Stability Index Research Articles

Optimization of Fermentation Process of Zanthoxylum bungeanum Seeds and Evaluation of Acute Toxicity of Protein Extract in Mice

The seeds of Zanthoxylum bungeanum seeds, a high-quality vegetable protein source, encounter application limitations due to their high molecular weight and anti-nutritional factors. This study focused on optimizing the fermentation process by investigating key parameters such as inoculation amount, inoculation ratio, material-to-liquid ratio, fermentation temperature, and fermentation time. Both single-factor experiments and response surface methodology were used to determine the optimal conditions. The effects of fermentation on particle size, surface morphology (scanning electron microscopy), water holding capacity, oil holding capacity, solubility, and emulsification properties of Zanthoxylum bungeanum seed protein were analyzed. In addition, acute toxicity was investigated at doses of 1.5 g/kg, 3 g/kg, 6 g/kg, and 12 g/kg. The results showed that the optimal fermentation conditions were an inoculum concentration of 10%, a ratio of Bacillus subtilis to Lactobacillus plantarum of 1:1, a material-to-liquid ratio of 0.8:1, a temperature of 35 °C, and a fermentation period of 4 days. Under these optimized conditions, the soluble protein content reached 153.1 mg/g. After fermentation, the functional properties of Zanthoxylum bungeanum seed protein improved significantly: the water holding capacity increased by 89%, the oil holding capacity by 68%, while the emulsifying activity and stability indices improved by 6% and 17%, respectively. The macromolecular proteins in the seeds of Zanthoxylum bungeanum were effectively broken down into smaller fragments during fermentation, resulting in a more folded and porous surface structure. In acute toxicity tests, all mice treated with fermented Zanthoxum seed protein survived for more than 7 days after injection, and there were no significant differences in body weight, organ index, and hematological tests between groups, but FZBSP of 1.5 g/kg~12 g/kg caused varying degrees of steatosis and inflammatory damage in the heart and liver. In conclusion, this study confirms that follow-up pilot studies using 1.5 g/kg FZBSP have the potential for further development and utilization.

Physiological and Yield Responses of Indian Mustard (Brassica juncea) to Terminal Heat Stress

In present investigation we studied the influence of terminal heat stress on several agronomic, physiological and yield-related variables in 10 mustard genotypes; Advance-414, Anmol, Bond, Coral-432, JKMS 8532, MRR-8030, NMS-2018, Rajshree, RH-30 and Sonalika. The experiment conducted under control condition (Sown in October) and heat stressed environment (Sown in November) to assess the role of ambient and high temperatures, respectively. Different characteristics including relative water content (RWC), water saturation deficit (WSD), relative dry weight (RDW), membrane stability index (MSI), days to flowering, plant height and yield attributes were analysed in respect to heat stress. The results demonstrated strong relationship between genotype and treatment in responses to heat stress. In terms of RWC, RH-30 maintained high value in both normal (95.17 ± 0.991%) and late sown (72.78 ± 1.022%) circumstances, but Coral-432 showed sensitivity to stress conditions with reduction in relative water content ranging from 80.91±0.085% in control environment to 51.30±0.988% in late sown condition. Heat stress significantly raised water saturation deficit in all genotypes, with RH-30 retaining lower WSD (4.83 ± 0.083%; control and 27.22±0.595% heat stress) than Coral-432 (19.08 ± 0.467% control and 48.70 ± 0.179% heat stress) whereas membrane stability index ranged from 5.03 ± 0.033% to18.03 ± 0.176%. Yield attributes such as seed yield per plant, test weight drastically reduced under heat stress whereas, genotype RH-30 showed resistance to stress and highest in seed yield (14.22 ± 0.215 g) and 1000-seed weight (test weight; 4.35 ± 0.066 g) under stress. Plant height and number of branches also showed similar reduction in respect to heat stress. Overall, genotypes RH-30 and Rajshree found superior to stress tolerance in all tested parameters and further used in the breeding programme to develop the heat resilience cultivar in mustard.

