Hasil untuk "q-bio"

Raffaele Pelorosso, Sergio Noce, Francesco Cappelli et al.

Scenario planning supports strategic decision-making under uncertainty by comparing multiple plausible futures. Impact indicators help to prioritize scenarios, while rank-based evaluations clearly communicate indicator relevance for participatory planning, policymaking, and resource allocation. Ensuring that rankings are both sensitive and robust is therefore essential. However, conventional statistical measures fail to fully capture ranking dynamics. They describe overall dispersion but cannot jointly assess the magnitude of rank shifts and the frequency with which items occupy specific ranks across scenarios. This study explores the novel application of Rao’s Quadratic Entropy (Rao’s Q) in scenario analysis to quantify ranking variability. A theoretical test demonstrates that Rao’s Q captures full variability in rankings and continuous values, suggesting it as a promising alternative to existing approaches. Rao’s Q is then applied to a climate change hotspot in Central Italy to evaluate changes in bio-energy landscape connectivity across forty-eight scenarios. Results reveal how land-use and climate changes affect landscape unit connectivity over time, identifying which are highly stable across scenarios or consistently critical, and thus highlighting planning priorities for mitigation, conservation, and sustainable urban development. Supported by openly available R code, this study demonstrates the relevance of Rao’s Q for participatory, scenario-based decision-making processes.

Mrinal Kanti Rajak, Rajen Pudur

Abstract This paper presents a novel Mitochondrial Energy Production Optimization (MEPO) algorithm for enhancing grid-connected inverter control under weak grid conditions. The proposed bio-inspired approach addresses critical challenges in maintaining power quality and system stability in low Short Circuit Ratio (SCR) environments while ensuring robust performance during grid disturbances. A comprehensive LCL filter design achieves $$-53.31~\text {dB}$$ magnitude attenuation with $$115.57^\circ$$ phase margin at the resonant frequency of $$100~\text {kHz}$$ , providing superior harmonic suppression. The MEPO controller demonstrates exceptional performance with current Total Harmonic Distortion (THD) of $$1.8\%$$ , significantly outperforming Particle Swarm Optimization ( $$2.5\%$$ ) and Genetic Algorithm ( $$2.7\%$$ ) approaches. Dynamic response tests confirm rapid settling times of $$2.5~\text {ms}$$ for current control and voltage regulation within $$\pm 1\%$$ , while maintaining a power factor of 0.998. Experimental validation on a $$10~\text {kW}$$ prototype verifies the algorithm’s effectiveness, achieving precise d-q axis current control with steady-state errors below $$0.5\%$$ and robust frequency tracking at $$49.9~\text {Hz}$$ . Rigorous statistical analysis across 100 independent trials validates the algorithm’s reliability with a $$95\%$$ success rate and $$43.2\%$$ faster convergence than conventional methods. The proposed MEPO solution represents a significant advancement in grid-connected inverter technology, particularly beneficial for renewable energy integration in weak grid environments.

Mustafa Bin Tariq, Hafiz Adnan Habib

Students are a gold asset for each country. Proper guidance/recommendation to the students regarding their education-related issues can ultimately result in uplifting the economy of a country. Different education models are followed in the world, out of which Outcome Based Education (OBE) is the one. OBE education model comprises three main components, which include Program Educational Objectives (PEOs), Program Learning Outcomes (PLOs), and Course Learning Outcomes (CLOs). CLOs are outcomes that a student achieves after studying a course. A single course may contain one or more CLOs. These CLOs are then mapped to PLOs and PLOs are then mapped to PEOs. Therefore, our objective in this work is to improve deficient/weak CLOs of students by suggesting online resources. Whereas, in the absence of this proposed system, students have to find out these resources by themselves or course teacher recommends relevant online resources. To achieve this objective, we created a dataset for the OBE education model, as to date no standard dataset exists on the OBE education model. From this dataset, we created a Student-to-CLO matrix and performed bi-clustering on this matrix to find groups of students having similar performance in different CLOs. So far, Bi-clustering has been used in the Bio-informatics field to determine similarity in gene expression data. Generated bi-clusters are sorted according to their homogeneity of contained values. These sorted bi-clusters are then mapped to a 2D grid to formulate a reinforcement-learning environment. The start state of the recommendation agent is determined using cosine similarity. If an agent visits a state, deficient CLOs of that state are recommended to the student. The agent can visit only those states that are nearby to its current state and accessible through its legal action space. An optimal sequence of actions to visit different states of a 2D grid, which can improve student’s performance, is determined using Q-learning. Online resources including research articles, YouTube videos, books, and online tutorials are suggested to the student to improve his deficient CLOs using a mobile app.

