Specific Intervals Research Articles

A simple accurate method for concentration-QTc analysis in preclinical animal models

IntroductionIn preclinical cardiovascular safety pharmacology studies, statistical analysis of the rate corrected QT interval (QTc) is the focus for predicting QTc interval changes in the clinic. Modeling of a concentration/QTc relationship, common clinically, is limited due to minimal pharmacokinetic (PK) data in nonclinical testing. It is possible, however, to relate the average drug plasma concentration from sparse PK samples over specific times to the mean corrected QTc. We hypothesize that averaging drug plasma concentration and the QTc-rate relationship over time provides a simple, accurate concentration-QTc relationship bridging statistical and concentration/QTc modeling. MethodsCardiovascular telemetry studies were conducted in non-human primates (NHP; n = 48) and canines (n = 8). Pharmacokinetic samples were collected on separate study days in both species. Average plasma concentrations for specific intervals (CAverage0-X) were calculated for moxifloxacin in canines and NHP using times corresponding to super-intervals for the QTc data statistical analysis. The QTc effect was calculated for each super-interval using a linear regression correction incorporating QT and HR data from the whole super-interval. The concentration QTc effects were then modeled. ResultsIn NHP, a 10.9 ± 0.06 ms (mean ± 95% CI) change in QTc was detected at approximately 1.5× the moxifloxacin plasma concentration that causes a 10 ms QTc change in humans, based on a 0-24 h super-interval. When simulating a drug without QT effects, mock, no effect on QTc was detected at up to 3× the clinical concentration. Similarly, in canines, a 16.6 ± 0.1 ms change was detected at 1.7× critical clinical moxifloxacin concentration, and a 0.04 ± 0.1 ms change was seen for mock. ConclusionsWhile simultaneous PK and QTc data points are preferred, practical constraints and the need for QTc averaging did not prevent concentration-QTc analyses. Utilizing a 0-24 h super-interval method illustrates a simple and effective method to address cardiovascular questions when preclinical drug exposures exceed clinical concentrations.

Time is of the essence: unveiling the rapid response of Populus to insect feeding

Plant metabolism response to insect herbivores is the central theme of this publication. Genetically uniform individuals of European aspen (Populus tremula) were exposed to recurrent feeding by spongy moths (Lepidoptera) at specific time intervals. Changes in physiology, contents of phenolics and saccharides were quantified over the first hour. The unconventional experiment design, integrating analytical methods, and timeline led to the revealing of unexpected dynamics in plant metabolism. The time interval between herbivory initiation and sample collection revealed a pivotal moment, with induced defense activating strongly after 5 min of chewing resulting in an increase in catechin and procyanidin B1. After 10 min, a shift to a tolerant strategy occurs and induced substance concentrations return to control levels. Delayed physiological response was recorded as the first significant difference in transpiration between affected and nonaffected plants and was found after 10 min. A different strategy in exploitation of saccharides after spongy moths infestation was applied because the pool of selected saccharides was rising in the leaves but decreasing in the roots. Placing our results in the context of existing knowledge highlights the uncertain conceptual basis behind the often rigid and definitive classifications in induced plant defense or tolerance strategy.

Determination of the 1L-5-6L MGF110 Genes Influence on the Biological Properties of the African Swine Fever Virus (Asfarviridae; Asfivirus) “Volgograd/14c” in vivo