Impact of Neem-Coated Urea on NO₃-N and NH₄-N Availability and Growth Performance of Maize in Saline and Non-Saline Soils

This study investigates the effects of neem-coated granular urea on nitrogen volatilization and leaching in maize (Zea mays L.), focusing on nutrient availability (NO3-N and NH4-N) in both normal and saline soils. The pot experiment was conducted in a glass-panelled wire house CRD design with three replications. The experimental treatments included T1 (control without fertilizer), T2 (0.05 % neem-coated granular urea @ 200 kg ha⁻¹ + recommended P and K), T3 (0.08 % neem-coated granular urea @ 200 kg ha⁻1 + recommended P and K), T4 (0.01 % neem-coated granular urea @ 200 kg ha-1 + recommended P and K), and T5 (recommended NPK: 200 kg N ha⁻¹, 90 kg P₂O₅ ha⁻¹, and 60 kg K₂O ha⁻¹). Soil samples were taken prior to planting, one month later, and following harvest in order to examine key chemical components. The results demonstrated that maize growth and nutrient uptake were significantly enhanced by T3 (0.08 % neem-coated urea). Under T3, there was an increase of 34.32 % in shoot length, 50.48 % in fresh weight, and 22.40 % in dry weight. There were notable increases in root length, fresh weight, and dry weight of 36.68 %, 21.32 %, and 46.53 %, respectively. Additionally, in comparison to the control, the T3 treatment increased the plant membrane stability index (MSI), chlorophyll content, and nitrate retention by 21.32 %, 22.13 %, and 17.29 %, respectively. Treatment T3 enhanced potassium content, phosphorus absorption, and nitrogen concentration. According to data, applying 0.08 % neem-coated urea along with recommended levels of potassium and phosphate enhances maize growth, and overall crop productivity. This makes it a feasible substitute for long-term and effective fertilizer application in both normal and salinized soils.

Assessment of AMMI model for delineating the stability indices of high yielding variety of Java Citronella (Jor Lab C-5) evaluated in different location of NE India

An industrially important plant, Cymbopogon winterianus Jowitt ex Bor commonly known as Java Citronella belonging to Poaceae family gains its significance due to the presence of aromatic constituents and its capacity to yield a high quantity of essential oil. However, due to varied agronomic and climatic conditions, fluctuations in the chemical constituents and essential oil yield can be noticed. However, till now studies on stability analysis of Citronella are very scarce. Focusing the crop’s exceptional oil-yielding capacity and its high importance in industrial purposes extensive commercial cultivation of superior variety of Citronella is need of the hour. Hence, a study was conducted to establish a stable genotype of Java citronella where Jor Lab C-5 was taken to test the stability along with two check genotypes (Jor lab C-2 and Assam local). For two years (2021-2022 and 2022-2023) six agronomical traits were constantly studied with two sets of environmental factors for the eight different locations in a randomized block design. The Analysis of variance (ANOVA) by regression method revealed herbage recovery rate and essential oil yield as extensively high for Jor Lab C-5 as compared to the other two genotypes. Further, AMMI (Additive Main-effects and Multiplicative Interactions) ANOVA was used for the confirmation of uniform performance of various characters where Jor Lab C-5 was found to be stable in case of plant height, herbage yield, essential oil yield, citronellal content, and total essential oil yield. The GC-MS analysis of essential oil revealed 19 compounds with area percent 94.28% of which citronellal (42.52%) outcomes as major constituent. Additionally, environment such as Runne, Khehoyi, Yaongyimsen, and Jorhat were considered as the best suited locations for Jor Lab C-5, thus highlighting its multi-location stability and its potential industrial significance in the long run.

