Miracle-dz/UniFAR-FTUs huggingface dataset:
The First Five Mitochondrial Genomes for the Family Nidulariaceae Reveal Novel Gene Rearrangements, Intron Dynamics, and Phylogeny of Agaricales

The family Nidulariaceae, consisting of five genera including Cyathus, is a unique group of mushrooms commonly referred to as bird’s nest fungi due to their striking resemblance to bird’s nests. These mushrooms are considered medicinal mushrooms in Chinese medicine and have received attention in recent years for their anti-neurodegenerative properties. However, despite the interest in these mushrooms, very little is known about their mitochondrial genomes (mitogenomes). This study is the first comprehensive investigation of the mitogenomes of five Nidulariaceae species with circular genome structures ranging in size from 114,236 bp to 129,263 bp. Comparative analyses based on gene content, gene length, tRNA, and codon usage indicate convergence within the family Nidulariaceae and heterogeneity within the order Agaricales. Phylogenetic analysis based on a combined mitochondrial conserved protein dataset provides a well-supported phylogenetic tree for the Basidiomycetes, which clearly demonstrates the evolutionary relationships between Nidulariaceae and other members of Agaricales. Furthermore, phylogenetic inferences based on four different gene sets reveal the stability and proximity of evolutionary relationships within Agaricales. These results reveal the uniqueness of the family Nidulariaceae and its similarity to other members of Agaricales; provide valuable insights into the origin, evolution, and genetics of Nidulariaceae species; and enrich the fungal mitogenome resource. This study will help to expand the knowledge and understanding of the mitogenomes in mushrooms.
The important contribution of secondary formation and biomass burning to oxidized organic nitrogen (OON) in a polluted urban area: insights from in situ measurements of a chemical ionization mass spectrometer (CIMS)

Abstract. To investigate the sources and formation mechanism of oxidized organic nitrogen (OON), field measurements of OON were conducted using an iodide-adduct chemical ionization mass spectrometer equipped with a Filter Inlet for Gases and AEROsols (FIGAERO-CIMS) during fall of 2018 in the megacity of Guangzhou, China. Using levoglucosan as a tracer of biomass burning emissions, the results show that biomass burning (49±23 %) and secondary formation (51±23 %) accounted for comparable fractions to the total particle-phase OON (pOON) but 24±25 % and 76±25 % to the gas-phase OON (gOON), respectively, signifying the important contribution of biomass burning to pOON and secondary formation to gOON in this urban area. Calculations of production rates of gOON indicated that hydroxyl radical (42 %) and nitrate radical (NO3) (49 %) oxidation pathways potentially dominated the secondary formation of gOON. A high concentration of NO3 radicals during the afternoon was observed, demonstrating that the daytime NO3 oxidation might be more important than the previous recognition. Monoterpenes, found to be major precursors of secondary gOON, were mainly from anthropogenic emissions in this urban area. The ratio of secondary pOON to Ox ([Ox] = [O3] + [NO2]) increased as a function of relative humidity and aerosol surface area, indicating that heterogeneous reaction might be an important formation pathway for secondary pOON. Finally, the highly oxidized gOON and pOON with 6 to 11 oxygen atoms were observed, highlighting the complex secondary reaction processes of OON in the ambient air. Overall, our results improve the understanding of the sources and dynamic variation of OON in the urban atmosphere.
ETU-Net: efficient Transformer and convolutional U-style connected attention segmentation network applied to endoscopic image of epistaxis

Epistaxis is a typical presentation in the otolaryngology and emergency department. When compressive therapy fails, directive nasal cautery is necessary, which strongly recommended operating under the nasal endoscope if it is possible. Limited by the operator's clinical experience, complications such as recurrence, nasal ulcer, and septum perforation may occur due to insufficient or excessive cautery. At present, deep learning technology is widely used in the medical field because of its accurate and efficient recognition ability, but it is still blank in the research of epistaxis. In this work, we first gathered and retrieved the Nasal Bleeding dataset, which was annotated and confirmed by many clinical specialists, filling a void in this sector. Second, we created ETU-Net, a deep learning model that smartly integrated the excellent performance of attention convolution with Transformer, overcoming the traditional model's difficulties in capturing contextual feature information and insufficient sequence modeling skills in picture segmentation. On the Nasal Bleeding dataset, our proposed model outperforms all others models that we tested. The segmentation recognition index, Intersection over Union, and F1-Score were 94.57 and 97.15%. Ultimately, we summarized effective ways of combining artificial intelligence with medical treatment and tested it on multiple general datasets to prove its feasibility. The results show that our method has good domain adaptability and has a cutting-edge reference for future medical technology development.
Exploration on the football player physical fitness video monitoring system based on information technology

