Miracle-dz/UniFAR-FTUs huggingface dataset:
Fermentation, bioactivity and molecular identification of endophytic fungi isolated from mangrove Ceriops tagal

Abstract. Putra IPYA, Utami KS, Hardini J, Wirasuta IMAG, Ujam NT, Ariantari NP. 2023. Fermentation, bioactivity and molecular identification of endophytic fungi isolated from mangrove Ceriops tagal. Biodiversitas 24: 3091-3098. Mangrove-associated-endophytic fungi are recognized as a considerable source of bioactive compounds in drug discovery. This study evaluated the antimicrobial activity and toxicity of endophytic fungi isolated from Ceriops tagal. Four endophytic fungal isolates, documented as SU-1-4, were obtained. In addition, isolate SU-3 was further identified as Hypoxylon mangrovei according to the comparison of the internal transcribed spacer region. Each fungal isolate was fermented on a solid rice medium, then extracted with ethyl acetate at the end of fermentation. After that, the crude ethyl acetate extracts were partitioned between aqueous methanol and n-hexane, and the methanolic phases were subjected to phytochemical screening and antimicrobial and toxicity assays. Preliminary phytochemical identification suggested the presence of alkaloids, triterpenoids, and steroids in all fungal methanolic extracts. Among them, H. mangrovei SU-3 extract showed the most pronounced antimicrobial effects with minimum inhibitory concentration (MIC) values of 125 and 250 µg. mL-1 towards Staphylococcus aureus ATCC 6538 and Staphylococcus epidermidis ATCC 12228. Meanwhile, the toxicity assay employing the brine shrimp lethality test revealed that all fungal methanolic extracts were toxic, with LC50 values ranging from 173.09 to 227.76 µg. mL-1. Isolation of antibacterial compounds and evaluation of their cytotoxicity on human cancer cells will be promising for further studies.
Firm valuation in Brazil: evidence of overvaluation in the valuation reports

Under the Agency theoretical framework, information asymmetry is crucial in stakeholders’ conflicts. This problem may be present in the process of firm valuation. This work aims to analyze the determinants of the added value of firm financial experts’ valuations, i.e., the difference between disclosed firm value in the valuation report and firm market value. The study assesses the effect of ownership concentration, firm size, the costs of preparing the valuation report, and stock liquidity estimating a set of econometric models. The sample is composed of all firm valuation reports undertaken in Brazil between 2002 and 2012 with data hand collected from CVM (The Brazilian SEC) website and Economatica database. The results indicate that ownership concentration is directly related to the added value of financial experts’ valuations, indicating a possible problem of information asymmetry that benefits controlling shareholders who may be interested in higher firm valuation. The findings also indicate that firm size, higher cost of the firm valuation process, and firm market liquidity are associated with firm value overestimation. The paper contributes to the literature on firm valuation by using an important database with hand collected data from all firm valuation processes recorded at the CVM. Studies on firm valuation in Brazil are still scarce so that the finding that ownership concentration matters for firm valuation is important by showing that such process may be a source of agency conflicts.
Geant4 Monte-Carlo simulation for the response of INGA at TIFR-BARC Pelletron Linac Facility

The Indian National Gamma detector Array (INGA)[1] at Tata Institute of Fundamental Research (TIFR) consists of twenty four Compton suppressed high purity germanium detectors (HPGe). This is a powerful spectrometer used for the study of nuclear structure and dynamics by measuring γ-rays from an excited atomic nuclei produced in different nuclear reactions. A detailed knowledge of the efficiency of the array up to high energy is necessary to study high spin excitation near the shell closure and low mass nuclei which often produce high energy gamma rays of 4 to 5 MeV. A Geant4 simulation has been carried out to study the response of the array for various energies of γ-rays[2]. Investigation of the simultaneous hit efficiency of a gamma ray in clover and its BGO shield will validate the usage of the Compton suppressed clover for high energy gamma ray measurement with increased efficiency. The array has been simulated with the clover having 4-crystals arranged on a copper tray inside an aluminum housing, BGO anti-Compton shield, heavy metal collimator, target chamber and the beam line. The present INGA geometry at TIFR has the provision of placing 24 Compton suppressed clover detectors with 3 detectors each in 157◦, 140◦, 115◦, 65◦, 40◦ and 23◦ and 6 detectors at 90◦ with respect to the beam axis [3].
Ontogeny and miniaturization of Alvarezsauridae (Dinosauria, Theropoda)