Abstract African swine fever continues to pose a global agricultural problem due to the absence of vaccine prevention and the high cost of anti-epizootic measures. This study examines the functional role of the African swine fever virus (ASFV) 1L-5-6L multigene family 110 genes in vivo. Four clinically healthy Large White pigs were used in this study. Two groups of animals were inoculated with either the parental strain or the deletion variant, respectively. For subsequent challenge infection, the homologous virulent strain “Stavropol 01/08” was used. Blood samples were collected at specific time intervals. The ASFV infectious activity was determined by titration in porcine blood-derived macrophages. Virus-specific antibodies to the ASFV p30 protein were detected using an enzyme-linked immunosorbent assay (ELISA). The results of real-time polymerase chain reaction (PCR) showed a significant difference in Ct values between samples from the two groups of animals. The determination of ASFV infectious activity in blood samples demonstrated the presence of the virus in animals immunized with the parental strain. The virus was not detected in samples from animals immunized with the deletion strain. The ELISA method demonstrated the presence of p30 protein antibodies in serum samples from 10 to 14 days after immunization with the parental strain, while no antibodies were detected in serum samples from animals immunized with the deletion strain. The properties of the ASFV recombinant strain “Volgograd/D(1L-5-6L) MGF110” were studied in an in vivo experiment. It was found that the deletion strain does not reproduce in animals, unlike the parental strain.

Nanodrug delivery materials for digestive system diseases

Digestive system diseases, such as gastritis, gastric ulcers, chronic liver disease, inflammatory bowel disease (IBD), and colorectal cancer, represent a major group of diseases that have high morbidity and death rates worldwide. Their incidence continues to rise owing to factors such as dietary structure changes, accelerated lifestyles, increased environmental pollution, and population aging. Despite the rapid development of the medical technology, the treatment of digestive diseases still faces many challenges, such as addressing drug-resistant Helicobacter pylori infections, treating IBD, and improving the efficacy of advanced gastrointestinal tumor therapies. Fortunately, the emergence of drug-releasing materials has provided new insights that can be used in the treatment of digestive disorders. Drug-releasing materials are a category of specially designed carriers or systems capable of carrying drugs and controlling their release at specific time intervals on demand to achieve the desired therapeutic effect. This article reviews recent research progress of drug-releasing materials used to diagnose and treat digestive disorders. First, the limitations of traditional oral drug delivery methods, such as low bioavailability and nonspecific distribution, are discussed. Second, different types of drug-releasing materials, such as liposomes, dendritic polymers, micelles, nanogels, inorganic nanoparticles, and extracellular vesicles, along with their advantages in terms of improved drug stability, biocompatibility, targeting, and controlled release, are outlined. In addition, the application strategies and preclinical findings of various drug release materials for different digestive disorders are discussed in detail. This Review could help researchers explore more advanced nanomaterials for personalized treatment of drug delivery for digestive disorders.

Comprehensive Observational and Longitudinal study on the Outbreak of Stroke-related Spasticity focusing on the Early Onset management with Botulinum NeuroToxin (COLOSSEO-BoNT): protocol for a real-world prospective observational study on upper limb spasticity

IntroductionPoststroke spasticity (PSS) affects up to 40% of patients who had a stroke. Botulinum neurotoxin type A (BoNT-A) has been shown to improve spasticity, but the optimal timing of its...

Survival shifts in multiple myeloma: Evaluating the impact of therapeutic advances and racial disparities after a decade of change.