State Machine and Internal Model Control-based Hybrid Controller for Improved Transient Performance of Microgrids

The transient performance of microgrids is measured by their transient stability and transient response indices. The quality of these indices depends upon the design of the microgrid’s closed-loop control scheme, which is a cascaded combination of outer power controller and inner voltage-current (VA) controllers. Generally, the power controller is realized by droop control logic (fixed droop or adaptive droop), and VA controllers by conventional proportional-integral (PI) control. Control schemes with fixed droop coefficient logic and PI-based VA controllers suffer from stability and response issues. In this scheme, when these PI-based VA controllers are replaced with internal model control (IMC) based VA controllers, the response aspect is improved, while the stability aspect shows no improvement. Therefore, when fixed droop logic is replaced with adaptive droop control logic, stability is improved. However, adaptive droop coefficient schemes with PI-based VA controllers provide a limited improvement in stability. Moreover, conventional machine learning-based adaptive droop coefficient logic suffers from severe computational difficulties. It is verified in this work that IMC-based VA controllers which cannot improve stability with fixed droop logic, will contribute to stability enhancement when a suitable adaptive droop control logic is deployed. Therefore, to enhance both stability and response aspects with reduced computational effort, this paper proposes a hybrid control scheme made of a state machine-based droop controller (SMD) supported by IMC-based VA controllers. From the simulation results, while the conventional schemes could not withstand load power factors lesser than 0.707, the proposed hybrid controller scheme maintained stability at a power factor of 0.47 with a total harmonic distortion of less than 5%.

Application of monarch butterfly optimization algorithm for solving optimal power flow

This paper proposes a highly flexible, robust, and efficient constraint-handling approach for the solution of the optimal power flow (OPF) problem and this solution lies in the ability to solve the power system problem and avoid the mathematical traps. Centralized control of the power system has become inevitable, in the interest of secure, reliable, and economic operation of the system. In this work, OPF is solved by considering the three distinct objectives, generation cost minimization, power loss minimization, and enhancement of voltage stability index. These three objectives are solved separately by considering the evolutionary-based monarch butterfly optimization (MBO) algorithm. This MBO algorithm is validated on the IEEE 30 bus network and the obtained results are compared with differential evolution, particle swarm optimization, genetic algorithm, and Jaya algorithm. The obtained results reveal that among the various optimization algorithms considered in this work, the MBO evolves as the best algorithm for all three case studies.

Impacts of electric vehicle charging stations and DGs on RDS for improving voltage stability using honey badger algorithm

The intelligent computational technique used in this research handles the multi-objective voltage stability optimization (MOVSO) problem in radial distribution systems (RDS). The objectives of the proposed research are to minimize network loss, lower the average voltage deviation index (AVDI), and improve the voltage stability index (VSI) of RDS by taking into account the recently created distributed generators (DGs) and electric vehicle charging stations (EVCSs). To address the MOVSO problem, a novel and innovative honey badger algorithm (HBA) optimization technique is put forth. The two stages of HBA, known as the "digging" and "honey" phases, are responsible for effectively identifying the ideal position and appropriate quantity of EVCSs and DGs. The standard IEEE 33 node test system with different case studies is considered to validate the performance of HBA. The simulation results of improved voltage profile, minimized power loss, AVDI and improved VSI are tabulated. The proposed HBA fine-tunes the ideal position and size of the EVCSs to significantly enhance RDS performance under higher loading circumstances. To demonstrate the efficacy and originality of the suggested HBA, the numerical results are contrasted with those of earlier soft computing techniques.

Optimizing Sorghum for California: A Multi-Location Evaluation of Biomass Yield, Feed Quality, and Biofuel Feedstock Potential