The ontogenetic status of the known specimens of alvarezsaurid theropod dinosaurs is revised. We present histological data that the holotype of Parvicursor remotus from the Upper Cretaceous Barungoyot Formation of Mongolia is not an adult individual, as previously thought, but a juvenile less than one year old. The miniaturization took place only in the Late Cretaceous Asiatic Parvicursorinae, whereas the Late Cretaceous South American non-parvicursorine alvarezsaurids were large animals. The miniaturization occurred by shifting ossification to earlier ontogenetic stages, in particular, by the closure of the neurocentral sutures on the presacral vertebrae of juvenile animals. There is no morphological support for the myrmecophagy in the alvarezsaurids and a shift to a myrmecophagous ecological niche does not explain the need for miniaturization.
Shannon and Fisher entropy measures for a parity-restricted harmonic oscillator

We first present the analytical solutions to the Schrödinger equation with the parity-restricted harmonic oscillator V(x)=12mω2x2 0)~$ ? >(x>0) and then calculate the Shannon information entropies Sxn and Spn both in position space and in momentum space. It is interesting to find that the variation of the Shannon information entropy Spn in momentum space is different from our previous studies, i.e. the Spn first increases with the quantum number n and then decreases with the number n. This is a new and abnormal phenomenon and may be explained by the parity-restricted system. The BBM inequality is verified to be saturated, but the sum of the entropies first increases with the number n and then decreases with it. The entropy densities ρs(x) and ρs(p) are also demonstrated. We find that the Fisher entropy is exactly given by IF=8n+6,n=0,1,2,….
A Review of Hiding of Data in Mosaic Images by Reversible Color Transformations

3 Abstract: Images are transmitted through the internet for various purposes, such as confidential enterprise archives, document storage systems, medical imaging systems, and military applications. These images may contain secret or confidential information since it should be protected from leakage during transmissions. An approach for secure image transmission is needed, which is to transform a secret image into a meaningful Secret Fragment Mosaic Image with size almost same and looking similar to the preselected target image. The mosaic image is the outcome of arranging of the block fragments of a secret image in a way so as to disguise the other image called the target image. The mosaic image looks similar to a randomly selected target image. It is used for hiding of the secret image by color transforming their characteristics similar to the blocks of the target image. The appropriate information is embedded into the mosaic image for the recovery of the transmitted secret image.
Religious value-based strategy model on steel construction businesses performance

While the importance of implementing value-based strategies has been widely researched, empirical research on applying such strategies to create a religious atmosphere that can improve workers’ performance in companies is limited. Therefore, this study aims to generate a Value-Based Strategy Model for creating a religious atmosphere and examine its influence on steel construction businesses' performance in Indonesia. The model is based on the concept of religious-based values, which provide a competitive advantage for companies by affecting the performance of workers and the overall company performance. The population for this study was 120 steel construction companies in Indonesia, and the SEM-PLS technique was used for analysis. The findings demonstrate that a value-based strategy that creates a religious atmosphere significantly and positively affects the business performance of steel construction companies in Indonesia.
Bridging Assessment and Learning A Cognitive Diagnostic Analysis of a Large-scale Spanish Proficiency Test

