In context of the prolonged invasion of smooth cordgrass Spartina alterniflora, numerous native birds have progressively adapted to this invaded plant. Not only certain non-specialist birds demonstrate an ability to inhabit and utilize smooth cordgrass, but a subset of specialist birds is also detected in the habitat as well. In this study, we investigate a previously undocumented Rallidae species, the slaty-breasted rail Lewinia striata, living in smooth cordgrass. These rails exhibit a significant reliance on the invaded vegetative community during their breeding season, engaging in foraging, vocalization, and even successful reproduction within the smooth cordgrass. These findings underscore the likelihood that amidst the ongoing decline of natural wetlands, those avian species with a profound dependence on marsh ecosystems may be compelled to adopt invasive smooth cordgrass as a vital refuge. Such a transition is poised to impact their distribution, foraging, and reproduction. With the backdrop of large-scale removal of smooth cordgrass on the China coast, the disappearance of smooth cordgrass may harm the population of these birds. Further dedicated investigations and tracking of more individuals are needed to understand the specific ecological impact on slaty-breasted rail.

Facultative scavenging can be observed across a large range of carnivorous mammals, but is an uncommon behavioural trait in cheetahs (Acinonyx jubatus). Very few incidents of cheetahs scavenging have been reported, with no explanation given as to why it may occur. In this paper we provide three more observations of cheetahs scavenging between 2019 and 2023 in three different protected areas in South Africa and Malawi. We suggest a common factor between these observations, namely that all adult individuals involved were temporarily housed in holding enclosures (bomas) during relocation processes and were provisioned with carrion as supplemental feed. The observed scavenging events could also have been influenced by the easy access of food in a situation where food acquisition was potentially difficult (i.e. old age, loss of hunting partner, mother with cubs). We hypothesise that these contributing factors, combined with the prior exposure of the adult individuals to eating carrion, could be a potential explanation for our observations of cheetahs scavenging. These observations provide a basis for further research into cheetah scavenging behaviour and the potential impacts of translocations that require prolonged holding periods on wildlife behaviour post-release. Understanding these behavioural shifts is crucial for cheetah conservation, as successful reintroduction efforts depend on the ability of cheetahs to adapt to new environments and food acquisition strategies.

Due to the nonlinearity, non-stationarity and noise interference of the rolling bearing fault signals of wind turbines, the extraction of features is challenging. This paper proposes a fault diagnosis method for wind turbine bearings based on the improved dung beetle optimizer (IDBO) optimized Long Short-Term Memory (LSTM) network. Firstly, Levy flight strategy and T-distribution perturbation strategy are integrated into the traditional dung beetle optimizer (DBO) to optimize the algorithm. The optimized IDBO algorithm solves the problems of low convergence accuracy and easy entrapment into local optima in the traditional dung beetle algorithm. Secondly, the IDBO algorithm is combined with the long short-term memory method to build the IDBO-LSTM fault diagnosis model. The advantage of fewer parameters in this algorithm enables the model to reduce the overall number of parameters and computational complexity while ensuring the accuracy of temporal feature extraction. Finally, this pa-per takes the bearing open dataset of Case Western Reserve University as an example to compare the proposed method with other models through optimization tests. The experimental results show that the IDBO-LSTM model outperforms other models, with a fault diagnosis accuracy rate of 98.3%. This demonstrates the superiority of the proposed improved dung beetle optimizer and effectively improves the accuracy of fault diagnosis for rolling bearings of wind turbines.

Understanding the genetic processes underlying divergence and connectivity among species is crucial for identifying evolutionary histories and informing conservation strategies. The Santalum genus, exhibits distinct genetic variations across the complex geographic regions of Australia, Asia, and the Pacific Islands. This study leveraged genome-wide SNP markers to explore the genetic relationships within critically endangered and non-threatened species in an Austral-Pacific sandalwood complex, including Santalum lanceolatum, S. leptocladum, and S. macgregorii. Our findings revealed significant geographic partitioning and genetic divergence mostly aligned with current taxonomic classifications. However notably, we showed S. macgregorii populations in Papua New Guinea (PNG) were divided into two distinct genetic groups: one in the Central and Gulf provinces and another in the Western Province, which shows a closer genetic relationship with S. lanceolatum from Australia’s Northern Peninsula Area (NPA). This genetic connection suggests a history of secondary contact and potential hybridization, influenced by historical land bridges and geological events. Our study highlighted that the sandalwood trees from the Western Province may represent a divergent lineage of S. lanceolatum, the S. macgregorii populations in the Central and Gulf provinces display vicariant divergence due to geographic isolation. These insights underscore the evolutionary complexity of sandalwoods and emphasise the need for tailored conservation strategies. Our results advocate for genetic rescue programs involving NPA S. lanceolatum to enhance reproductive success in threatened sandalwood populations, offering crucial guidance for conservation and management efforts in Australasia.

A document by Gairan Pamei. Click on the document to view its contents.

