized over fetal concerns. TEVAR is safe and feasible for such patients. For complicated TBAD in the third trimester single-stage delivery and TEVAR are preferred, and TEVAR followed by cesarean section performed in one operative session is the treatment of choice.

In this paper, DC compact model of a resistive-switching random-access memory (ReRAM) has been characterized and developed. ReRAM is one of the types of nonvolatile memory that is a promising candidate for use in the future. It is currently being actively studied for use in fields such as neuromorphic and AI computing due to its advantages such as fast switching speed and low operating voltage. Since the use of ReRAM in this field is used as a large-scale array simulation, a compact model is required to confirm the operation characteristics. The compact model was calibrated based on the measured values of two actually fabricated ReRAM devices using HfOx and SiNx materials as switching layers. In addition, this compact model was written using Verilog-A so that it can be directly applied to SPICE simulation. We have seen that it is possible to have a compact model with high accuracy for with different switching layers ReRAM devices when adjusting the parameters in current density equations and fitting parameters.

IntroductionCoccidioidomycosis, known as Valley Fever, is the disease caused by the inhalation of arthroconidia from the soil-dwelling dimorphic fungi,Coccidioides immitis and Coccidioides posadasii [1]. In the United States, coccidioidomycosis is endemic to the southwestern part of the country, with most cases located in the San Joaquin Valley of California and Southern Arizona. The incidence of coccidioidomycosis is approximately 10,000 cases reported annually [1,2]. Coccidioidomycosis may affect any demographic, but primarily affects those aged 40-60 years old and has a slight male predominance. Clinical manifestations range from asymptomatic to disseminated infection depending on the patient’s immune status.Cutaneous manifestations in coccidioidomycosis can be classified as reactive or organism-containing lesions in secondary or primary cutaneous infection [3]. Sweet syndrome, or acute febrile neutrophilic dermatosis, is an inflammatory, non-infectious skin reaction rarely observed as one of the reactive skin manifestations of coccidioidomycosis. Patients with Sweet syndrome clinically present with fever, leukocytosis with neutrophilia, and painful erythematous papules, plaques, pustules, and nodules commonly appearing on the upper limbs, trunk, head, and neck [4]. Here, we present a case of coccidioidomycosis associated with Sweet’s syndrome.

Light exposure has been proven to significantly impact human health, and as a result, researchers are increasingly exploring its potential benefits and drawbacks. With the advancements in understanding light and the manufacturing of light sources, modern health lighting has become widely utilized in daily life and plays a critical role in the prevention and treatment of various illnesses. The use of light in healthcare is a global trend, and many countries are actively promoting the development and application of relevant scientific research and medical technology. This field has gained worldwide attention and support from scientists and doctors alike. In this review, we examine the application of lighting in human health and recent breakthroughs in light exposure related to pathology, therapeutic strategies, molecular changes, and more. Finally, we also discuss potential future developments and areas of application.

Objective(s): There are high rates of trauma in people who experience psychosis and a focus on the negative impact. The current study explores people’s perceptions of factors that facilitate positive adjustment and Post Traumatic Growth (PTG) following trauma, which is important for developing interventions to support resilience and well-being. Methods: Semi-structured interviews were completed by eleven people with experiences of both trauma and psychosis. Transcripts were subject to thematic analysis. Results: Participants welcomed the idea of growth and stressed the importance of hearing growth stories from other people with similar experiences and practitioners. However, growth was considered a sensitive topic that clinicians should introduce tentatively to not undermine the potential suffering caused by trauma. Participants effectively used various strategies to deal with their traumas, including some typically considered maladaptive by clinicians (e.g., avoidance and self-harm). Conclusion: When working with trauma in the context of psychosis, mental health professionals should formulate behaviours in terms of whether or not they are functional to a specific moment and environment, rather than routinely consider methods of coping as adaptive or maladaptive. Our findings also highlight the importance of assessing and supporting recovery from trauma rather than just from psychotic symptoms and suggest that clinicians should offer interventions for fostering PTG in psychosis, such as supporting access to a diverse range of narratives about adapting to life beyond trauma.

In this paper, we introduce an innovative temporal consistency enhancement approach, which enables image-based models on video data by leveraging a deep-learning-based Kalman Filter. More specifically, we propose a novel Bi-direction Kalman filter strategy, utilizing forward and backward processing to capitalize on higher-quality pose estimations near the camera, enhancing the robustness and precision of vehicle tracking across varying distances and conditions. Then, rather than using the conventional mathematical motion model, we propose a learnable motion model, dubbed Future State Predictor, to represent the complex, non-linear motion patterns observed in vehicles. The experimental results demonstrate that our approach enhances pose accuracy and temporal consistency, which allows us to handle the challenging occluded/distant vehicles.

