Miracle-dz/UniFAR-FTUs huggingface dataset:
Hematological Response Studies of Climbing Perch (Anabas testudineus) Fed with Fermented Feed on the Fermentation of Kelakai Leaves (Stenochlaena palustris)

The purpose of this study was to analyze the nutritional value of fermented feed on kelakai leaves that are feasible as climbing perch feed and the hematological response of climbing perch raised by fermentation-based feeding of kelakai leaves. The study was carried out using an experimental method on the maintenance of climbing perch which was fed based on fermented leaves with 5 treatments and 3 tests. The parameters observed are the nutritional content of feed based on fermented leaves and hematological responses which include erythrocyte, leukocyte, hemoglobin, and hematocrit values. The results of the research on the nutritional content of feed showed that fermented feed on kelakai leaves has a protein content of 27%-31%, crude fiber content of 4%-7%, water content of 12%-14%, ash content of 11%-13%, fat content of 4%-6%. It was concluded that there was a decrease in fiber content and fat content and an increase in protein content, water content, and ash content. It happens gradually in line with the increase in probiotic dose. The results of the study on the hematological response of climbing perch are erythrocytes range from 1.65-3.91, leukocytes range from 223.23-287.43, hematocrit ranges from 15.30-35.07 and hemoglobin ranges from 5.37-10.33. The results of the proximate analysis of feed based on the fermentation of kelakai leaves showed that the values of water content, ash content, crude fiber, protein, and fat were in the recommended range. The hematological response of climbing perch shows good results and is in the normal range.
Cyclic AMP-guanine exchange factor activation inhibits JNK-dependent lipopolysaccharide-induced apoptosis in rat hepatocytes

Lipopolysaccharide (LPS) is known to damage hepatocytes by cytokines released from activated Kupffer cells, but the ancillary role of LPS as a direct hepatotoxin is less well characterized. The aim of this study was to determine the direct effect of LPS on hepatocyte viability and the underlying signaling mechanism. Rat hepatocyte cultures treated overnight with LPS (500 ng/mL) induced apoptosis as monitored morphologically (Hoechst 33258) and biochemically (cleavage of caspase 3 and 9 and the appearance of cytochrome C in the cytoplasm). LPS-induced apoptosis was additive to that induced by glycochenodeoxycholate or Fas ligand, was associated with activation of c-Jun N-terminal kinase B (JNK) and p38 mitogen-activated protein kinases (MAPK), and inhibition of protein kinase (AKT). Inhibition of JNK by SP600125, but not of p38 MAPK by SB203580 attenuated LPS-induced apoptosis, indicating JNK dependency. CPT-2-Me-cAMP, an activator of cAMP-GEF, decreased apoptosis due to LPS alone or in combination with glycochenodeoxycholate or Fas ligand. CPT-2-Me-cAMP also prevented LPS-induced activation of JNK and inhibition of AKT Taken together, these results suggest that LPS can induce hepatocyte apoptosis directly in vitro in a JNK-dependent manner and activation of cAMP-GEF protects against the LPS-induced apoptosis most likely by reversing the effect of LPS on JNK and AKT
Swimming depth, ambient water temperature preference, and feeding frequency of young Pacific bluefin tuna (Thunnus orientalis) determined with archival tags