Football is a high-intensity sport that requires high physical fitness from athletes. Physical fitness is a key element that every football player must master. This article aimed to design an information technology based football player physical fitness video monitoring system, which can provide coaches with detailed information about the athlete’s physical condition and help them develop training plans. This article mainly used experimental design and data comparison to analyze the pre and post monitoring data of football players. The experimental data showed that the speed standard deviation of athletes before and after monitoring was below 0.1 at 10m and 5m. A football player physical fitness video monitoring system based on information technology is a feasible way to provide coaches with detailed information about their physical condition and help them develop training plans.
International Journal of Hospitality Management the Impact of Quality Management on Productivity in the Hospitality Sector

This paper attempts to determine the relationship between quality and productivity in the hospitality sector. Although both variables are crucial to the competitive and value creation processes in hotels, few empirical studies have explicitly analyzed the relationship between them. Thus, we estimated a production function for a hotel sample that shows how a set of determinants influences labour productivity. Among these determinants we included different quality variables, defined from the point of view of total quality. The estimation results show a direct and significant effect of quality on labour productivity. This suggests that the implementation of total quality management (TQM) systems, or the adoption of the TQM principles, have a positive impact on hotel labour productivity.
The marine diatom Thalassiosira rotula: chemical profile and antioxidant activity of hydroalcoholic extracts

The cosmopolitan centric diatom Thalassiosira rotula produces compounds in its natural habitat that can inhibit copepod reproduction. Moreover, it has been reported to possess compounds with therapeutic effects beneficial for health care. In this experiment, the extraction yield, total phenolic content (TPC), antioxidant activity by 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging ability, ferric reducing/antioxidant power (FRAP) and oxygen radical absorbance capacity (ORAC), and chemical profile by gas chromatography-mass spectrometry (GC-MS) analyses of T. rotula were investigated. Extractions were performed with 50% and 70% ethanol. A higher extraction yield [0.21 ± 0.01 g extract/g dry weight (DW) diatom] was observed for 70% ethanol. In addition, higher TPC (5.80 ± 0.32 mg gallic acid equivalents (GAE)/g DW diatom) and antioxidant activity [DPPH inhibition of 17.53% ± 0.56%, FRAP of 766.67 ± 34.69 µM Trolox equivalents (TE), and ORAC of 58.87 ± 2.03 µM TE] were observed for this extract. Myristic acid, palmitelaidic acid, palmitic acid, eicosapentaenoic acid, 24-methylenecholesterol, and docosapentaenoic acid were identified as dominant compounds in both extracts, while extraction in 70% ethanol yielded a higher content of fatty acids such as myristic acid, eicosapentaenoic acid, docosapentaenoic acid, and sterol 24-methylenecholesterol. Thus, it can be concluded that extraction of T. rotula with 70% ethanol improves antioxidant activity and provides a higher yield of compounds such as polyunsaturated fatty acids and sterols. Therefore, the species T. rotula could be considered a sustainable source of essential fatty acids and other bioactive compounds for further applications.
Evaluating the effectiveness of ground motion intensity measures through the lens of causal inference

When solving the performance‐based earthquake engineering (PBEE) integral, the engineering demand parameters (EDPs) are assumed to be independent of the “upstream” parameters used in ground motion models (e.g., magnitude and source‐to‐site distance) after conditioning on the intensity measure (IM). This paper formulates a methodology for evaluating this conditional independence assumption through the lens of causal inference (CI). From a causal perspective, the effect of an upstream parameter on the EDP of interest is partially mediated by the IM with the remainder having a direct influence on the EDP. An IM is judged to be desirable (from a conditional independence standpoint) if the mediated effect of the upstream parameter is maximized, which implies that the direct effect is minimized. In the language of causal inference (CI), the IM, EDP and upstream parameters are described as the “treatment”, “outcome” and “confounding” variables, respectively. It then follows that the best performing IM is the one that maximizes the effect on the EDP after controlling for the upstream parameters. A semi‐parametric model that employs double machine learning is used to estimate the causal effect. The methodology is demonstrated through a case study application utilizing the responses from five special steel moment frames analyzed using 240 site‐agnostic ground motions. Compared to sufficiency‐based assessments, the casual inference method produces findings that are more explainable using structural dynamics principles and invariant to the number of ground motions used in the evaluation.
GPS-Derived Precipitable Water Compared with the Air Force Weather Agency's Mm5 Model Output