There is still relatively little research on cognitive diagnostic analysis of large-scale, high-stakes language tests to assess the individualized strengths and weaknesses of every learner, and even less on the accuracy and applicability of the feedback information in post-hoc learning. Using both cognitive diagnostic results of 1.933 test takers of a national Spanish test and qualitative data from their bachelor thesis drafts, the precision of the diagnostic feedbacks was examined to verify its usefulness for better literature review and discussion. The results showed that this method has an appropriate model fit with the test performance, and is able to determine specific skill profile of each test taker, which is not always consistent with the scores provided by classical test analysis. By triangulating the diagnostic reports and the literature review and discussion of the learners’ thesis drafts, it is clear that the cognitive diagnostic approach in a large-scale test can assess the reading skills more accurately and the feedbacks are valuable for remedying the future academic reading and thesis revision.
Robust Self-Constructing Fuzzy Neural Network-Based Online Estimation for Industrial Product Quality

Online estimation for product quality is crucial for improving industrial process efficiency. However, model degradation and outliers usually challenge industrial quality estimation models. To tackle the above problems, a robust self-constructing fuzzy neural network (RSC-FNN) is developed in the article. In the RSC-FNN, the rules can be automatically created or pruned, obtaining the online self-constructing mechanism (OSCM). First, an online error compensation algorithm is developed to generate new rules. Second, the model performance and contribution of existing rules are evaluated online to delete redundant rules. Thus, the OSCM effectively improves the structural adaptability and compactness of the RSC-FNN. Moreover, the correntropy-induced criterion, which can handle complex outliers, is modified for the parameter learning algorithm. Hence, the adverse effect of outliers can be suppressed during the parameter updating process. Besides, we analyze the convergence of the RSC-FNN to ensure its feasibility in industrial applications. Finally, two industrial applications are studied to test the effectiveness of the RSC-FNN. Compared with other FNNs, the results indicate that the RSC-FNN performs better in learning efficiency, structure compactness, and robustness.
Imaging supermolecular interactions of the pharmaceutical-cocrystal of apigenin-nicotinamide binding with serum albumin

In this paper, a new pharmaceutical cocrystal was synthesized using apigenin (AP) and pharmaceutically acceptable conformer nicotinamide (Nico), and the drug delivery between AP-Nico pharmaceutical cocrystal and human serum albumin (HSA) in vivo was studied at atomic scale. The pharmaceutical cocrystal was characterized using Fourier-transform infrared (FTIR) spectroscopy, 1H NMR spectroscopy, differential scanning calorimetry (DSC), and powder X-ray diffraction (PXRD), and the self-assembling mechanism was explored. The dissolution and cumulative release in vitro were investigated. Molecular dynamic (MD) simulation combined with fluorescence spectroscopy was used to study the delivery mechanism of AP-Nico to HSA. The results showed that AP was pharmaceutically cocrystallized with Nico, which formed a pharmaceutical cocrystal mainly through hydrogen interaction between the -OH groups of AP and –NH2 groups of Nico. The solubility of the AP-Nico was 3 times higher than raw AP and the cumulative release rate was 71%. The fluorescence spectroscopy results showed that the AP-Nico pharmaceutical cocrystal bind with Sudlow’s site I inside the HSA molecule with hydrogen-bond interaction as the main force. The Sudlow’s site I of HSA conjugated with AP-Nico explains the conformational changes of HSA in-silico. This study provided a useful reference for synthesizing flavonoid pharmaceutical cocrystal to improve solubility and exploring the interaction mechanism while understanding its delivery mechanism in vivo.
Training Data Generation Using Human Link Model for State Estimation of Care Robot User

The importance of care robots is growing owing to the increasing numbers of the elderly and the shortage of caregivers. For robots to automatically assist the movements of the elderly users, the state of their pose should be estimated. Hence, we proposed a method for estimating the user’s state using candidate positions of the center of gravity of the robot user using a few sensors. In this method, sensor outputs in all states and movements of the user are collected in advance, and a state estimation and abnormality detection model created by machine learning using the relationship between the outputs and state is used as training data. However, it is difficult to collect training data pertaining to elderly people, before use, for this purpose. Therefore, a database of human actions is created for use as the training data. Rich databases of such actions performed sans robots already exist, but not where care robots are used. Conventional methods for simulating human body movements to estimate human states require actual data and expert coordination and do not address detailed state estimation for physical support. Therefore, this study proposed a method for generating training data using a human link model, which enables the creation of a model that can estimate the state of a robot user without requiring the elderly user to stand up and perform other robot-assisted actions before use. Training data is generated using a link model and candidate centers of gravity, a simple method by which the state of the care robot user can be estimated, and physical support for standing, walking, and sitting can be provided. The effectiveness of the state estimation using the link model generated training data is verified off-line using sensor data independently obtained from the actual movements of the robot and user and also through experiments using an actual care robot. The results validated the state estimation since the time error was sufficiently short (0.35–1.85s), and the experiment confirmed that the robot could realize assistive actions with 90% accuracy.
Improved latrine coverage may reduce porcine cysticercosis: a comparative cross-sectional study, Busia County, Kenya 2021