We investigated the migration and behavior of young Pacific Bluefin tuna (Thunnus orientalis) using archival tags. The archival tag measures environmental variables, records them in its memory, and estimates daily geographical locations based on measured light levels. Of 166 archival tags implanted in Pacific bluefin tuna that were released at the northeastern end of the East China Sea from 1995 to 1997, 30 tags were recovered, including one from a fish that migrated across the Pacific. This article describes swimming depth, ambient water temperature, and feeding frequency of young Pacific bluefin tuna based on retrieved data. Tag performance, effect of the tag on the fish, and horizontal movements of the species are described in another paper. Young Pacific bluefin tuna swim mainly in the mixed layer, usually near the sea surface, and swim in deeper water in daytime than at nighttime. They also exhibit a pattern of depth changes, corresponding to sunrise and sunset, apparently to avoid a specific low light level. The archival tags recorded temperature changes in viscera that appear to be caused by feeding, and those changes indicate that young Pacific bluefin tuna commonly feed at dawn and in the daytime, but rarely at dusk or at night. Water temperature restricts their distribution, as indicated by changes in their vertical distribution with the seasonal change in depth of the thermocline and by the fact that their horizontal distribution is in most cases confined to water in the temperature range of 14−20°C.
A multibiomarker approach to investigate paracetamol effects in the reproduction regulatory axis of a male Neotropical catfish Rhamdia quelen

Abstract: Aim Paracetamol (PCM), or acetaminophen, is one of the most used drugs for human treatment of pain and fever. Since it has often been found in the aquatic environment, the aim of this study was to investigate the effects of PCM on the reproductive axis of male Rhamdia quelen catfish. Methods Different biomarkers were evaluated in hypothalamus, liver and gonads, as well as the plasma sexual hormone quantification. The fish were exposed to three PCM concentrations: 0.25, 2.5 and 25 µg. L-1 and to a control group (solvent acetone 0.0003%). After 14 days of exposure, fish were anesthetized, for blood sampling and biometrics, and after euthanasia, the tissues were sampled. Plasma was used for 11- keto testosterone and 17β - estradiol quantification. The hypothalamus was collected for brain aromatase (cyp19a1b) gene expression; the liver for the vitellogenin (vtg) gene expression and biochemical biomarkers; and gonad for the biochemical and histological biomarkers analyses. Results No alterations were observed in the hormone’s levels, sexual maturation level or in cyp19a1b and vtg gene expression. In the liver the non-protein thiols concentration increased at 2.5 µg. L-1 of PCM, and the superoxide dismutase (SOD) activity was reduced at 0.25 µg. L-1 of PCM. In gonads, glutathione S-transferase (GST) activity decreased and SOD activity increased at 25 µg. L-1 of PCM, while the glutathione peroxidase (GPx) activity reduced after exposure to both PCM concentrations. Conclusion The results showed that environmental concentrations of PCM can cause alterations in the antioxidant system, mainly in the gonads of R. quelen males. However, without significant change in the hormones levels or in the expression of genes related to the reproduction axis. These alterations occurred at concentrations already found in aquatic environment, including in Brazil.
Entropy-based Keyframe Established and Accelerated Fast LiDAR Odometry and Mapping

With the advancement of computer computing power, most of the current SLAM (Simultaneous Localization and Mapping) algorithms use graph optimization to build graphs. The key to graph optimization is to establish nodes and edges, that is keyframes and pose constraints. However, most algorithms still use heuristic methods to determine whether to establish new keyframes. This method usually creates redundant keyframes, adding invalid nodes to the graph optimization process, which results in lower efficiency of back-end optimization. Moreover, the frequent creation of keyframes leads to the need for frequent updates to the local map in front-end point cloud matching, reducing its efficiency. In this paper, we introduce an information-theoretic method for deciding when to generate new keyframes and optimizing updates to the local map for better front-end point cloud matching. Specifically, we calculate the information entropy of each point cloud matching pose. Once it reaches the set threshold, it indicates that the previous local map does not provide sufficient information for point cloud matching, which necessitates the establishment of a new keyframe. The local map is also updated immediately. This proposed method can establish keyframes with sufficient information and improve the accuracy of point cloud matching in the public dataset evaluation.
Reconstruction of Near‐Surface Hourly Wind Speed Data Sets During the Period 1959–2021 Over China