Abstract : Current moisture initialization sources lack the spatial and temporal resolution required for mesoscale moisture forecast accuracy critical for military operations. The Global Positioning System (GPS) satellite constellation provides an opportunity to extract accurate moisture observations based on the refraction of the GPS signal through the troposphere. GPS-derived precipitable water (PW) from two different research areas was independently compared with the Air Force Weather Agency s (AFWA's) MM5 PW model output. Results were concurrent with similar studies comparing GPS-derived PW with numerical weather models. The mean correlation in CONUS was 92.5%, while in Alaska it was 72.8%. Mean model biases were 1.22 mm in CONUS and 0.69 mm in Alaska. Mean RMSEs were 4.36 mm in CONUS and 2.76 mm in Alaska. In addition, comparisons were made between moist and dry locations, showing a 21.5% difference in correlation and a 17.8% difference in RMSE. The GPS network s superior temporal resolution captured the diurnal variations in PW, while the model consistently failed to take such variations into account as its forecast progressed. This seems it could be the largest source of error between the two data sets. A number of non-meteorological error sources exist that could impact use of GPS-derived PW in operational applications, such as terrain differences between the GPS receiver sites and the model interpolated heights. These error sources need to be further addressed prior to operational assimilation of this data into military weather models.
Ocean–atmosphere circulation coherences associated with temperature increase in Pakistan

In recent decades, temperature variations have significantly affected the ecosystem and human livelihood in Pakistan. The wavelet analysis is employed to identify the associations between regional temperature change and global teleconnections, i.e. Atlantic Multidecadal Oscillation (AMO), Arctic Oscillation (AO), North Atlantic Oscillation (NAO), El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Tropical Northern Atlantic Index (TNA), Pacific/North American Index (PNA), North Pacific Pattern (NP), Western Pacific Index (WP), and Western Hemisphere Warm Pool (WHWP). This paper first uses monotonic modified Mann–Kendall and Sen’s slope estimator to compute the temperature changes in Pakistan and its homogenous climatic regions during 1960–2020. It is found that the temperature in Pakistan has increased significantly at 0.23 °C dec−1 in the last 62 years, which is also higher than the global average increase. This increase is more evident in region IV and V in spring at 0.63 and 0.43 °C dec−1 respectively, followed by summer and autumn. Temperature changes in Pakistan and its sub-regions are mainly associated with NP, WP and WHWP with higher mean significant coherences. Overall, temperature changes are significantly influenced by multiple interactions of global teleconnections, and these combinations indicate that the integrated influence of teleconnections can better explain the regional temperature changes. The teleconnections with broader significant influence over Pakistan are NP + WP + WHWP, followed by Pacific-based (ENSO, PDO, and PNA), and Atlantic-based (AMO, AO, and NAO) indices as revealed by the mean significant coherences of 0.82, 0.82 and 0.72 respectively. Annually, AMO, TNA and WHWP showed significant correlation with higher magnitudes of 0.44, 0.42 and 0.20 respectively, indicating the modulation effect of these teleconnections on temperature changes over Pakistan. The combined impacts from the various teleconnections represent a considerable advancement in the accuracy of significant temperature variations over the country. These findings have significant implications for policymakers in terms of better planning and policies in light of climate change as well as atmospheric circulation variability.
Finance and Economics Discussion Series Divisions of Research & Statistics and Monetary Affairs Federal Reserve Board , Washington , D . C . Bank Core Deposits and the Mitigation of Monetary Policy

We consider the business strategy of some banks that provide relationship loans (where they have loan origination and monitoring advantages relative to capital markets) with core deposit funding (where they can pass along the benefit of a sticky price on deposits). These “traditional banks” tend to lend out less than the deposits they take in, so they have a “buffer stock” of core deposits. This buffer stock of core deposits can be used to mitigate the full effect of tighter monetary policy on their bank-dependent borrowers. In this manner, the business strategy of “traditional banks” acts as a “core deposit mitigation channel” to provide funds to bankdependent borrowers when there are monetary shocks. In effect, there is no bank lending channel of monetary policy associated with these traditional banks. In contrast, other banks mainly rely on managed liabilities that are priced at market rates. These banks do not have to shift from insured deposits to managed liabilities in response to tighter monetary policy. At the margin, their loans are already funded with managed liabilities. For these banks as well, there is no unique bank lending channel of monetary policy. The only banks that are likely to raise loan rates substantially in response to an increase in the federal funds rate are banks with a high proportion of relationship loans that are close to a loanto-core deposit ratio of one. These banks must substitute higher cost nondeposit liabilities, which have an external finance premium, for core deposits, which do not because of deposit insurance. Some of these banks may also face higher marginal costs as their loan-to-core deposit ratio approaches one because of the costs associated with lending to default-prone relationship borrowers. It is among these banks (which we refer to as high relationship lenders), and only these banks, that we find evidence of a bank lending channel – they significantly reduce lending in response to a monetary contraction. Importantly, these banks hold only a small fraction of U.S. banking assets. Thus, in the United States, the bank lending channel seems limited in scope and importance, mainly because so few banks that specialize in relationship lending switch from core deposits to managed liabilities in response to changes in interest rates. Υ The views expressed are those of the authors and do not necessarily reflect those of the Board of Governors of the Federal Reserve System or its staff. The authors wish to thank Jerry Dwyer and participants at the conference on “The Credit Channel of Monetary Policy in the 21 Century” (held at the Federal Reserve Bank of Atlanta on June 14, 2007) for their useful comments. The authors thank Reid Dorsey-Palmateer and Jessica Lee for their outstanding research assistance. All errors remain those of the authors.
Dimethyl Sulfoxide Inhibits Bile Acid Synthesis in Healthy Mice but Does Not Protect Mice from Bile-Acid-Induced Liver Damage