Seasonal differences in marine size spectra of micronekton at the shelf-ocean interface of the northern (NBUS) and southern Benguela Upwelling System (SBUS) in Feb-Mar 2019 and Sep-Oct 2021 were analysed. It was distinguished between mesopelagic fishes and total micronekton, comprising both the invertebrate and the vertebrate components. The metabolic theory of ecology (MTE) model containing a resource and a temperature term and a term representing a transfer function was applied to test three different types of size spectra slope estimates. The model fitted best with linear slopes calculated of log-binned averaged community biomass (LBNbiom method), while maximum likelihood without binning and quantile regression estimates without averaging proved less effective. The best model for total micronekton contained significant effects both for resource term and transfer function, but not for temperature. Normalized biomass size spectra slopes of the total micronekton were in the range predicted by MTE ranging between -0.80 and -1.37, and NBUS slopes were steeper than SBUS slopes in both seasons. The slopes for the fishes’ subcomponents were less steep ranging from -0.23 to -0.92, where values > -0.75 fall outside the theoretical range, suggesting that selecting taxonomic subsets for size spectrum analysis is problematic. The importance of the productivity regime shaping the biomass spectrum directly through the resource level and indirectly through the transfer function is highlighted.

The human gut microbiome exhibits characteristics of complex ecosystems, including the ability to resist and compete with exogenous species or communities. Understanding microbiome responses to such competition is crucial, especially for fecal microbiota transplantation (FMT), where success depends on microbial interactions. During these processes, microbial communities undergo coalescence, combining and interacting in ways that lead to complex ecological outcomes. In this study, we investigated the coalescent dynamics of ten pairs of human gut microbiota through in vitro co-culturing. Metaproteomic analysis revealed that post-coalescence changes were not simply an average of the initial microbiotas but instead, both coalescent microbiotas behaved as cohesive structures, influencing the competitive outcome towards one of them.. While taxonomic similarities were observed between co-cultured communities and their parental samples, 23% of proteins showed differential expression. Interestingly, the competitive outcomes followed a “rock-paper-scissors” dynamic, with different species contributing to competition outcomes across different pairs. This highlights the complexity of microbial competition, suggesting that no single factor consistently determines dominance. Pre-co-culturing may thus be a promising method for predicting outcomes in FMT and other ecological therapies.

Smith-Magenis Syndrome (SMS) is an uncommon genetic disorder caused by microdeletions of chromosome 17p11.2 including the RAI1 gene, or loss-of-function mutations that directly affect RAI1. Due to the involvement of RAI1 in neurodevelopment, SMS leads to typical pathologic features in the behavioral and physical phenotype that must be recognized by clinicians

A document by Muhammad Nadeem Ahmad. Click on the document to view its contents.

Background: Sinusoidal obstruction syndrome (SOS), a serious complication after hematopoietic cell transplant (HCT), is associated with multi-organ dysfunction (MOD) and a high mortality rate. In severe cases, continuous kidney replacement therapy (CKRT) is initiated to manage fluid overload (FO) and acute kidney injury. Studies that evaluate the use of CKRT in this population are lacking. The aim of our study was to assess the outcome of critically ill children with severe SOS post HCT who received CKRT. We also sought to assess factors associated with survival and liberation post CKRT. Procedure: Retrospective review of all children admitted to the intensive care unit (ICU) with SOS post HCT who received CKRT from January 2010 to August 2022. Results: Among the 53 children who received CKRT post HCT, 13 had severe SOS. The median age was 6 years; 62% were males, and most (77%) received allogeneic HCT. In this cohort, 92% required respiratory support and 85% required vasopressor support. The ICU survival rate was 62%. Survivors experienced lower cumulative FO on the 2 days following CKRT initiation (-4.2% in survivors versus -0.5% in non-survivors, p=0.07). Higher urine output on D1 and D2 after discontinuation of CKRT was associated with successful liberation. Conclusions: In this study of post-HCT children with SOS and MOD who received CKRT, 62% survived until ICU discharge. This survival rate is encouraging as it approximates the survival rates of general pediatric cohorts treated with CKRT. Reducing FO after initiation of CKRT can improve survival in these children.

A document by Bahareh Abtahi-Naeini. Click on the document to view its contents.

The understanding of financial behavior, especially its application in the stock market, has become increasingly important in recent years due to its significant impact on the global economy. One field that explores the intersection of finance and computer science to create predictive models is known as stock market prediction. This field aims to predict the behavior of various securities in the financial market. Deep Learning, one of the most renowned and utilized techniques, consists of various deep neural network structures that facilitate learning from non-linear models. In this study, we utilized open data from some of Brazil’s largest companies – Petrobras (PETR4), Itausa (ITSA4), and Vale (VALE3) – provided by BovDB, which includes stock quote data for all companies listed on the Brazilian stock market from 2000 to 2020. The data for the years in question were processed using a recurrent neural network to assess the impact of a price correction factor that accounts for the influence of past events not included in the training and validation results of the RNN model. The findings indicate a strong correlation of the model with temporal data and suggest a positive effect on reducing noise and forecast errors during model training.

This paper focuses on privacy-preserving distributed convex optimization across directed graphs within a prescribed time. To reduce the communication cost and achieve fast convergence, we propose a novel event-triggered and prescribed-time convergent distributed optimization algorithm built upon an extended Zero-Gradient-Sum method with free initialization. Specifically, we formulate event-triggering conditions for each agent, ensuring that inter-agent communication occurs solely upon meeting these conditions, thus significantly reducing communication costs. By the Lyapunov stability theory, the proposed algorithm is proven to achieve an accurate convergence to the optima within a prescribed time. Moreover, we establish the absence of Zeno behavior throughout any arbitrary period except the specified convergence time. When the environment exists eavesdropping attacks, we further provide a privacy-preserving prescribed-time event-triggered distributed algorithm based on state and objective decomposition. Finally, two comprehensive simulations demonstrate the performance of our proposed algorithm.

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.

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.

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.