The reconstruction models of hourly 10‐m wind speeds were developed for each of 2384 stations over China using stepwise regression, random forest and XGBoost machine learning approaches based on hourly observed and ERA5 reanalysis data from 2005 to 2021. The reconstruction procedures applied observed hourly data to reduce the systematic biases of reanalysis data sets. Furthermore, the procedures employed the past dynamically consistent states of the atmosphere simulated by ERA5 reanalysis techniques to reduce/remove wind‐observed data impacts of long‐term non‐meteorological condition changes over time (e.g., urbanization around weather stations), which provide homogenous hourly wind speed data sets from 1959 to 2021. The systematic errors of the models' simulations derived from three approaches are similarly small, with almost two orders of magnitude smaller than ERA5 original data sets. The systematic errors of reconstructed data sets derived from stepwise regression are similar to its simulation; however, the biases from two machine learning methods are even much greater than ERA5 original data sets. This result implies that machine learning methods are not suitable for such typical time‐series predictions using the previous‐hour wind speed as a predictor to reconstruct wind speed data for the next hour. Therefore, stepwise regression was selected to reconstruct hourly wind speed data sets, which have much better quality than ERA5 reanalysis data with the median correctness increased by >50% and the median rRMSE decreased by 25%–50%. Consequently, the reconstructed wind speed data sets have great potential to be useful for more precisely assessing the characteristics/trends of wind energy resources in the past 60 years over China.
Competence framework of information technology for students of Thai Nguyen University of Agriculture and Forestry

Currently, with the positive impact of information technology (IT), the world’s agriculture is gradually shifting from the traditional agricultural model to the digital agricultural model, creating high productivity, increasing the product value and labor productivity. However, the agriculture with applied digital also requires laborers to be capable of applying IT in the agricultural sector. On the basis of theoretical research, output standards from bachelor training programs in the field of agriculture in the world and Vietnam, along with practical investigation results, the article focuses on two main contents: clarify the content of IT application capacity of a student in the field of agriculture and forestry; building a competence framework and assessment criteria for IT application competence for students in the field of agriculture and forestry. The results of the article are documents for Thai Nguyen University of Agriculture and Forestry as well as training institutions for bachelors and engineers in agriculture and forestry to refer to in the process of developing training programs, assessing outcomes for students, as well as innovating training methods towards developing learners’ capacity.
Seasonal variation and biological effects on mudflat erodibility in the Minas Basin, Bay of Fundy

ix List of Abbreviations and Symbols Used . x Acknowledgements . xi Chapter
Evaluating the Effects of Rivastigmine on Decision-Making in Patients with Mild Cognitive Impairment by Cambridge Neuropsychological Test Automated Battery (CANTAB); A Randomized, Double-Blind, Placebo-Controlled Trial

Background Decision-making is a complex process, and most studies showed that patients with mild cognitive impairment (MCI) make worse decisions than healthy people. Objectives This study aims to evaluate the effect of rivastigmine on the decision-making of MCI patients using the Cambridge Neuropsychological Test Automated Battery (CANTAB) tests. Methods The study was conducted at the Roozbeh Hospital neurology clinic, and 30 patients with mild cognitive impairment over 40 years old were randomly recruited to receive rivastigmine or placebo twice daily for 12 weeks. The initial dose of rivastigmine or placebo was 1.5 mg twice daily and was increased to 3 mg twice daily per patient compliance. A CANTAB test was conducted before and following the intervention. Results The mean age of patients in the rivastigmine group was 58.93 ± 10.88, and in the placebo group was 59.33 ± 10.34. The median MMSE (Mini-Mental State Examination) was 26 (IQR = 25 - 26) in both groups. Patients in the rivastigmine group showed significant differences in all subgroup tests of CGT, IST, and SST except in risk adjustment in the CGT test, discrimination in the IST test, and median correct RT on the go trial and SSRT in the SST test. The most commonly reported adverse effects were gastrointestinal complications. Conclusions According to the results, rivastigmine significantly improved the primary decision-making outcomes in comparison with placebo.
Benefits of Wasabi Supplements with 6-MSITC (6-Methylsulfinyl Hexyl Isothiocyanate) on Memory Functioning in Healthy Adults Aged 60 Years and Older: Evidence from a Double-Blinded Randomized Controlled Trial