Anila Paul, Athira Ajayan, Abraham Joseph

Pueraria phaseoloides (PP), commonly known as tropical kudzu or puero, stands as an invasive leguminous vine native to Southeast Asia; yet recent studies unveil its promising potential in myriad applications beyond its weed-like reputation. Pueraria phaseoloides seed was extracted into powder form (PPS) was followed by a comprehensive characterization employing CHNS-O, UV-Visible, FTIR, SS NMR, and TGA analysis, while surface analysis via XPS and SEM unveiled the presence of polysaccharides and proteins, encompassing S-containing protein amino acids like cysteine. The corrosion studies of epoxy coatings formulated with PPS (PPE) in acidic and saline media tagged PPS as a laudable bio-filler. Pursuant to the gravimetric analysis, the optimum concentration for superior corrosion inhibition is found to be 0.3 wt% PPE. Tafel plots confirm the viable anticorrosive characteristics of 0.3 wt% PPE coating (97.62 % and 98.08 % in acidic and saline media respectively), which are validated by electrochemical impedance spectroscopy (98.75 % and 95.00 % in acidic and saline media respectively) employing the L(R(C(R(Q(R(LR)(CR))))) equivalent circuit model, with constant protection efficiency values across all techniques. Assessing the corrosion studies of PPE composite coating, turned the table of the invasive weed into a powerful corrosion deterrent.

H. B. Chethan, Nasser Bin Turki, D. G. Prakasha

Abstract Enzyme reactions have numerous applications in diverse disciplines of science like chemistry, biology and biomechanics. In this study, we examine the role and act of enzymes in chemical reactions which is considered in the frame of fractional order model. The proposed model includes system of four equations which are studied via Caputo fractional operator. The systems of non-linear equations are evaluated by a semi-analytical approach called $$q$$ q -homotopy analysis transform method. The uniqueness and existence of the solutions has been investigated through fixed point theorem. The solutions of the proposed model are achieved through the considered method and the obtained outcomes are in the form of series which shows rapid convergence. The solutions are computed and graphs are plotted for the obtained results using mathematica software. The achieved results by the proposed method are unique and illustrate the significant dynamics of the considered model via 3D plots and graphs. The results of this study demonstrate the importance and effectiveness of projected derivative and technique in the analysis of time dependent fractional mathematical models. This study also gives an idea to extend the applications of enzymatic reactions in drug development, bio mechanics, and chemical reactions in various cellular metabolisms. Also, enzymatic reactions have a vital role in the fields of the food industry for processing food, in biotechnology for the manufacture of biofuels, and in metabolic engineering to design metabolic pathways.

Yue Zheng, Yanyu Zhao, Junjun Xu et al.

Because of affections from fluctuation, the migration or reaction rate of bio-molecules is mainly related to the time-memory effect. This kinetic phenomenon is primarily dominated by dynamic ductility and molecular crowding in the solvent. These two important elements directly connect with the affections of the random force and systematic friction (ζ) in a real solvent. They can affect fluctuation characteristics of bio-molecules. Properties of bio-molecular kinetics are mainly submitted to the configuration quality and random collision. The multidimensional landscape must be needed in typical research processes for kinetics of bio-molecules. The random collision affection in the x dimension and the typical ductility for the free-energy surface in the Q dimension have been abstracted in our work. The two-dimensional generalized Langevin equation including fractional Gaussian noise or white noise is used to study the migration rate or the mean waiting time. The essential quality of the bio-molecules’ kinetic properties can be revealed by the comparative study between dynamic disorder (DD) and common diffusion. We have found that there are sharp dynamic differences between DD and normal kinetics. Moreover, dynamic ductility and solvent friction can lead to great affections to the bio-molecular dynamics.

