bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sublethal effects of cadmium on the osmoregulatory and acid-base parameters of tilapia (Oreochromis niloticus) at various times
Authors: Soegianto Agoes , Yulianto Bambang , Payus Carolyn Melissa , Affandi Moch , Mukholladun Wildanun , Indriyasari Khudrotul Nisa , Marchellina Ary , Rahmatin Nailul Muthiati 
Published: February 2023

Abstract

Background. Cadmium (Cd) can contaminate aquatic environments as a result of anthropogenic activity. Cd accumulates quickly in the tissues of fish and has the potential to affect their physiology, including osmoregulation and acid-base balance. Therefore, the purpose of this study was to examine the sublethal effects of Cd on the osmoregulation and acid-base balance of tilapia Oreochromis niloticus at different times.
Methods. Fish were exposed to sublethal concentrations of Cd (1 and 2 mg/L) for 4 and 15 days. At the end of the experiment, fish were collected from each treatment to examine the levels of Cd and carbonic anhydrase (CA) in the gills, plasma osmolality, ions, blood pH, pCO2, pO2, and hematological parameters.
Results. Cd concentrations in gills rose with increasing Cd concentrations in the medium and exposure time. Cd inhibited respiration by generating metabolic acidosis, decreasing gill CA, reducing pO2, plasma osmolality, Cl-, and K+, particularly at 2 mg/L for 4 days and 1 and 2 mg/L for 15 days. Red blood cell (RBC), hemoglobin (Hb), and hematocrit (Ht) levels decreased as Cd levels in water and exposure duration increased.
Conclusion. Cd inhibits respiration, lowers RCB, Hb, and Ht levels, and decreases ionic and osmotic regulation. All of these impairments can limit a fish's ability to provide appropriate oxygen to its cells, hence diminishing its physical activity and productivity.
Type I Fiber-Predominant Muscle Targeted- Low Volume Progressive Resistance Training Improves Aerobic Capacity in Young Sedentary Individuals
Authors: ŞAHİN Elif , AYAR Ahmet 
Published: February 2023

Abstract
PURPOSE: This pilot study examined possible effects of a low-volume, short-term progressive resistance exercise (PRE) protocol, specifically targeting muscles with predominantly type I fibers (namely soleus, tibialis anterior, vastus medialis, adductor magnus and biceps femoris), on aerobic capacity in young sedentary individuals.
METHODS: Volunteer (19-25 year old) were randomly assigned into one of the three group: PRE (performed progressive resistance training, targeting muscles with predominantly type I fibers, 25 minutes bouts, 3 times/week, for 6 weeks), walking (W) (65-75 % of maximal heart rate, 25 minutes bouts, 3 times/week for 6 weeks) and control group (C) (n=12 for each). Baseline and final evaluations of cardiopulmonary fitness (included VO2 peak, breathing reserve, e.g) was assessed by incremental cardio-pulmonary exercise testing
RESULTS: In PRE group, median value of peak VO2 significantly increased (from 33,55 ml/kg.min-1 to 37,4 ml/kg.min-1, p=0,008) after training, while no significant change was obtained in W and C groups. VO2 peak/fat free mass (FFM) significantly increased from 40,36 ml/kg.min-1 to 45,4 ml/kg.min-1 in PRE group (p= 0,006) but did not change significantly in either W or C group. Breathing reserve at maximum exercise level was 82,4 L (74,8-105,6) before training and this value was 62,4 L (55,2-83,4) after training at PRE group (p=0,003) but did not change significantly in W and C group either.
CONCLUSION: Results implicates that, this time-saving protocol, also suitable for performing in the home environment, could be beneficial for young sedentary individuals who can not perform aerobic exercise.
Machine Learning-enabled Globally Guaranteed Evolutionary Computation
Authors: Li Bin , Wei Ziping , Wu Jingjing , Yu Shuai , Zhang Tian , Zhu Chunli , Zheng Dezhi , Guo Weisi , Zhao Chenglin , Zhang Jun 
Published: February 2023