Background: Cognitive functions decline with age. Declined cognitive functions negatively affect daily behaviors. Previous studies showed the positive effect of spices and herbs on cognition. In this study, we investigated the positive impact of wasabi, which is a traditional Japanese spice, on cognitive functions. The main bioactive compound of wasabi is 6-MSITC (6 methylsulfinyl hexyl isothiocyanate), which has anti-oxidant and anti-inflammatory functions. Anti-oxidants and anti-inflammatories have an important role in cognitive health. Therefore, 6-MSITC is expected to have positive effects on cognitive function. Previous studies showed the beneficial effects on cognitive functions in middle-aged adults. However, it is unclear that 6-MSITC has a positive effect on cognitive functions in healthy older adults aged 60 years and over. Here, we investigated whether 12 weeks’ 6-MSITC intervention enhances cognitive performance in older adults using a double-blinded randomized controlled trial (RCT). Methods: Seventy-two older adults were randomly assigned to 6-MSITC or placebo groups. Participants were asked to take a supplement (6-MSITC or a placebo) for 12 weeks. We checked a wide range of cognitive performances (e.g., executive function, episodic memory, processing speed, working memory, and attention) at the pre- and post-intervention periods. Results: The 6-MSITC group showed a significant improvement in working and episodic memory performances compared to the placebo group. However, we did not find any significant improvements in other cognitive domains. Discussion: This study firstly demonstrates scientific evidence that 6-MSITC may enhance working memory and episodic memory in older adults. We discuss the potential mechanism for improving cognitive functions after 6-MSITC intake.
Application of NMR Data to Evaluation of Deep Glutenite Pore Structure and Reservoir Validity

Capillary pressure curve and T2 spectrum have high correlation.The radication of product of porosity and permeability is used as input parameter to obtain the conversion factor C,then the maximum mercury saturation is used to determine the longitudinal conversion coefficient D between NMR T2 spectrum and intrusive mercury curve(i.e.,T2 integral curve times the maximum mercury saturation),and finally,acquiring the fitting capillary pressure curve.18 microcosmic pore structure parameters,which reflect the reservoir pore throat sizes,sortings and connectivity are quantitatively and continously obtained,such as expulsion pressure,maximum mercury saturation,average radius,lithology coefficient,sorting coefficient,and the like.The corresponding parameters estimating models have been built on the basis of analyzing and comparing multiple pore structure algorithms and intrusive mercury tests.The models have higher calculation accuracy,and may be used to quantitatively analyze the reservoir pore throat radius distribution.The reservoir quality aggregate index derived from the reservoir macro and micro parameters is better for reservoir validity evaluation.
CHAAIS: Climate-focused Human-machine teaming and Assurance in Artificial Intelligence Systems – Framework applied toward wildfire management case study

Climate change and the resulting cascade of impacts pose a real and urgent threat to human safety. Simultaneously, products from Artificial Intelligence (AI) research have grown exponentially and show high potential towards use in climate adaptation. However, an increasingly large barrier to responsive deployment and adoption of AI tools into climate change adaptation workflows is the actionable knowledge discrepancy between the fields of AI, Human Machine Teaming (HMT), AI Assurance, and the work of climate adaptation decision makers. To ensure alignment, applications of AI to climate change adaptation actions need a framework and knowledge base that map development considerations to the decision maker workflow. This paper introduces CHAAIS (Climate-focused Human-machine teaming and Assurance in Artificial Intelligence Systems), a design standard and accompanying knowledge base detailing the necessary human element of AI interaction in the high-risk domain of climate change. CHAAIS incorporates direct user interaction, decision maker adoption considerations, and downstream implications. Our process combines accepted HMT and AI Assurance principles for ethical design while testing specific issues in their intersection in the climate change domain. Specifically, we demonstrate this process with a case study in forestry and implications for wildfire management. The goal for the CHAAIS design framework and knowledge base is to be both a living information source and an adaptable method of tailoring future climate change AI solutions for responsive deployment directly informed by climate decision makers.
Multi Objective Generation Dispatch for Bulky Thermal Power Plants Using Novel Corona Virus Optimization Algorithm