Fabian Audu Ugbe, Gideon Adamu Shallangwa, Adamu Uzairu et al.

Abstract Background Leishmaniasis is a neglected tropical disease caused by a group of protozoan of the genus Leishmania and transmitted to humans majorly through the bite of the female sand fly. It is prevalent in the tropical regions of the world especially in Africa and estimated to affect a population of about 12 million people annually. This theoretical study was therefore conducted in support of the search for more effective drug candidates for the treatment of leishmaniasis. This study focuses on the in silico activity prediction of twenty-eight (28) maleimides, structure-based design, molecular docking study and pharmacokinetics analysis of the newly designed maleimides. All the studied compounds were drawn using ChemDraw Ultra and optimized by the density functional theory (DFT) approach using B3LYP with 6-31G⁄ basis set. Results The built QSAR model was found to satisfy the requirement of both internal and external validation tests for an acceptable QSAR model with R 2 = 0.801, R 2 adj = 0.748, Q 2 cv = 0.710, R 2 test = 0.892 and cR p 2 = 0.664 and has shown excellent prediction of the studied compounds. Among the five (5) protein receptors utilized for the virtual docking screening, pyridoxal kinase (PdxK) receptor (Pdb id = 6k91) showed the strongest binding interactions with compounds 14, 21 and 24 with the highest binding affinities of − 7.7, − 7.7 and − 7.8 kcal/mol, respectively. The selected templates (14, 21 and 24) were used to design twelve (12) new compounds (N1–N12) with higher docking scores than the templates. N7 (affinity =  − 8.9 kcal/mol) and N12 (− 8.5 kcal/mol) showed higher binding scores than the reference drug pentamidine (− 8.10 kcal/mol), while N3 and N7–N12 showed higher predicted pIC50 than the templates. Also, the pharmacokinetics properties prediction revealed that the newly designed compounds, obeyed the Lipinski’s rule for oral bio-availability, showed high human intestinal absorption (HIA), low synthetic accessibility score, CNS and BBB permeability and were pharmacologically active. Conclusions The activities of the various maleimides were predicted excellently by the built QSAR model. Based on the pharmacokinetics and molecular docking studies therefore, the newly designed compounds are suggested for further practical evaluation and/or validation as potential drug candidates for the treatment of leishmaniasis.

Nargis Nazir, Zaffar Afroz Badri, Nazir Ahmad Bhat et al.

Abstract Root rot of pea caused by Fusarium spp. is one of the important diseases of pea (Pisum sativum L.). The causal fungus of the disease isolated from naturally infected pea plants was identified as Fusarium solani f. sp. pisi (Jones). Evaluation of four bio agents and nine fungicides was done in vitro against Fusarium solani. Trichoderma harzianum was the most effective bio agent in inhibiting the mycelial growth of F. solani by (82.62%). Carbendazim 50 WP was the most effective fungicide in inhibiting the mycelial growth of F. solani by (91.06%). Carbendazim at the rate of 0.1% and T. harzianum at concentration of 109 cfu when used as seed treatment under field conditions were evaluated along with three planting techniques v.i.z, raised beds, ridges and flat beds. It was found that Carbendazim at the rate of 0.1% when given as seed treatment in raised beds exhibited the lowest disease incidence (10.97%), intensity (2.89%) and the maximum pod yield (89.63 q ha−1) as compared to control.

Mohammad Azam, Mohammad Rizwan Khan, Saikh Mohammad Wabaidur et al.