Abstract
Evolutionary computation, e.g., particle swarm optimization (PSO), has made impressive achievements in solving complex problems in science and industry. As an important open problem for more than 50 years, there is still no theoretical guarantee on the global optimum and the general reliability, due to lack of a unified representation of diverse problem structures and a generic mechanism to avoid local optimums. The long-standing pitfalls severely impair their trusted applications in a variety of problems. Here, we report a new evolutionary computation framework aided by machine learning, named EVOLER, which for the first time enables the theoretically guaranteed global optimization of complex nonconvex problems. This is achieved by: (1) learning a low-rank representation of problem with the limited samples, which helps to identify one attention subspace; and (2) exploring this small attention subspace via the evolutionary computation method, which allows to reliably avoid local optimums. As validated on 20 challenging benchmarks, it finds the global optimum with probability approaching 1; and moreover, it attains the best results in all cases, thus substantially extending the applicability in diverse problems. We use EVOLER to tackle 2 important problems, dispatch of power grid and inverse design of nano-photonics devices, whereby it consistently gains the optimal results that were rarely achieved by state-of-the-art methods. Our method takes a crucial step forward in globally guaranteed evolutionary computation, overcoming the uncertainty of data-driven black-box methods, offering broad prospects for tackling complex real-world problems.
The importance of species addition versus replacement varies over succession in plant communities after glacial retreat
Authors: Cantera Isabel , Carteron Alexis , Guerrieri Alessia , Marta Silvio , Bonin Aurélie , Ambrosini Roberto , Anthelme Fabien , Azzoni Roberto , Almond Peter , Gazitúa Pablo Alviz , Cauvy-fraunié Sophie , Lievano Jorge Ceballos , Chand Pritam , Sarma Milap Chand , Clague John , Rapre Justiniano Alejo Cochachín , Compostella Chiara , Encarnación Rolando Cruz , Dangles Olivier , Eger Andre , Erokhin Sergey , Franzetti Andrea , Gielly Ludovic , Gili Fabrizio , Gobbi Mauro , Hagvar Sigmund , Khedim Norine , Meneses Rosa , Peyre Gwendolyn , Pittino Francesca , Rabatel Antoine , Urseitova Nurai , Yang Yan , Zaginaev Vitalii , Zerboni Andrea , Zimmer Anais , Taberlet Pierre , Diolaiuti Guglielmina , Poulenard Jérôme , Thuiller Wilfried , Caccianiga Marco , Ficetola Francesco 
Published: February 2023

Abstract
Mechanisms underlying plant succession remain highly debated. A global quantification of the relative importance of species addition versus replacement is lacking due to the local scope of most studies. We quantified their role in the variation of plant communities colonizing the forelands of 46 retreating glaciers distributed worldwide, using both environmental DNA and traditional surveys. Both mechanisms concur in determining community changes over time but their relative importance varied over time along successions. Taxa addition predominated immediately after glacier retreat, as expected in harsh environments, while replacement became more important for late-successional communities. Those changes were aligned with total beta-diversity changes, which were larger between early successional communities than between late-successional communities (>50 years since glacier retreat). Despite the complexity of community assembly over plant succession, our global pattern suggests a generalized shift from the dominance of facilitation and/or stochastic processes in early successional communities to a predominance of competition later on.
Embodied carbon emission in the industrial equity portfolios of the leading global asset managers
Authors: Guan Dabo , Chen Danbo , Yu Xiang , Zhang Zengkai , Wang Jinglei , Chen Yuxing 
Published: February 2023

Abstract
Investors, hidden at the top of the global supply chain, are the key beneficiaries of the entire chain. However, they appear to generate only a small number of direct emissions which may obscure the reality that they should undertake more climate responsibility. No systematic accounting and disclosure of carbon emissions are incorporated in the financial institution assets. Here, we examine the embodied carbon emissions of the 380 leading global asset managers, using industrial equity portfolios as an example, and show that the embodied carbon emissions of these companies' industrial portfolios have reached 636.97–875.88 MtCO2-eq, and are expected to rising rapidly in 2019. Over 90% of the financed carbon emissions were embodied in the industrial equity portfolios of the top 20 asset managers in North America and Europe. Meanwhile, weighted average carbon intensity (WACI) and carbon emission to revenue (CETR), reflecting institutions' carbon exposure and efficiency, have not decline tremendously over the last decades, despite divestment only occurring in a few typical high carbon-intensive industries. Moreover, the leading investee companies in the emissions embodied in the industrial equity portfolio were highly contributed by the leading investee companies in high carbon-intensive sectors. In the study, we propose an accounting framework that integrates macro-sector emissions data with micro-financial data to attribute carbon emissions embodied in equity investment activities to investors, which can inform targeted and effective climate reporting and action. Some large asset managers, for instance, play a pivotal role in portfolio investments' carbon emissions and therefore bear more responsibility for decarbonization equity portfolios.
Reducing risk for chronic disease: evaluation of a collective community approach to sustainable evidence-based health programming
Authors: Oestman Katherine , Rechis Ruth , Williams Pamela A. , Brown Jill A. , Treiman Katherine , Zulkiewicz Brittany , Walsh Michael T. , Basen-Engquist Karen , Rodriguez Trina , Chennisi Catherine , Macneish Amber , Neff Alise , Pomeroy Mike , Bhojani Faiyaz A. , Hawk Ernest 
Published: February 2023