e19509 Background: Multiple myeloma (MM) is the second most common hematologic malignancy and is considered an incurable disease. However, the last two decades have witnessed the emergence of new therapies that have improved overall survival by several folds. In the current study, we are examining the evolving trends in age-adjusted incidence and relative survival among myeloma patients over the last 20 years, specifically focusing on discerning disparities in these trends based on racial classifications. Methods: We performed a retrospective cohort study using the SEER Plus Data, 12 registries, Nov 2022 Sub (1992-2020) to calculate the age-adjusted incidence and relative survival rate (RSR) of MM in the US in two specific time intervals 2001-2010 & 2011-2020 consistent with changes in MM treatment during 2011-2020 including the emergence of immunomodulatory drugs (IMiDs). The year of diagnosis, sex, and race data were available for each case. We excluded cases diagnosed before 2001 and after 2020. Patients were stratified by sex and categorized into two racial groups: White and Black. The 60-month (5-year) and 116-month (used as a 10-year estimate) RSR and age-adjusted incidence rate were calculated for the cohort and each racial group. We calculated survival utilizing the Kaplan-Meier method. Using the log-rank test, we also found hazard ratios (HR), with the corresponding CI for each racial group stratified by sex. Results: We investigated MM incidence and survival rate trends over two decades while considering gender and race. The age-adjusted incidence rate showed a significant overall increase from 6.5 to 7.4 per 100,000, with changes in gender-specific rates. Higher incidence rates among Black populations were noted. Cohort relative survival analysis revealed improved median survival (53 to 83 months) and increased relative survival rate both at five years (46.4% to 56.3%) and at ten years (28.8% to 40.8%). An investigation based on race revealed substantial improvements among both White and Black populations. The HR (Table) emphasized the improved survival outcomes for patients diagnosed in period two across genders and races. Conclusions: The study highlights the changes in the incidence and survival rates of MM. Notably, MM incidence has seen a significant rise in the last decade, particularly among the Black population. The survival of patients diagnosed between 2011 and 2020 revealed statistically significant improvement at both the 5- and 10-year mark compared to patients diagnosed between 2001 and 2010. [Table: see text]

Corticosteroid Injections Within 2 Weeks After Knee Arthroscopy Are Associated With Increased Infection Risk

PurposeWe quantified the risk of 90-day postoperative infection following arthroscopy, stratified by specific time intervals of corticosteroid injection (CSI) postoperatively (0-2 weeks, 2-4 weeks, 4-6 weeks, and 6-8 weeks). MethodsA national, all-payer database was queried. In the primary and secondary analyses, the main outcome was infection at 90-days. Infection was defined by documentation of a septic knee or surgical-site infection according to International Classification of Disease (ICD) Ninth Revision (9) and Tenth Revision (10) codes, and Current Procedure Terminology (CPT) codes. ResultsIn the multivariable regression, the odds ratio (OR) of postoperative infection at 90-days was greater in the CSI injections within 0-<2 weeks (OR 3.31, 95% CI 1.85-5.92, P<0.001) and 2-<4 weeks (OR 2.72 95% CI 1.57-4.71, P=0.003) cohorts in comparison to the control group.When comparing CSI administered within 0-2 weeks to CSI administered within 2-4 weeks, there was a greater odds of postoperative infection (OR 2.50) at 90-days following arthroscopy. ConclusionCSI given within 2 weeks following knee arthroscopy increases the risk of postoperative infection the greatest whereas CSI given with 4 weeks increases the risk but to a lesser degree.

Removal of colour methylene red orange (MRO) by using commercial granular activated carbon (CGAC)

Abstract This study examined the effectiveness of granular activated carbon as an adsorbent for removing methylene red orange (MRO) colour from synthetic wastewater. The experiment involved using 250 mL conical flasks and maintaining the pH at an optimised value of 9. A concentration of 1.6 g of commercial granular activated carbon (CGAC) was mixed with 100 mL of MRO solution (200 mg/L) and agitated at room temperature. Samples were collected at specific time intervals to measure the MRO concentration. The collected data was analysed to describe the interaction between adsorbates and adsorbents. The Langmuir model showed a good fit for isotherm studies, supporting the efficacy of CGAC as an adsorbent for MRO dye removal. This study highlights the potential of CGAC for MRO dye removal and contributes to the understanding of the adsorption process.