Lead (Pb(II)), an extremely hazardous heavy metal that has been shown to have detrimental effects on both the environment and humans, mostly gets into the ecosystem through industrial activities. In this work, a new solid-phase extraction (SPE) based on treated date pits bio-sorbent and iCAP Q inductively-coupled plasma mass spectrometry (iCAP Q ICP/MS) method has been optimized for the trace determination of Pb(II) in various industrial wastewater effluents. A cost-effective biomass material was prepared from date pits (DP), and chemically modified with H2O2 and successively used as SPE bio-sorbent for Pb(II) extraction. Extracting solutions for instance H2SO4, HNO3 and HCl at various concentrations (1–5 mM) were optimized, and best extraction of Pb(II) was obtained by HCl (1 mM). The optimized SPE and iCAP Q ICP/MS method has offered excellent validation conditions in terms of coefficient of determination (CoD, R2 > 0.999), detection limit (DL, 0.011 µg/L), quantification limit (QL, 0.034 µg/L), and run-to-run and day-to-day precision (RSD < 6 %). The optimized procedure was practically applied in the determination of Pb(II) in industrial wastewater comprising iron and steel, textile, printing and battery industries. Among the analyzed samples, the battery industry produced higher amounts of Pb(II) (18.55 µg/L) followed by iron and steel (14.65 µg/L), petroleum (12.38 µg/L) printing (5.78 µg/L) and textile (3.76 µg/L) industries. The recovery values were achieved between 95 % and 99 %. The obtained results have established the appropriateness of the offered technique as a new useful method for the routine examination of Pb(II) in industrial wastes. In addition, the current method could be expansively used in the proficient removal and identification of other heavy metals contaminants from similar matrices. Further, the metal ions saturated bio-sorbents were used in the preparations of bricks and it was found to be a successful approach for heavy metals and agricultural waste management.

Qiuyun Fan, Cornelius Eichner, Maryam Afzali et al.

Tremendous efforts have been made in the last decade to advance cutting-edge MRI technology in pursuit of mapping structural connectivity in the living human brain with unprecedented sensitivity and speed. The first Connectom 3T MRI scanner equipped with a 300 mT/m whole-body gradient system was installed at the Massachusetts General Hospital in 2011 and was specifically constructed as part of the Human Connectome Project. Since that time, numerous technological advances have been made to enable the broader use of the Connectom high gradient system for diffusion tractography and tissue microstructure studies and leverage its unique advantages and sensitivity to resolving macroscopic and microscopic structural information in neural tissue for clinical and neuroscientific studies. The goal of this review article is to summarize the technical developments that have emerged in the last decade to support and promote large-scale and scientific studies of the human brain using the Connectom scanner. We provide a brief historical perspective on the development of Connectom gradient technology and the efforts that led to the installation of three other Connectom 3T MRI scanners worldwide – one in the United Kingdom in Cardiff, Wales, another in continental Europe in Leipzig, Germany, and the latest in Asia in Shanghai, China. We summarize the key developments in gradient hardware and image acquisition technology that have formed the backbone of Connectom-related research efforts, including the rich array of high-sensitivity receiver coils, pulse sequences, image artifact correction strategies and data preprocessing methods needed to optimize the quality of high-gradient strength diffusion MRI data for subsequent analyses. Finally, we review the scientific impact of the Connectom MRI scanner, including advances in diffusion tractography, tissue microstructural imaging, ex vivo validation, and clinical investigations that have been enabled by Connectom technology. We conclude with brief insights into the unique value of strong gradients for diffusion MRI and where the field is headed in the coming years.

Joseph Gatto, Parker Seegmiller, Garrett Johnston et al.