Sorghum cultivars, particularly those used for forage and biomass, present significant potential as drought-resistant crops suitable for animal feed and biofuel production. This study evaluated 59 sorghum hybrids over five years (2019–2023) across three University of California research farm locations in the Central Valley: Kearney REC (KARE), West Side REC (WSREC), and Davis. The primary aim was to identify genotypes that exhibit high yield and stability across diverse environments in California, which is crucial for meeting the state’s significant feed needs associated with dairy operations and animal production. The evaluation focused on biomass yields, forage quality traits such as Relative Feed Quality (RFQ) and milk yield per ton (milk/ton), and biofuel-relevant chemical compositions like Neutral Detergent Fiber (NDF) and starch. A multi-trait stability index was employed to pinpoint superior genotypes that combine high yield with desirable quality traits. Results indicated significant genotypic, environmental, and genotype-by-environment (GxE) interaction effects for all traits except fat and water-soluble sugars. Eight hybrids were notable for maintaining high and stable biomass yields across different locations. Additionally, high fat and starch content were found to correlate with improved milk/ton potential, while lower fiber content (ADF, NDF) was associated with enhanced RFQ. Specifically, nine hybrids were identified as optimal for dairy forage due to their combination of high yield, RFQ, and milk/ton. Furthermore, distinct hybrids were identified for first-generation (starch-based) and second-generation (NDF-based) biofuel strategies. Three hybrids stood out as having desirable traits for both feed and biofuel applications, underscoring their versatility. This study highlights the utility of a multi-trait stability index in selecting superior sorghum genotypes for specific trait combinations. The identified candidates for forage and biofuel use, especially the multipurpose varieties, offer valuable insights that can aid growers and industry stakeholders in developing more sustainable and versatile sorghum production systems in California. Findings from this study contribute significantly to the development of more resilient sorghum production systems. By identifying hybrids that excel in both yield and quality across various environments, this research supports future cropping decisions aimed at enhancing water use efficiency and drought resilience in sorghum cultivation. These advancements are crucial for maintaining competitive dairy operations and advancing biofuel production in the face of climate change-induced challenges.

Effect of high-pressure homogenization optimized by response surface methodology on the techno-functional properties of protein concentrate isolated from date seed

The study investigates the impact of high-pressure homogenization (HPH) optimized using response surface methodology (RSM) on the techno-functional properties of protein concentrate isolated from date seeds. The protein concentrate was subjected to HPH at various pressures (50, 100, and 150 MPa) and protein concentrations (1 %, 2 %, and 3 %) to optimize solubility, emulsifying activity, and antioxidant properties. RSM indicated optimal conditions at 150 MPa and 1 % protein concentration, resulting in significant enhancements in solubility (14.10 % to 43.69 %) and antioxidant activity (60.5 TE/g to 71.67 TE/g). The emulsifying activity index (EAI) increased from 11.92 m²/g to 22.29 m²/g, though the emulsion stability index (ESI) slightly decreased from 17.63 min to 16.15 min. Besides, HPH improved oil-binding capacity (1.73 g/g to 3.02 g/g) while reducing water-binding capacity (2.76 g/g to 1.38 g/g). Structural analysis revealed that HPH caused partial protein unfolding and aggregation, indicated by changes in FTIR spectra, reduced fluorescence intensity, and increased surface sulfhydryl content (1.58 µmol/g to 2.65 µmol/g). These findings highlight HPH as an effective method to enhance the functional properties of date seed protein concentrate for potential applications in the food industry. In addition, the current study can lay a foundation for future HPH applications in other protein-rich by-products such as soybean cake, rapeseed cake, wheat bran, and others.

An intelligent transformer enabled medium voltage AC network for loss minimization and node voltage improvement

Abstract The research work presented here discusses about design and integration of intelligent transformer (IT) to the 15 kV/0.4 kV overloaded distribution feeder in Wolaita Sodo Town. The feeder contains 113 distribution transformers with different capacities ranging from 50 kVA to 1250 kVA. The proposed intelligent transformer is a three-stage modular type using phase shift multicarrier modulations for MMC front end converter. Its middle stage is dual active bridge having input series output parallel (DAB-ISOP) configuration using a phase shift modulation. The smart transformer’s back end uses an MMC inverter using interleaved phase shift modulation. The distribution feeder is modeled in MATLAB/Simulink and the designed intelligent transformer is allocated to it using voltage stability index (VSI). The peak load data, feeder data and transformer data of the distribution system under study are obtained from the utility office. The existing distribution feeder’s performance was evaluated by using backward-forward sweep load flow simulation for peak loading condition. The line flows and voltage profile at all nodes were observed and candidate nodes for enhancement were identified. Placement of modular intelligent transformer by using voltage stability index (VSI) was conducted to improve the voltage profiles, minimize reactive power flows and losses. Based on the simulation results for base case scenario, total power loss of 936.5 kW is obtained. The minimum node voltage of 0.81PU and maximum reactive power flow of 10.9MVAr were observed for the base case simulation. Placement of intelligent transformer at weak node 67 and node 111 improves the node voltages to have a minimum value 0.965 PU and maximum value of 1.05PU. The total power loss is reduced to 511.5 kW (54.5% improvement) after integration of intelligent transformer