Introduction Smallholder pig farming is an important economic activity for many poor, rural communities in developing countries. Porcine cysticercosis is a growing public health risk in countries where pig rearing is popular. A sanitation-based intervention to reduce the prevalence of open defecation was completed in Busia County, Kenya in 2016. We capitalized on this third party intervention to evaluate its impact on porcine cysticercosis prevalence. Methods We conducted a comparative cross-sectional survey from August through to September 2021. Household selection was done using multistage sampling. Household questionnaire data on pig production, transmission, risk factors and awareness of porcine cysticercosis were collected from 251 households. Lingual palpation was used to test for cysticerci in 370 pigs while serum was tested for circulating antigen using Ag-ELISA. We compared results of our survey to an effective baseline, which was a near equivalent cross sectional survey conducted in 2012 before the third party sanitary intervention was established. The difference in prevalence was measured using Chi-square tests. Multivariable logistic regression analysis was used to identify risk factors for lingual cysts in pigs. Results The prevalence of palpable lingual cysts was estimated to be 3.8% (95% CI 2.3–6.3%) (14/370). This was 6% (95% CI 0.8–13.9%; p-value 0.0178) lower than the prevalence reported in the pre-implementation period of 9.7% (95% CI: 4.5–17.6%). Circulating antigen was detected in 2 samples (0.54%, 95% CI: 0.2–1.9). Latrine coverage was 86% (95% CI: 81–90%), which was 11% (95% CI: 4.8–16.8%; p < 0.001) higher than the pre-implementation period coverage of 75% (95% CI: 71–79%). There was reduced prevalence of lingual cysts in pigs from households that had a latrine (OR = 0.14; 95% CI: 0.05–0.43; p < 0.001) and where pigs were confined or tethered (OR = 0.27; 95% CI: 0.07–1.02; p = 0.053). Conclusion There was a reduction in the prevalence of porcine cysticercosis in Busia County over the study period from 2012 to 2021. This was not a trial design so we are unable to directly link the decline to a specific cause, but the data are consistent with previous research indicating that improved sanitation reduces porcine cysticercosis. Programs for controlling porcine cysticercosis should include a focus on sanitation in addition to other integrated One Health approaches.
Language of Legitimization in Political Discourse on Kashmir Issue

This study concerns the discursive strategies used in political discourse to legitimize conflicting positions on the Kashmir issue, a major issue between Pakistan and India. More specifically, the study has attempted to address the question of legitimization strategies and their linguistic realizations feature in the Pakistani and the Indian Prime Minister’s speeches after the abrogation of Article 370 about the Kashmir issue. The data consists of the speeches the Pakistani Prime Minister Imran Khan and the Indian Prime Minister Narendra Modi delivered after the abrogation of Article 370 on Kashmir. The whole research has been framed under the scope of Critical Discourse Analysis, and the speeches have been analyzed in terms of Reyes’ (2011) strategies of legitimization, and Halliday’s (2014) Transitivity Model. The data analysis reveals that both prime ministers use the strategies of emotion, hypothetical future, rationality, the voice of expertise, and altruism to justify their respective positions and to attack their opponents. Yet, they differ in the linguistic realizations of these strategies mainly due to their different mental models of the communicative event rooted in their differing ideological perspectives. The findings establish the significance of language as an analytical tool that can help understand the nature of discursive practices underlying certain ideologies.
Exploratory Inference Learning for Scribble Supervised Semantic Segmentation