BackgroundTriage of textual telemedical queries is a safety-critical task for medical service providers with limited remote health resources. The prioritization of patient queries containing medically severe text is necessary to optimize resource usage and provide care to those with time-sensitive needs. ObjectiveWe aim to evaluate the effectiveness of transfer learning solutions on the task of telemedical triage and provide a thorough error analysis, identifying telemedical queries that challenge state-of-the-art natural language processing (NLP) systems. Additionally, we aim to provide a publicly available telemedical query data set with labels for severity classification for telemedical triage of respiratory issues. MethodsWe annotated 573 medical queries from 3 online health platforms: HealthTap, HealthcareMagic, and iCliniq. We then evaluated 6 transfer learning solutions utilizing various text-embedding strategies. Specifically, we first established a baseline using a lexical classification model with term frequency–inverse document frequency (TF-IDF) features. Next, we investigated the effectiveness of global vectors for text representation (GloVe), a pretrained word-embedding method. We evaluated the performance of GloVe embeddings in the context of support vector machines (SVMs), bidirectional long short-term memory (bi-LSTM) networks, and hierarchical attention networks (HANs). Finally, we evaluated the performance of contextual text embeddings using transformer-based architectures. Specifically, we evaluated bidirectional encoder representation from transformers (BERT), Bio+Clinical-BERT, and Sentence-BERT (SBERT) on the telemedical triage task. ResultsWe found that a simple lexical model achieved a mean F1 score of 0.865 (SD 0.048) on the telemedical triage task. GloVe-based models using SVMs, HANs, and bi-LSTMs achieved a 0.8-, 1.5-, and 2.1-point increase in the F1 score, respectively. Transformer-based models, such as BERT, Bio+Clinical-BERT, and SBERT, achieved a mean F1 score of 0.914 (SD 0.034), 0.904 (SD 0.041), and 0.917 (SD 0.037), respectively. The highest-performing model, SBERT, provided a statistically significant improvement compared to all GloVe-based and lexical baselines. However, no statistical significance was found when comparing transformer-based models. Furthermore, our error analysis revealed highly challenging query types, including those with complex negations, temporal relationships, and patient intents. ConclusionsWe showed that state-of-the-art transfer learning techniques work well on the telemedical triage task, providing significant performance increase over lexical models. Additionally, we released a public telemedical triage data set using labeled questions from online medical question-and-answer (Q&A) platforms. Our analysis highlights various avenues for future works that explicitly model such query challenges.

C. Raju, G. R. Babu, S. M. et al.

Background: The accurate and efficient diagnosis at the early stages of cancers is the key feature for effective treatment and productive research for finding out news to types of cancers. It is essentially true for cancers, where there is no effective cure, but only one treatment is available. But most people have a combination of treatments, such as surgery with chemotherapy or radiation therapy or immunotherapy or targeted therapy or hormone therapy.Cancers symptoms of abnormal periods or pelvic pain, changes in bathroom habits, bloating, breast changes, chronic coughing, chronic headache, difficulty swallowing, excessing bruising. Despite the fact of having great need, the current availability of diagnostic tests is unable to diagnose different forms of cancers. Aim: The aim of the review is to explore the application of GC-MS, LC-MS and UP-LC/Q-TOF MS for the evaluation of changes in the biochemical composition of blood serum, urine and saliva. The power of high differentiation method will promote the translation of hyphenated techniques from a laboratory to clinical useful tool. Determination of biochemical information derives from hyphenated techniques from blood, serum, saliva and urine that will yield accurate and selective detection of cancer disorders. They will also provide diagnostic and prognostic indicators and will also play a significant role in the development of personalized medicine. Conclusion: Hyphenated techniques will allow differentiating blood serum, saliva and urine samples of common cancer disorders from normal control patients with sensitivity and specificity.

Quintín Rascón-Cruz, Carmen Daniela González-Barriga, Blanca Flor Iglesias-Figueroa et al.