Impact of investment climate on foreign direct investment in Nigeria, Ghana, Kenya and South Africa,

The study examined the Impact of Investment Climate on Foreign Direct Investment in Nigeria, Ghana, Kenya and South Africa, for the period of 2000 to 2021. The focus of this study is on how the business environment in Nigeria, Ghana, Kenya and South Africa influences foreign direct investment. Specific goals are as follows: (i). Evaluate critically the effect of the economic investment climate in Nigeria, Ghana, Kenya and South Africa on the inflow of FDI The variable scope include economic investment climate (ease of doing business index, gross domestic product, inflation rate), political investment climate (political stability index, corruption perception index, quality of institutions), environmental investment climate (nitrous-oxide emission, population density, land/air pollution rate) as the independent variable. The dependent variable was foreign direct investment inflows. Time series analysis, and more specifically the multiple panel regression analysis method, was used in analyzing the data adopting the Cobb Douglass model for its theoretical framework and data was sourced from the Statistical Bulletin of the countries studied and the World Bank Statistics.\The results show that, Economic investment climate variable (GDP) had significant positive effect on the inflow of foreign direct investment into Nigeria, Ghana, Kenya and South Africa. While inflation have positive insignificant relationship with FDI; It was recommended that; Efforts should be made by the governments of Nigeria, Ghana, Kenya and South Africa to enhance their economic fortunes by strengthening their economy through engaging in massive production for exports which will boost economic growth and as well attract more foreign direct investment

Tokenization Stability Index: A Catalyst for Optimizing Transformer Models for Low Resource Languages

Tokenization Stability Index: A Catalyst for Optimizing Transformer Models for Low Resource Languages

Analytical hierarchy process based stability assessment of soil nailed structures

ABSTRACT In practice the preliminary design of routine soil nailed structures is usually based on thumb rules derived from existing knowledge and local experiences. In such a scenario, judgement of project engineer is crucial in assessing the stability of the constructed structure. In the present study, the Analytical Hierarchy Process (AHP) is utilized to assess the influence of seven key design factors on the prominent failure modes of soil nailed structures. AHP is a multi-criteria decision-making process, wherein, pairwise comparisons among all influencing criteria and among different alternatives with respect to each criterion are made. The responses required to constitute pairwise comparison matrices are obtained by performing a limit equilibrium-based parametric analysis. Based on the AHP analysis, nail spacing & soil friction angle are found to be the most influencing variables to overall stability. Further, the study also proposes a parameter Composite Stability Index (CSI) for soil nailing design optimization.

Factors governing crusting formation in soils in Southern Mali, West Africa: Evaluation of susceptibility indices

In Southern Mali and neighboring semi-arid Sahel regions, soil crusting and sealing are common and significant phenomena for people who depend on agriculture for their livelihoods. These processes form hard, impermeable layers on the soil surface, reducing water infiltration, increasing runoff and erosion, and hindering germination, seedling emergence, and productivity. Factors such as rainfall intensity, topography, soil attributes, and poor management practices contribute to these phenomena. Here, we aimed to analyze soil attributes affecting crust formation and evaluate them using indicators like the structural stability index (StI), particle separability index (PSI), and crusting susceptibility index (CSI). Soils samples from agricultural and native areas in Southern Mali were analyzed for physical, chemical, mineralogical, and micromorphological attributes. Results revealed that the soils in these regions have high silt and fine sand content and low organic carbon content. Poor soil management, leading to prolonged periods of bare soils, significantly contributes to crusting. Kaolinitic clays, Ca2+ and Mg2+ contents did not appear to affect crusting. The PSI revealed a high risk of aggregate disruption in both agricultural and native lands, demonstrating soil vulnerability to degradation. The StI showed limited risk of structural degradation in native lands, while agricultural soils were more susceptible to crusting. The CSI indicated moderate crusting susceptibility across the regions. By examining the three indices related to texture attributes and organic carbon, this study provides insights into estimating susceptibility to crusting through the evaluation of the risk of soil structural degradation, particle separation, and overall soil susceptibility to surface crusting, all of which underscore the need for improved soil attributes. It emphasizes the importance of implementing effective soil management strategies, particularly the adoption of cover crops, to enhance organic carbon content and increase vegetation cover. These measures are essential for improving soil health and minimizing the risk of crusting.