The covalent immobilization of β-galactosidase from Aspergillus oryzae and alkaline protease from Bacillus licheniformis on amino-functionalized multi-walled carbon nanotubes in milk

This study aimed was to covalently immobilize β-galactosidase from Aspergillus oryzae and protease from Bacillus licheniformis on amino-functionalized multi-walled carbon nanotubes. In this study, a two-level factorial design was employed to investigate the impact of seven continuous variables (activation pH, glutaraldehyde molarity, activation time (0–8 h), buffer solution pH (8-0), buffer solution molarity, MWCNT-NH2-glutaraldehyde quantity, and stabilization time (0–180 h)) on the immobilization efficiency and enzymatic activity of protease and β-galactosidase. Furthermore, the effect of time on the percentage of enzymatic activity was examined during specific intervals (24, 48, 72, 96, and 120 h) of the immobilization process. The analysis of variance results for protease enzymatic activity revealed a notable influence of the seven variables on immobilization efficiency and enzymatic activity. Additionally, the findings indicate that activation time, buffer pH, MWCNT-NH2-glutaraldehyde quantity, and stabilization time significantly affect the activity of the protease enzyme. The interplay between buffer pH and stabilization time is also significant. Indeed, both activation time and the quantity of MWCNT-NH2-glutaraldehyde exert a reducing effect on enzyme activity. Notably, the influence of MWCNT-NH2-glutaraldehyde quantity is more significant (p < 0.05). In terms of beta-galactosidase enzymatic activity, the study results highlight that among the seven variables considered, only the glutaraldehyde molarity, activation time, and the interplay of activation time and the quantity of MWCNT-NH2-glutaraldehyde can exert a statistically significant positive impact on the enzyme's activity (p < 0.05). The combination of activation time and buffer solution molarity, as well as the interactive effect of buffer pH and MWCNT–NH2–glutaraldehyde, can lead to a significant improvement in the stabilization efficiency of the protease of carbon nanotubes. The analysis of variance results demonstrated that the efficiency of covalently immobilizing β-galactosidase from Aspergillus oryzae on amino-functionalized multi-walled carbon nanotubes is influenced by the molarity of glutaraldehyde, buffer pH, stabilization time, and the interplay of activation time + buffer pH, buffer pH + activation time, activation time + buffer molarity, and glutaraldehyde molarity + MWCNT-NH2-glutaraldehyde (p < 0.05). Through the optimization and selection of optimal formulations, the obtained results indicate enzyme activities and stabilization efficiencies of 64.09 % ± 72.63 % and 65.96 % ± 71.77 % for protease and beta-galactosidase, respectively. Moreover, increasing the enzyme stabilization time resulted in a reduction of enzyme activity. Furthermore, an increase in pH, temperature, and the duration of milk storage passing through the enzyme-immobilized carbon nanotubes led to a decrease in enzyme stabilization efficiency, and lactose hydrolysis declined progressively over 8-h. Hence, the covalent immobilization of β-galactosidase from Aspergillus oryzae and protease from Bacillus licheniformis onto amino-functionalized multi-walled carbon nanotubes is anticipated to be achievable for milk applications.

Radiation Dose Levels in Submandibular and Sublingual Gland Regions during C-Arm Scopy

The subject of this study is to determine the radiation dose exposure to the sublingual glands and submandibular glands during c-arm fluoroscopy imaging by measuring them with dosimeters (TLD-100). The results of this study will contribute to understanding the effects of radiation exposure on the human body. Data for the research was collected by measuring the radiation exposure at specific time intervals: 0.5, 1, 2, 4, and 8 minutes. Measurements were taken for three regions: right and left submandibular glands, and sublingual gland. The maximum radiation exposure for the right submandibular gland at 0.5, 1, 2, 4, and 8 seconds were 1294, 3119, 5916, 11925, and 21274 microSieverts (μSv) respectively. The maximum radiation exposure for the left submandibular gland at the same intervals were 877, 2104, 3704, 7816, and 14618 μSv respectively. For the sublingual gland, the maximum radiation exposure at these intervals were 958, 2081, 3815, 8332, and 14128 μSv respectively

Fuzzy-based dilemma assessment in confrontation analysis with applications to the Walkerton Drinking Water Crisis