Chloroplast biotechnology has emerged as a promissory platform for the development of modified plants to express products aimed mainly at the pharmaceutical, agricultural, and energy industries. This technology’s high value is due to its high capacity for the mass production of proteins. Moreover, the interest in chloroplasts has increased because of the possibility of expressing multiple genes in a single transformation event without the risk of epigenetic effects. Although this technology solves several problems caused by nuclear genetic engineering, such as turning plants into safe bio-factories, some issues must still be addressed in relation to the optimization of regulatory regions for efficient gene expression, cereal transformation, gene expression in non-green tissues, and low transformation efficiency. In this article, we provide information on the transformation of plastids and discuss the most recent achievements in chloroplast bioengineering and its impact on the biopharmaceutical and agricultural industries; we also discuss new tools that can be used to solve current challenges for their successful establishment in recalcitrant crops such as monocots.How to cite: Quintín Rascón-Cruz Q, González-Barriga CD, Iglesias-Figueroa BF, et al. Plastid transformation: Advances and challenges for its implementation in agricultural crops. Electron J Biotechnol 2021;51. https://doi.org/10.1016/j.ejbt.2021.03.005

NT DileepKumar, M. Mohan

Alfred Mitema, Naser Aliye Feto, M. S. Rafudeen

ABSTRACT Some secondary metabolites produced by fungi are carcinogenic, hepatotoxic, and/or cause birth defects in humans and animals. We developed and optimised bio-analytical tools for detection of metabolites, aflatoxins and evaluated the effectiveness of the methods in co-infected maize tissues. Isolate KSM012 (atoxigenic) demonstrated no peaks and no blue fluorescence on HPLC and TLC plates respectively confirming non-toxicity. AFB1 and AFB2 were produced by Isolate KSM015 in addition to AFG1 and AFG2, which is an indication of possible SBG morphotype. The limits of quantification and detection ranged from 0.02 to 35.81 µg/mL and 0.01–6.8 µg/mL, respectively. The best mass spectrum with lowest noise was obtained at 100% ACN and sterile water spiked with 0.1% formic acid at a flow rate of 0.3 mL/min. The positive ion mode with electrospray ionisation application exhibited better fragmentation for mycotoxins. In total 17 metabolites were detected by targeted and formula mass. KDVI maize line exhibited high fungal colonisation in comparison to GAF4 at equal co-infection ratio 50:50. AFB1 and AFG2 were remarkably higher in GAF4 in comparison to sensitive KDV1 (p ˂ 0.05). The detection limits, linearity and sensitivity showed the method developed was suitable for the determination of mycotoxin in comparisons to the guidelines of European Commission 657/EC 2002.

W. El-Menhawey, S. Kholeif, Rehab Elshanawany et al.

Abstract The assemblages of benthic foraminifera were studied in surface sediment samples collected along two transects from the mangrove swamp and the intertidal flat zone in Abu Ghoson area, the Red Sea coast of Egypt, to validate and support their use as bio-indicators of ecosystem quality. Using Q-mode and R-mode cluster analyses, three biotopes following the bathymetric and environmental gradients have been documented. The seaward intertidal flat stations were dominated by larger symbiont-bearing foraminifera (Peneroplis planatus, Peneroplis pertusus, Sorites orbiculus, Coscinospira spp., and Amphisorous spp.). This biotope reflects the oligotrophic environment. Assemblage of smaller miliolids and rotaliids is diversified and characterized the swamp stations and the closest intertidal stations. The assemblage from the most landward semi-closed swamp station was distinguished by stress-tolerant taxa, especially Ammonia tepida, found in high percentages, though relatively low diversity.

M.S.A. Fouzi, Manjula Thimma, Mohammad BinSabt et al.