Maize growth and physiological dynamics: Arsenic uptake modulation under combined abiotic stresses of salinity, boron and arsenic

Soil salinity and relatively high boron (B), frequently co-occur in agricultural environments, posing significant challenges to crop growth and productivity. This inhibitory effect on plant growth can be further exacerbated when crops like maize (Zea mays L.) are exposed to the arsenic (As) contaminated soils and irrigation water, along with elevated salinity and B levels. Understanding these combined effects is crucial for optimizing crop resilience. A hydroponic study was conducted to assess the interactive effects of high B and As under saline conditions on maize. Plants were stressed with salinity (60 mM NaCl), boron (3 mM H3BO3) and arsenic (40 µM Na3AsO4) alone and in combination. A 20-day stress period caused significant reduction in overall growth, with more pronounced effect under combined stress. Root and shoot dry biomass was decreased by 63.45 and 57.84 % while leaf area and chlorophyll index (SPAD value) were diminished by 56.34 and 64.23 %, membrane stability index (MSI) and leaf relative water contents (RWC %) were reduced by 63.92 and 61.59 % upon exposure to these combined stressors as compared to the control treatment. Arsenic stress increased the shoot and root As accumulation by 52.4 and 84.6-fold, respectively. However, high B and salinity effectively suppressed these levels due to their negative correlation with As uptake. Further in-depth phytometric profiling is needed to understand the underlying mechanisms of plant stress tolerance and nutrient homeostasis under these combined stresses.

Peculiarities of Assessing the Efficiency of Research Organization Divisions

Nowadays when requirements to effectiveness and productivity become more and more tough, analysis of ways and methods of assessing the efficiency of research divisions gains in importance. Quantitative analysis is one of simple and frequently used approaches to estimating efficiency of organization and its divisions work. It is based on calculation of traditional indices and studying their dynamics for a certain period of time. Practice shows that within the frames of quantitative analysis indices of liquidity, finance stability, business activity and profitability are estimated. However, in view of work specificity, goals of analysis and mentality of finance manager the list of indicators shall be prolonged. For complex assessing research organizations quantitative analysis can be supplemented by qualitative one. Only in this case information can show the real situation in the organization and its divisions.

Effects of air content on rheological behavior and segregation of self-compacting concrete

Self-compacting concrete (SCC) offers significant advantages due to its low yield stress and plastic viscosity, yet challenges such as bleeding and segregation can compromise its stability. Maintaining a uniform aggregate distribution is essential to prevent these issues. Air-entraining admixtures (AEA) are often used to introduce air bubbles that enhance SCC's resilience in freeze-thaw conditions and potentially improve stability. This study addresses contradictions in prior research regarding the impact of entrained air on SCC's rheological behavior, experimentally evaluates the effects of varying air content on SCC's workability and segregation resistance, and establishes correlations between rheological characteristics and segregation stability. A comprehensive series of rheological tests, including slump flow diameter, flow time, blocking rate, segregation stability, plastic viscosity, yield stress, and segregation index, was conducted on SCC mixes with different AEA dosages. Regression models revealed significant correlations between air content and both the stability and workability of SCC, with results indicating that optimal AEA levels improve flowability and reduce segregation risks. These findings provide valuable insights into designing stable, high-performance SCC formulations tailored for challenging structural applications.