As the global population continues to rise and the processes of globalization gather momentum, the conflicting nature of water management issues is becoming increasingly apparent. The purpose of this paper is to introduce a fuzzy-based dilemma assessment method into the methodology confrontation analysis to analyze and assess the conflict problems. More specifically, the inherent logic of dilemma classification and mathematical definitions to the dilemmas are furnished initially to assist in understanding the mechanism of dilemma generation and assessment. Next, the statements of decision-makers (DMs) are quantified and assigned to a specific interval of fuzzy values, which serve to denote the degree of preference regarding their position and intention, as well as the intensity of doubts. Based on that, the dilemma intensity is calculated using the logic derived from the dilemma itself and the dilemma effect is obtained through the application of the same quantitative methodology. Then, to circumvent the complexities associated with parameter discussions, a four quadrant analysis framework is employed, utilizing dilemma intensity and dilemma effect as the two axes to assess dilemma priority. Finally, the Walkerton Drinking Water Crisis is presented to demonstrate the effectiveness and feasibility of the aforementioned approach.

Partition Entropy as a Measure of Regularity of Music Scales

The entropy of the partition generated by an n-tone music scale is proposed to quantify its regularity. The normalized entropy relative to a regular partition and its complementary, here referred to as the bias, allow us to analyze various conditions of similarity between an arbitrary scale and a regular scale. Interesting particular cases are scales with limited bias because their tones are distributed along specific interval fractions of a regular partition. The most typical case in music concerns partitions associated with well-formed scales generated by a single tone h. These scales are maximal even sets that combine two elementary intervals. Then, the normalized entropy depends on each number of intervals as well as their relative size. When well-formed scales are refined, several nested families stand out with increasing regularity. It is proven that a scale of minimal bias, i.e., with less bias than those with fewer tones, is always a best rational approximation of log2h.

Improving Muscat Hamburg Wine Quality with Innovative Fermentation Strategies Using Schizosaccharomyces pombe Derived from Fermented Grains of Sauce-Flavor Baijiu.

This study investigates innovative approaches to improve the quality and aroma characteristics of Muscat Hamburg wine production by substituting the conventional Saccharomyces cerevisiae yeast with an efficient fermentation strain of Schizosaccharomyces pombe. The typical use of S. cerevisiae in Muscat Hamburg wine often leads to uniformity and prolonged processing times, requiring subsequent malolactic fermentation to degrade excessive malic acid. The study advocates for the replacement of S. cerevisiae with a specific S. pombe strain, Sp-410, isolated from the fermented grains of sauce-flavor Baijiu, a Chinese spirit. Muscat Hamburg wine fermented with the S. pombe strain demonstrates decreased malic acid levels, offering a potential alternative to malolactic fermentation. However, exclusive S. pombe fermentation may result in an overproduction of acetic acid metabolites, leading to a monotonous taste. In response, the study proposes a mixed fermentation approach, combining the S. pombe strain with a Saccharomyces uvarum strain and a non-Saccharomyces yeast, Torulaspora delbrueckii. The optimized mixed fermentation strategies (M:SP+TD and M60SP+TD) involve specific proportions and intervals of inoculation, aiming to enhance the quality and aroma complexity of Muscat Hamburg wine. In conclusion, this research contributes to advancing the production of high-quality Muscat Hamburg wines, utilizing S. pombe as the primary yeast strain and implementing mixed fermentation methodologies.

The role of atrial pacing site in reducing filling pressures by accelerated pacing in virtual HFpEF patients