This paper proposes a novel bio-inspired meta-heuristics (BIM) imposing highest quality scheduling for price of fuel for generating devices and emission level for cumbersome thermal devices subjected to valve factor loading, ramp rate constraints, ice deposition, wind strain and, prohibited running zones in addition to equality and inequality constraints. When compared to certain other comparable tactics, this corona virus (CV) optimization algorithm (CVOA) has two key advantages. To begin with, entered parameters are pre-determined based on disease data, prohibiting researchers from starting with random values. Second, techniques, in addition to putting this pace, have the ability to stop after a certain number of iterations. A virus variant is also proposed, in which multiple corona virus trails evolve in parallel and investigate a larger search area in a smaller number of epochs. Finally, heuristic algorithms and deep learning have been merged to know (DL) models, to discover most effective hyper-parameters at some stage in the education phase. Using a concurrent multi virus variant, where many corona virus lines evolve simultaneously and cover a larger search region in fewer iterations. Ultimate scheduling is carried out for three extraordinary test cases involving aforesaid constraints and it is ascertained that the results obtained outperform different soft computing (SC) methods.
Design of a Multiprobe Planar Near-Field Scanner for Ku-Band

Demand for broadband connectivity in moving platforms on land, sea, and air has opened the mass market for low-cost mobile ground-station terminals that employ electrically steerable antennas. The antennas of these terminal units need to be tested in a production line environment. Planar near-field scanning is considered as a convenient measurement method, but the time needed for conventional scanning may be prohibitive. In this paper, the design of a multiprobe planar near-field scanner for rapid antenna testing at Ku-band is presented. A probe array is moved along a spiral path to avoid large accelerations and decelerations of the probe array, and the near-field sampling is done simultaneously with multiple of respective receivers. Thus, the data acquisition time is significantly reduced compared to the single probe or receiver measurement. A preliminary antenna test-system design for the mobile ground-station terminal antennas operating at Ku-band is presented. The numerical results for simple representative antenna models suggest good performance of the system.
Transforming Automated Customer Service Responses Using ChatGLM Model: A Case Study of Expressway Toll Station Information System

This article presents a case study on using the ChatGLM model to transform automated customer service responses in an expressway toll station system. The traditional methods are impractical for millions of daily inquiries, leading to robotic responses. The ChatGLM model enhances dialogue capabilities by providing accurate and informative responses, trained on a large dataset of customer service conversations. The article discusses voice question answering challenges in toll booths and potential improvements through ongoing research. The proposed intelligent voice recognition system offers benefits like understanding natural language queries, context understanding, adaptability, and multilingual support. The methodology describes the GPT model architecture and fine tuning for the toll station system. The experiments outline the toll station assistant system development, including voice input, NLP-based task processing, and text-to-voice synthesis. The fine-tuned ChatGLM model's process and evaluation results demonstrate its effectiveness compared to baseline models. In conclusion, the ChatGLM model significantly enhances the toll station voice assistant response service.
Electronic Reprint Biological Crystallography Phenix : a Comprehensive Python-based System for Macromolecular Structure Solution

permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are cited. Acta Crystallographica Section D: Biological Crystallography welcomes the submission of papers covering any aspect of structural biology, with a particular emphasis on the structures of biological macromolecules and the methods used to determine them. Reports on new protein structures are particularly encouraged, as are structure–function papers that could include crystallographic binding studies, or structural analysis of mutants or other modified forms of a known protein structure. The key criterion is that such papers should present new insights into biology, chemistry or structure. Papers on crystallographic methods should be oriented towards biological crystallography, and may include new approaches to any aspect of structure determination or analysis.