Simple Summary Bile acids are crucial in breaking down and absorbing fats. However, in excessive amounts, they can damage the liver. Our research investigated whether dimethyl sulfoxide (DMSO) could diminish bile acid production and subsequently protect the liver in mice. Our results showed that DMSO effectively reduced bile acid production in mouse primary hepatocytes and in vivo. Yet, DMSO failed to protect the liver when we evaluated its efficacy in two separate mouse models with liver damage induced or partially induced by excess bile acids. Notably, while DMSO decreases hepatic bile acid levels in healthy mice, the body appears to counterbalance this effect under disease conditions, resulting in persistent liver damage. These outcomes confirm that DMSO is not merely an inert solvent, but a biologically active agent. However, it falls short in treating liver diseases precipitated by elevated bile acid levels. Abstract Bile acids serve a vital function in lipid digestion and absorption; however, their accumulation can precipitate liver damage. In our study, we probed the effects of dimethyl sulfoxide (DMSO) on bile acid synthesis and the ensuing liver damage in mice induced by bile acids. Our findings indicate that DMSO efficaciously curbs bile acid synthesis by inhibiting key enzymes involved in the biosynthetic pathway, both in cultured primary hepatocytes and in vivo. Contrarily, we observed that DMSO treatment did not confer protection against bile-acid-induced liver damage in two distinct mouse models: one induced by a 0.1% DDC diet, leading to bile duct obstruction, and another induced by a CDA-HFD, resulting in non-alcoholic steatohepatitis (NASH). Histopathological and biochemical analyses unveiled a comparable extent of liver injury and fibrosis levels in DMSO-treated mice, characterized by similar levels of increase in Col1a1 and Acta2 expression and equivalent total liver collagen levels. These results suggest that, while DMSO can promptly inhibit bile acid synthesis in healthy mice, compensatory mechanisms might rapidly override this effect, negating any protective impact against bile-acid-induced liver damage in mice. Through these findings, our study underscores the need to reconsider treating DMSO as a mere inert solvent and prompts further exploration to identify more effective therapeutic strategies for the prevention and treatment of bile-acid-associated liver diseases.
Software Architectural Practices: Influences on the Open Source Ecosystem Health

The health state of a software ecosystem has been determined by its capacity of growth and longevity. Three health indicators represent a healthy software ecosystem: robustness, productivity, and niche creation. Studies focusing on understanding the causes and processes of the state of health of ecosystems have used these indicators largely. Researchers have intensified studies to understand how to achieve a good health state. Despite the growing number of studies, there is little knowledge about influences and actions to achieve health and, more specifically, that consider the effects of the software architecture on the ecosystem. This article presents a study exploring seven open source ecosystems within different domains to describe the influence of architectural practices on the software ecosystem health in terms of their motivations and effects. Our main goal was to understand how the software architecture and related practices can contribute to a healthy ecosystem. We conducted a netnography-based study to gather practices used to create and maintain the software architecture of these ecosystems. Our study brings evidence that architectural practices play a critical role in the achievement of ecosystems’ health. We found fifty practices that have influenced different aspects of health indicators. We highlight the importance of five influential factors – business goals, experience, requirements, resources, and time-to-market – for motivating the adoption of such practices. These factors may also contribute to understanding different strategies used to achieve a good health state. Moreover, we proposed a novel health indicator, trustworthiness, that accounts for the normal operation of a healthy software ecosystem.
Research on the improved apple classification method of AlexNet

To address the issue of high cost and low efficiency in the manual sorting of apples, we proposed an improved apple classification method based on the AlexNet architecture. The algorithm added a batch normalization layer after each convolutional layer in the network structure to speed up the model's training process. Furthermore, we replaced the fully connected layer with a global average pooling layer to reduce the number of training parameters and save model training time. To improve the algorithm's robustness, we also performed data augmentation on the training samples before validating the algorithm to obtain an expanded dataset. Experimental results showed that the improved AlexNet network shortened the training time by 0.54%, increased the testing speed by 2.5%, and improved the accuracy by 1.12% compared to the original AlexNet network. Moreover, the training time of the improved AlexNet network was lower than that of other networks (AlexNet, ResNet50, Vgg16). The improved AlexNet network can efficiently and quickly classify apples and promote the automation of apple classification.