Abstract
Background

Community initiatives can shape health behaviors, such as physical activity and dietary habits, across a population and help reduce the risk of developing chronic disease. To achieve this goal and impact health outcomes, the Pasadena Vibrant Community initiative aimed to engage communities in an ongoing dialogue about the importance of healthy behaviors, implement and advance community-based strategies to promote health, and improve diet and physical activity behaviors. The initiative is centered around a collaboration between a backbone organization, steering committee, and 7 organizations funded to implement multicomponent, evidence-based programs with adults and youth in Pasadena, Texas.

Methods

A mixed methods evaluation of the initiative was conducted over 4 years. Data sources included document reviews of quarterly progress reports (n=86) and supplemental data reports (n=16) provided by collaborating organizations, annual stakeholder surveys (n=4), and interviews conducted with staff from a subset of collaborating organizations (n=4).

Results

The initiative reached over 50,000 community members per year through 19 evidence-based interventions and impacted health outcomes, including knowledge and application of healthy eating practices and increased physical activity. Thirty-one systems changes were implemented during the initiative, including 16 environmental changes. Steering Committee meetings and shared goals enabled connections, communication, and cooperation, which allowed partners to address challenges and combine resources to deliver their programs.

Conclusions

Community initiatives can effectively permeate the community by reaching individuals, improving physical activity and dietary habits, and ensuring sustainability. Based on the experience reported here, the success of a community initiative can be facilitated if collaborating organizations come together to implement evidence-based interventions and tailor them to the community, and if they are empowered by significant leadership and supportive collaboration and aligned by common goals.
Trial Registration: Not applicable
Significant transfer of surgical skills acquired in an advanced laparoscopic training program for total laparoscopic gastropexy assessed in a live porcine model
Authors: Peñata Carlos A Oviedo , Lemus-Duque Juan D. , Maldonado-Estrada Juan G. 
Published: February 2023

Abstract
Background. Currently, legal limitations avoid repetition and deliberate practice on cadavers and experimental models, which are fundamental for minimally invasive surgery skills acquisition. The CALMA Veterinary Lap-trainer (CVLTS) simulator is an ergonomic canine abdominal model developed to allow training of basic and advanced laparoscopic skills for total laparoscopic gastropexy (TLG) in dogs. This study aimed to evaluate an advanced curriculum using the CVLTS to simulate TLG with intracorporeal suturing and to evaluate the transfer of surgical skills to a live porcine model. Veterinarians trained in basic laparoscopic surgical skills (experimental group, n=10) practiced TLG in 15 training sessions. Performances before and after training were videotaped and compared to veterinary surgeons with intermediate (n=10) or advanced (n=6) laparoscopic skills, including a Hand Movement Assessment System (HMAS). Video records performed before and after training were evaluated by external experts using the Global Operative Assessment of Laparoscopic Skills (GOALS) and TLG-specific scales (SRS) and quantitatively by evaluating HMAS performance. Skill transfer was assessed by performing TLG in fattening pigs under operating room conditions using barbed sutures. Three months after surgery, a postmortem biopsy of the gastropexy site was evaluated by histopathology.
Results
GOALS and SRS scores (P<0.05) time, movements, and angular displacement during TLG significantly improved after training within the Experimental group (P>0.01) and when compared to expert and intermediate groups (P<0.05). The learning curve for intracorporeal suture stabilized since the tenth (out of 15) training session. Besides, trainees achieved significant skill transfer for TLG in the in vivo model, with no significant difference from the expert group. Histopathology findings of the gastropexy site showed mature collagen (100% of cases), cartilage and bone metaplasia, and foreign body reaction (25% of cases), indicating a strong healing process.
Conclusion
The advanced laparoscopic training program for total laparoscopic gastropexy resulted in a statistically significant improvement in surgical skills, as supported by objective assessment score (GOALS - SRS), metrics (HMAS), and postmortem findings at the gastropexy site. Training in the CVLTS simulator resulted in the successful transfer of surgical skills for TLG.
Multimedia Luxun literature online learning based on deep learning
Authors: Hongsheng Wang 
Published: February 2023