Scribble supervised semantic segmentation has achieved great advances in pseudo label exploitation, yet suffers insufficient label exploration for the mass of unannotated regions. In this work, we propose a novel exploratory inference learning (EIL) framework, which facilitates efficient probing on unlabeled pixels and promotes selecting confident candidates for boosting the evolved segmentation. The exploration of unannotated regions is formulated as an iterative decision-making process, where a policy searcher learns to infer in the unknown space and the reward to the exploratory policy is based on a contrastive measurement of candidates. In particular, we devise the contrastive reward with the intra-class attraction and the inter-class repulsion in the feature space w.r. t the pseudo labels. The unlabeled exploration and the labeled exploitation are jointly balanced to improve the segmentation, and framed in a close-looping end-to-end network. Comprehensive evaluations on the benchmark datasets (PASCAL VOC 2012 and PASCAL Context) demonstrate the superiority of our proposed EIL when compared with other state-of-the-art methods for the scribble-supervised semantic segmentation problem.
Experimental Models of Traumatic Injuries: Do They Capture the Coagulopathy and Underlying Endotheliopathy Induced by Human Trauma?

Trauma-induced coagulopathy (TIC) is a major cause of morbidity and mortality in patients with traumatic injury. It describes the spectrum of coagulation abnormalities that occur because of the trauma itself and the body’s response to the trauma. These coagulation abnormalities range from hypocoagulability and hyperfibrinolysis, resulting in potentially fatal bleeding, in the early stages of trauma to hypercoagulability, leading to widespread clot formation, in the later stages. Pathological changes in the vascular endothelium and its regulation of haemostasis, a phenomenon known as the endotheliopathy of trauma (EoT), are thought to underlie TIC. Our understanding of EoT and its contribution to TIC remains in its infancy largely due to the scarcity of experimental research. This review discusses the mechanisms employed by the vascular endothelium to regulate haemostasis and their dysregulation following traumatic injury before providing an overview of the available experimental in vitro and in vivo models of trauma and their applicability for the study of the EoT and its contribution to TIC.
Effect of Red-Beetroot-Supplemented Diet on Gut Microbiota Composition and Metabolite Profile of Weaned Pigs—A Pilot Study

Simple Summary Weaning causes gut microbiota disruption that results in dysbiosis and post-weaning diarrhea. The recent ban on pharmacological doses of in-feed zinc oxide in the weaned pig diet has made exploration of alternative dietary supplements to improve the post-weaning condition of pigs imperative. Plants (e.g., red beetroot) containing bioactive compounds have shown great potential in this regard, favorably abating gut microbiota dysbiosis and promoting gut metabolite production and health. Abstract Red beetroot is a well-recognized and established source of bioactive compounds (e.g., betalains and polyphenols) with anti-inflammatory and antimicrobial properties. It is proposed as a potential alternative to zinc oxide with a focus on gut microbiota modulation and metabolite production. In this study, weaned pigs aged 28 days were fed either a control diet, a diet supplemented with zinc oxide (3000 mg/kg), or 2% and 4% pulverized whole red beetroot (CON, ZNO, RB2, and RB4; respectively) for 14 days. After pigs were euthanized, blood and digesta samples were collected for microbial composition and metabolite analyses. The results showed that the diet supplemented with red beetroot at 2% improved the gut microbial richness relative to other diets but marginally influenced the cecal microbial diversity compared to a zinc-oxide-supplemented diet. A further increase in red beetroot levels (4%—RB4) led to loss in cecal diversity and decreased short chain fatty acids and secondary bile acid concentrations. Also, an increased Proteobacteria abundance, presumably due to increased lactate/lactic-acid-producing bacteria was observed. In summary, red beetroot contains several components conceived to improve the gut microbiota and metabolite output of weaned pigs. Future studies investigating individual components of red beetroot will better elucidate their contributions to gut microbiota modulation and pig health.