INTRODUCTIONPleural effusion is an abnormal collection of fluid within pleural space usually resulting from excess fluid production and or decreased lymphatic absorption. Pleural effusion is rare during neonatal period with the estimated prevalence of 0.06%1. Neonatal pleural effusion may be due to antenatal congenital causes or postnatal acquired causes. Antenatal pleural effusion may be due to hydrops fetalis, congenital chylothorax, congenital heart disease (CHD), chromosomal anomalies, pulmonary anomalies or infection like congenital herpes simplex viral (HSV) and Paro virus infection. Postnatal acquired causes include extravasation of peripherally inserted central catheters, parapneumonic effusion or traumatic chylothorax.As neonatal pleural effusion can cause significant respiratory distress, vigilant delivery room management is required. Identifying the underlying cause is important as it leads to specific therapeutic measures. Diagnostic chests tap for pleural fluid analysis is important for diagnosis and its consequent management.2Similarly, echocardiography, karyotyping and other investigations are also indicated for identifying subsequent etiology.Here, we report a case of neonatal pleural effusion; which on evaluation; pulmonary sequestration-extra lobar type was found as the cause of effusion. Extra lobar pulmonary sequestration associated with pulmonary effusion is a very rare entity.3 The purpose of this case report is to familiarize clinician regarding lung sequestration as the cause of neonatal pleural effusion and prevent subsequent morbidity and mortality.

Ternary transition metal sulfides are extensively considered as supercapacitor electrode materials due to their remarkable electrochemical properties. However, inferior electrical conductivity and structural stability severely limit their applications. Here, we address these limitations by introducing N-doped carbon dots (N-CDs) into Ni-Co-Mn-S nanoflowers via a two-step hydrothermal process followed by electrodeposition. Ni-Co-Mn-S nanoflowers feature a skeleton structure supporting rich ion transfer paths and abundant active sites, while electrodeposited N-CDs increase the electrical conductivity and enhance the cycling performance. The resulting Ni-Co-Mn-S@N-CDs material demonstrates a remarkable specific capacity of 2267 F g–1 at 1 A g–1 and maintains 96.2% capacity after 10000 cycles at 10 A g–1. Moreover, this electrode material allows the development of hybrid supercapacitors with an impressive energy density of 61.6 Wh kg–1 at 800 W kg–1 and a superior capacitance retention of 89.0% after 20,000 charge/discharge cycles at 5 A g–1, alongside an excellent flexibility under various deformations. These findings represent a significant advancement in hybrid solid-state supercapacitors with promising implications for flexible energy storage technologies.

Dr Gebeyehu Tessema Azibte -Addis Ababa University, college of medicine and health sciences, department of internal medicineEmail -gebe10tessema@gmail.comDr Zekarias Seifu Ayalew –Addis Ababa University, college of medicine and health sciences, department of internal medicineEmail -zekariasseifu123@gmail.comDr Getnet Yigzaw Mossie- Addis Ababa University, college of medicine and health sciences, department of internal medicineEmail - yig2008gondar@gmail.com

Sydenham’s chorea in a female child with rheumatic fever in Bhutan: a case reportTshering Penjor1, Thinley Dorji1, Sangay Wangchuk11Department of Internal Medicine, Central Regional Referral Hospital, Gelephu, BhutanAddress of corresponding author: Dr Tshering Penjor, MD. Department of Internal Medicine, Central Regional Referral Hospital, Gelephu, Bhutan.

The multi-energy complementary power generation system with “wind-wind fire storage” as a typical representative is an important path to promote the symbiotic and complementary collaborative development of thermal power and new energy. Under the background of the construction of new power system and the integration of wind-wind, fire and storage, the scientific and rational configuration optimization of multi-energy complementary power generation system has become an important prerequisite for its sustainable development. In this paper, a two-layer optimization model for multi-energy complementary power generation system configuration based on particle swarm optimization is proposed. The outer layer optimization aims to maximize the net income of the wind-wind storage power generation system, and the inner layer optimization aims to minimize the carbon emission of thermal power units, so as to realize the balance between environmental benefits and economic benefits of the multi-energy complementary power generation system. The research results provide a reference for the planning and configuration of wind-wind-fire storage complementary power generation system.

This paper explores the role of Intrusion Detection Systems (IDS) in the context of High-Frequency Trading (HFT). Given the rapid, automated nature of HFT, it’s crucial to have robust security measures to promptly detect and address any malicious activities. IDS presents a compelling solution by monitoring network traffic and detecting any suspicious activities based on predefined rules. By considering various types of IDS and their appropriateness for HFT environments, this paper discusses effective implementation strategies and the impact of these systems on HFT operations. We demonstrate through this discussion that while incorporating IDS within HFT may present specific challenges, it is a crucial component for the secure and efficient functioning of HFT platforms.