Abstract
As a great Chinese thinker and writer in the 20th century, Lu Xun and his literary works are widely known. However, as a successful cultural communication activist, editor and publisher, we still need to conduct in-depth research on Lu Xun in many aspects. Therefore, based on deep learning, this paper constructs an online multimedia learning system of Lu Xun Literature. This system takes the relationship between classical Lu Xun Literature and modern multimedia technology as the research object,and compare the calculation effect of other different types of algorithms and this dhraa algorithm. Through the availability of data, the dhraa algorithm is significantly better than other algorithms in the recommendation accuracy, thus proving its effectiveness.This system is managed by two servers and one system. The two servers are database server and web server respectively. After testing, the system has good bearing capacity, can make up for the limited processing capacity of the server, and ensure the system has high performance. Its performance characteristics also show that the system achieved the expected performance. This paper systematically combines Lu Xun's literature with modern multimedia, which can provide online learning services for Lu Xun's literature lovers, thus helping scholars to expand Lu Xun's research field and academic vision. This paper designs an effective online learning system of Lu Xun's literature by combining deep learning, multimedia technology and Lu Xun's literature.
Screening of a potential bioinformatics-based biomarker in keloid and its correlation with immune infiltration
Authors: Li Zihan , Zhang Chuwei , Zhang Qingrong , Dong Yipeng , Sha Xinyu , Jiang Ming , Yan Jun , Wang Wenmiao , Li Houqiang , Zhang Yi , Zhou Youlang 
Published: February 2023

Abstract
Keloid is a pathological result caused by cutaneous injury and irritation, which is on account of excessive deposition of collagen matrix and the growth of fibrous tissue. Long term and uncontrolled chronic inflammation is also one of the main causes. The mechanism of its formation is not clear. Therefore, in this study, we aimed to find key genes for diagnosis. We selected two datasets from the GEO database to find DGEs. Then, we finally obtained one gene, HOXC9, via WGCNA analysis and two algorithms (LASSO and SVM-RFE). Next, we analyzed its expression in normal tissues versus keloid and studied its change over time by Mfuzz time clustering analysis. Finally, through the analysis of this gene and previous studies we realized that, in addition to cell proliferation, immune infiltration also plays a role during the process of keloid formation, and we then explored the infiltration of immune cells in the normal versus keloid groups and the relationship between this gene and them.
Word and bit line operation of a 1x1 μm2 superconducting vortex-based memory
Authors: Golod Taras , Morlet-Decarnin Lise , Krasnov Vladimir 
Published: February 2023

Abstract
The lack of dense random access memory is one of the main bottlenecks for the creation of a digital superconducting computer. In this work we study experimentally vortex-based superconducting memory cells. Three main results are obtained. First, we test scalability and demonstrate that the cells can be straightforwardly miniaturized to submicron sizes. Second, we emphasize the importance of conscious geometrical engineering. In the studied devices we introduce an asymmetric easy track
for vortex motion and show that it enables a controllable manipulation of vortex states. Finally, we perform a detailed analysis of word and bit line operation of a 1×1 μm2 cell. High-endurance, nonvolatile operation at zero magnetic field is reported. Remarkably, we observe that the combined word and bit line threshold current is significantly reduced compared to the bare word-line operation. This could greatly improve the selectivity of individual cell addressing in a multibit RAM. The achieved one square micron area is an important milestone and a significant step forward towards creation of a dense cryogenic memory.
Development of Word Count Data Corpus for Hindi and Marathi Literature
Authors: Belhekar Vivek , Bhargava Radhika 
Published: February 2023