BACKGROUND: Merging stem cells with biomimetic materials represent an attractive approach to tissue engineering. The development of an alternative scaffold with the ability to mimic the extracellular matrix, and the 3D gradient preventing any alteration in cell metabolism or in their gene expression patterns, would have many medical applications. OBJECTIVE: In this study, we introduced the use of RGD (Arg-Gly-Asp) bio-conjugated cotton to promote the growth and proliferation of mesenchymal stem cells (MSCs). METHODS: We measured the expression of stem cell markers and adhesion markers with Q-PCR and analyzed the transcriptomic. The results obtained showed that the MSCs, when cultured with bio-conjugated cotton fibers, form aggregates around the fibers while proliferating. The seeded MSCs with cotton fibers proliferated in a similar fashion to the cells seeded on the monolayer (population doubling level 1.88 and 2.19 respectively). RESULTS: The whole genome sequencing of cells adhering to these cotton fibers and cells adhering to the cell culture dish showed differently expressed genes and pathways in both populations. However, the expression of the stem cell markers (Oct4, cKit, CD105) and cell adhesion markers (CD29, HSPG2 and CD138), when examined with quantitative RT-PCR, was maintained in both cell populations. CONCLUSION: These results clearly show the ability of the cotton fibers to promote MSCs growth and proliferation in a 3D structure mimicking the in vivo environment without losing their stem cell phenotype.

B. S. Thapa, T. Chandra

A. Mahdi, Marwan M. A. Rashed, Waleed Al-Ansi et al.

This study mainly aimed to optimize a sustainable and green process for extracting bioactive compounds from Foshou fruit by using an integrated technique based on ultrasonic-microwave assisted extraction (UMAE). Response surface methodology (RSM) based on a Box–Behnken design was applied to determine optimal conditions. The following optimized UMAE processing parameters were obtained: sonication time (96.13 s), microwave power (305.28 W), and solid/solvent ratio (1:37). Based on a total phenolic compound extraction yield of 9.21 mg gallic acid (GA) equ/g dry weight (DW), a 2,2-diphenyl-1-picrylhydrazyl (DPPH) scavenging activity with a half maximal inhibitory concentration (IC50) of 27.52 μg GA equ, and an antioxidant capacity detected by 2,2′-azino-bis-3-ethylbenzthiazoline-6-sulphonic acid (ABTS) assay of 8.79 mg trolox equ/g DW. The optimized UMAE extract was superior to those obtained using microwave-assisted extraction (MAE) or conventional solvent extraction (CSE) methods. Scanning electron microscopy (SEM) analysis showed that the three extraction methods affected the sample tissue microstructure. Among them, UMAE caused the most marked structural disruption. UPLC-PDA-Q-TOF-MS analysis identified 67 phenolic compounds in the optimized UMAE extract of the Foshou fruit extract. This study indicated that the integrated UMAE technique is a suitable and safe technique to enhance the qualitative and quantitative extraction of phenolic compounds from Foshou fruit. These phenolic compounds can be used as a functional food ingredient in industrial production.Graphical abstract

F. Filho, J. A. L. Cruz, G. Zebende

Abstract The process of reading a specific text is considered complex and little known in neuroscience, since it involves the vision, memory, motor control, learning, among others. In this sense, an excellent possibility to study the brain activity in the reading task can be achieved by the analysis of the multi-channel Electroencephalogram (EEG) and also with new statistical methods, like the detrended fluctuation analysis method (DFA). In this paper it will be proposed a model to analyze the brain activity in the reading task, performed by two subjects using a 22-channels EEG (NEUROMAP® model E Q S A 260 ). In order to test our model, two adults subjects (graduates) were tested here. These subjects were arranged in a chair facing a panel with the specific text, excluding involuntary movements that activated regions of the brain that were not being stimulated by reading. For the first subject, chosen at random, the text was presented before the task for understanding and some memorization. For the other subject the text was presented at the time of task. For the signal processing we chose 11 bio-electrodes located at the frontal, parietal, temporal and occipital regions of the brain. Therefore, to treat these non-stationary bio-signals we must apply robust and modern statistical techniques. With this objective, DFA method was applied in order to analyze the F D F A ( n ) fluctuation function in multi-channel EEG bio-sensors, more specifically the difference of its logarithm, i.e., Δ l o g F D F A . The results show that the use of this new function can be useful for brain activities. This paper, as we shall see here, is an initial contribution for EEG data analyze, that would be of medical interest, mainly in neuroscience area.