Nanoencapsulation of flaxseed oil: Fabrication, characterization, and storage stability

As a class of oil with high polyunsaturated fatty acid content, the poor oxidative stability of flaxseed oil (FO) has been the key factor restricting its expanded use. FO was encapsulated using flaxseed gum nano-capsules loaded with secoisolariciresinol diglucoside as wall materials. Flaxseed oil nano-capsules (FO-NC) had a particle size of 208.22 nm, an encapsulation efficiency of 96%, a PDI value of 0.131, and a zeta potential of −21.98 mV. By monitoring the changes in the above indicators during accelerated storage of FO-NC, the mechanism of the change in stability of FO-NC was comprehensively analyzed. The study also showed that the nano-encapsulated FO improved its oxidative stability by determining the fatty acid composition, peroxide value and oxidative stability index. Transmission electron (TEM) micrographs showed that FO-NCs were spherical, with a smooth surface. FTIR showed that the FO had been successfully encapsulated. The FO-NC showed good stability over 0–7 days, with higher oxidative stability than unencapsulated FO emulsions. Encapsulation efficiency is a key factor in the stability of FO-NC. The results suggest that nano-encapsulation is an effective means to enhance the oxidative stability of FO.

Altered Blood Oxygen Level-Dependent Signal Stability in the Brain of Patients with Major Depressive Disorder Undergoing Resting-State Functional Magnetic Resonance Imaging

Introduction: Major depressive disorder (MDD) is a common, relapse-prone psychiatric disorder with unknown pathogenesis. Previous studies on resting-state functional magnetic resonance imaging of MDD have mostly focused on the spontaneous activity of blood oxygen level-dependent (BOLD) signals; however, a few studies have investigated BOLD signal stability. Methods: We conducted a resting-state functional study in 42 patients with MDD and 42 healthy controls (HC) matched for age and sex. This included the BOLD signal stability, resting-state functional connectivity (RSFC) analysis, correlation analysis, and support vector machine (SVM) analysis. Results: The BOLD signal stability of the left fusiform gyrus, right inferior temporal gyrus, right temporal pole superior temporal gyrus, and left thalamus was significantly lower in the MDD group compared to the HC group. Further RSFC analysis revealed that the connectivity between right inferior temporal gyrus and both left inferior temporal gyrus and left supramarginal gyrus was significantly reduced in the MDD group. Additionally, the RSFC levels of left thalamus and right thalamus were decreased. Combining BOLD signal stability and RSFC, the SVM-based classification model achieved an accuracy of 80.95% (sensitivity: 78.57%; specificity: 83.33%; receiver-operating characteristic area under the curve: 0.8793). Conclusion: The integration of the BOLD signal stability index and RSFC index demonstrates a robust capability to differentiate between individuals with MDD and HC subjects. We tentatively believe that a combination of the BOLD signal stability index and RSFC can be used to diagnose MDD.

Study of the oxidative stability via Oxitest and Rancimat of phenolic-rich olive oils obtained by a sequential process of dehydration, expeller and supercritical CO2 extractions.

The oxidative stability of olive oils extracted by different methods, i.e. conventional 2-phase extraction (cOO), and sequential extraction by expeller press (eOO) and supercritical CO2 (SCOO), was determined by using two accelerated oxidation methods, Oxitest and Rancimat, in the temperature range 90-160°C. The kinetic analyses carried out provided Arrhenius activation energies, enthalpies, entropies and Gibb's free energies of activation, temperature coefficients, Q10 factors, and the oxidative stability indexes at 20°C (OSI20) for the different oils. A good correlation between the two techniques was obtained (r2 = 0.996). Oxitest showed, however, shorter induction times and less sample quantity (1 g vs. 3 g in Rancimat) requirements, suggesting that it could be a good and faster alternative to Rancimat for the evaluation of the oil oxidative stability. cOO showed OSI20 values of 38.5 and 42.5 months, by the Rancimat and Oxitest methods, respectively. Furthermore, eOO and SCOO showed OSI20 values of 43.3 and 138.6 months by Rancimat and 67 and 142 months by the Oxitest method, respectively. The strong correlation found between the phenolic content of the oils and their OSI20 values confirms that a higher oil phenolic content would improve the oxidative stability of the oils.