Abstract
India has a huge diversity of languages, and Hindi and Marathi are the most spoken languages in the northern and western parts of India. Hindi and Marathi have more than 528 million and 83 million speakers, respectively. The present paper describes the development of the Hindi Word Corpus (Hindi WordCorp) and the Marathi Word Corpus (Marathi WordCorp), reporting the frequency of single words (1-gram) used in written texts of the respective languages using the bag-of-words model (BoW). The word frequencies are provided for eleven decades, ranging from 1920 to 2020. Word frequency was separately computed for undated texts and texts published before 1920. These texts include books (fiction, non-fiction, history, autobiographies, etc.) and magazines. Academic and reference books were not used. Six hundred forty texts were used for the Hindi WordCorp, and 712 texts were used for the Marathi WordCorp. An analysis was employed to check whether the texts used were enough to stabilize the rank-order of the total frequencies of the words. Zipf’s and Heaps’ law coefficients were also estimated. Researchers in various areas like linguistics, social sciences, language sciences, text mining, machine learning analysis, etc., can use the dataset to answer research questions about language and culture. Some demonstrative examples are provided for using the datasets in the two languages. The dataset is made available on an open data repository. The paper is an account of dataset creation for Hindi and Marathi WordCorp. Hence, no empirical results or conclusions are made based on the data created. A web app named Indian Languages Word Corpus (ILWC) has been developed for users.
Fault Detection of Gearbox by Multivariate Extended Variational Mode Decomposition-Based Time-Frequency Images and Incremental RVM Algorithm
Authors: Nao Siwei , Wang Yan 
Published: February 2023

Abstract
A novel detection method based on multivariate extended variational mode decomposition-based time-frequency images and incremental RVM algorithm(MEVMDTFI-IRVM) is presented for fault detection of gearbox. The time-frequency images are constructed by multivariate extended variational mode decomposition. Compared with single-variable modal decomposition method, multivariate extended variational mode decomposition not only has an accurate mathematical framework, but also possible to better align the common frequency mode of the signal. The incremental RVM algorithm is presented for fault detection of gearbox based on the time-frequency images constructed by multivariate extended variational mode decomposition. The testing results demonstrate that the detection results of MEVMDTFI-IRVM for gearbox are stable, in addition, the detection results of MEVMDTFI-IRVM for gearbox are better than those of variational mode decomposition-based time-frequency images and incremental RVM algorithm (VMDTFI-IRVM), variational mode decomposition- RVM algorithm(VMD-RVM),and traditional RVM algorithm.
Pan-genome de Bruijn Graph using the Bidirectional FM-index
Authors: Depuydt Lore , Renders Luca , Abeel Thomas , Fostier Jan 
Published: February 2023

Abstract
Background: Pan-genome graphs are gaining importance in the field of bioinformatics as data structures to represent and jointly analyze multiple genomes. Compacted de Bruijn graphs are inherently suited for this purpose, as their graph topology naturally reveals similarity and divergence within the pan-genome. Most state-of-the-art pan-genome graphs are represented explicitly in terms of nodes and edges. Recently, an alternative, implicit graph representation was proposed that builds directly upon the unidirectional FM-index. As such, a memory-efficient graph data structure is obtained that inherits the FM-index' backward search functionality. However, this representation suffers from a number of shortcomings in terms of functionality and algorithmic performance.
Results: We present a data structure for a pan-genome, compacted de Bruijn graph that aims to address these shortcomings. It is built on the bidirectional FM-index, extending the ability of its unidirectional counterpart to navigate and search the graph in both directions. All basic graph navigation steps can be performed in constant time. Based on these features, we implement subgraph visualization as well as lossless read-to-graph alignment using search schemes. We demonstrate that we can retrieve all occurrences corresponding to a read within a certain edit distance in a very efficient manner. Through a case study, we show the potential of exploiting the information embedded in the graph's topology through visualization and sequence alignment.
Conclusions: We propose a memory-efficient representation of the pan-genome graph that supports subgraph visualization and lossless alignment of reads against the graph using search schemes. The C++ source code of our software, called Nexus, is available at https://github.com/biointec/nexus under AGPL-3.0 license.