In recent years, with the updating and iterating of new global technologies, digital twins (DTs) originated in the aerospace industry has been widely used in smart manufacturing, smart construction, and smart management as a new type of informatization management tool. It is therefore important for scholars to understand the current state of research on DTs to conduct more targeted research in the future. Based on Scopus, 7384 publications related to DTs were found from 1951 to 2023 in this study. With VOSviewers, the major countries, authors, and institutions researching DTs globally were analyzed and discussed. In conclusion, the study found that since 2018, increasing numbers of scholars around the globe, especially in China and the United States, have conducted relevant research in relation to DTs. Manufacturing and construction are the most common application areas for DTs. Over the past three years, the integration of AI, IoT, cloud, and digital technologies has developed into a hotpot of research. Additionally, communication technologies such as 5G and 6G contribute to the development of DTs. In the future, it can be predicted that DTs will be utilizing machine learning, blockchain and other technologies as a result of advancements in becoming smarter and more secure over the years.

The Andean and Atlantic forests are separated by the open vegetation corridor, which acts as a geographic barrier. However, these forests experimented cycles of connection and isolation in the past which shaped the phylogeographic patterns of their biotas. We analyzed the evolutionary history of the Rufous-capped Antshrike (Thamnophilus ruficapillus), a species with a disjunct distribution in the Atlantic and Andean forests and therefore an appropriate model to study the effect of the open vegetation corridor and the Andes on the diversification of the Neotropical avifauna. We performed a phylogenetic/phylogeographic analysis including the five subspecies, using mitochondrial and nuclear genomic DNA, and also studied their differences in vocalizations and plumage coloration. Both the mitochondrial and nuclear DNA evidenced a marked phylogeographic structure with three differentiated lineages that diverged without gene flow in the Pleistocene (1.0-1.7 million years ago): one in the Atlantic Forest and two in the Andean forest. However, the two Andean lineages do not coincide with the two disjunct areas of distribution of the species in the Andes. Vocalizations were significantly different between most subspecies, but their pattern of differentiation was discordant with that of the nuclear and mitochondrial DNA. In fact, there is no song differentiation between the subspecies of the Atlantic Forest and that of the northwestern Bolivian Andes, even though they differ genetically and belong to different lineages. Consistently, no differences were found in plumage coloration between the subspecies of the Atlantic Forest and that of the southern Andes. Our results suggest a complex evolutionary history in this species, which differentiated both due to dispersion across the open vegetation corridor, likely during a period of connection between the Andean and Atlantic forests, and as a consequence of a geographic barrier in northern Bolivia. In both cases Pleistocene climatic oscillations appear to have influenced the species diversification.

An operating system is the essence of software, serving as the foundation for the operation of various application software. The security of the operating system is crucial for the national informatization construction. Data indicates that many cybersecurity incidents result from exploiting security vulnerabilities in the operating system. Linux is currently the most widely used open-source operating system, with thousands of Common Vulnerabilities and Exposures (CVE) related to Linux system reported each year. Therefore, research and prevention of vulnerabilities in the Linux system are particularly important. To gain a better understanding of the characteristics of Linux system vulnerabilities, this paper leverages knowledge in the field of software security to analyze nearly 10,000 historical vulnerability data in two core systems of Linux: Linux Kernel and Debian Linux. The study explores the evolutionary patterns of vulnerability characteristics. Specific research contents include: (1) Data collection and cleaning of vulnerability data in Linux Kernel and Debian Linux systems; (2) Cross-statistical analysis of structured data features in vulnerability reports; (3) Unstructured data feature mining in vulnerability reports based on domain knowledge; (4) Analysis of the evolution of vulnerability characteristics. This paper provides empirical lessons and guidance for Linux system vulnerabilities to assist practitioners and researchers in better preventing and detecting vulnerabilities in Linux and Linux-based systems.

Dongting Lake wetland is a typical lake wetland in the Middle and Lower Yangtze River Plain in China. Due to the influence of natural and human activities, the landscape pattern has changed significantly. 12 Landsat images of Dongting Lake wetland from 1991 to 2022 were extracted and classified based on the CART decision tree method. The dynamic characteristics of wetland vegetation spatial pattern changes were analyzed using landscape pattern index, dynamic degree model and transition matrix model. Redundancy analysis and grey correlation analysis methods were used to explore the driving factors. The results showed that from 1991 to 2022, the area of water and mudflat showed a trend of first decreasing and then increasing due to the establishment of the Three Gorges Dam. The mutual conversion of mudflat and water was one of the forms of landscape transformation, while the mutual conversion of sedge and reed area was the main trend of vegetation landscape change. In the past 32 years, the fragmentation degree of Dongting Lake wetland landscape has increased, the heterogeneity has decreased and the landscape shape has become more complex. Water level had the greatest contribution to wetland landscape fragmentation, with the lower the water level, the greater the degree of landscape fragmentation. Human activities were the most important driving force, especially the policy changes in reed and woodland, as well as the establishment of the Three Gorges Dam, which have a significant impact on the landscape change pattern and ecological function of wetland. The research results are of great significance for wetland ecological restoration and environmental protection, providing scientific support for China to achieve the goals of “carbon peak” and “carbon neutrality”.