Abstract Background Patients with heart failure with preserved ejection fraction (HFpEF) and pacemakers have been shown to benefit from moderately accelerated pacing rates compared to the standard 60bpm. HFpEF patients often present with prolonged P-wave duration (PWD) and atrial fibrillation. Right atrial appendage pacing (RAAP) lengthens PWD, RA septal (RASP) has a neutral effect, while Bachmann’s bundle pacing (BBP) normalizes or shortens PWD compared to sinus rhythm. The mechanical and hemodynamic effects of atrial pacing site selection remain unknown. Aim To investigate the impact of RAAP, RASP and BBP on cardiac mechanics and hemodynamics in an established cohort of virtual HFpEF patients undergoing accelerated pacing. Method HFpEF with prolonged PWD was simulated using the validated CircAdapt computational model of the human cardiovascular system. First, left ventricular (LV) diastolic dysfunction was simulated by decreasing LV myocardial relaxation rate and compliance, such that mean left atrial (LA) pressure (mLAP) was 15mmHg. Second, PWD was prolonged by prescribing a gradual electrical activation delay from RA to LA of 140ms. We then simulated atrial pacing with three different lead positions (Fig.1, left) and gradually increased pacing rate with a constant 120-ms paced atrioventricular (AV) delay. The CircAdapt model computed regional LA strain and mLAP with RAAP, RASP, and BBP. Cardiac output (5L/min) and mean arterial pressure (92mmHg) were kept constant in all simulations. Results Simulated BBP demonstrated the most synchronous LA mechanical activation and function, characterized by uniform segmental LA strain patterns and highest LA reservoir strain (LASR) (Fig.1, middle, with colored arrows highlighting the mechanical dyssynchrony). Hemodynamically (Fig.1, right), BBP acutely decreased mLAP (-1.0mmHg) at the initial heart rate of 60bpm, while RAAP increased it (+0.3mmHg). As pacing rate accelerated, BBP reduces filling pressure (mLAP: -2.8mmHg), more than RASP (-1.8mmHg) or RAAP (-1.2mmHg) at 80bpm. At high pacing rates, RASP and RAAP adversely increase mLAP, due to the prolonged atrial contraction duration and shorter LV filling time. Conclusion Our simulations of different atrial pacing sites in virtual HFpEF patients suggest that BBP yields the most synchronous LA activation pattern and a more substantial reduction in filling pressures with accelerated atrial pacing compared to RASP. Reduction in mLAP with accelerated pacing was attenuated with RAAP. While our study concentrated on a specific paced AV interval, the favorable outcomes observed with BBP could be further improved by including different, rate-adaptive, AV protocols.Fig 1.

Study on Evaluation and Prediction for Shale Gas PDC Bit in Luzhou Block Sichuan Based on BP Neural Network and Bit Structure

Deep and ultra-deep shale gas resources have great potential, but well drilling faces many challenges. The Polycrystalline Diamond Compact (PDC) bit has become the primary rock-breaking instrument for oil and gas drilling. Reasonable bit structure designs can promote rock-breaking efficiency and extend service life. In this study, reverse modeling technology is used to analyze the structural characteristics of PDC bits collected in the field, and the influence of the structural characteristics of the bit at a specific interval on the rate of penetration (ROP) and drill footage is investigated using the Spearman rank correlation coefficient method. The number of blades, cutting angle of the cutters, crown rotation radius, internal cone angle, and diameter of the cutters are discovered to be the main structural characteristics that affect the ROP and footage of the bits, and the degree of influence varies depending on the formation conditions. The number of blades, crown rotation radius, inner cone angle, and cutting angle of the cutters have a significant impact on the ROP, whereas blade thickness, gauge length, gauge width, nozzle equivalent diameter have a significant impact on the bit footage. In addition, a back propagation (BP) neural network is utilized to build a prediction model of bit footage and ROP over a certain interval based on the structural characteristics of the bit. The goodness of fit of the model is greater than 85%, and its accuracy is high. Based on the usage of the bit, the evaluation and prediction of the bit can provide a reference for the structural design and optimization of the bit in a specific interval, guide the bit selection work, rationally plan the drilling operation, and reduce the drilling cost.

Follow-up care compliance among patients diagnosed with unruptured intracranial aneurysms

ObjectivesPeriodic imaging follow-up for patients with unruptured intracranial aneurysms (UIA) is crucial, as studies indicate higher rupture risk with aneurysm growth. However, few studies address patient adherence to follow-up recommendations. This study aims to identify compliance rates and factors influencing follow-up adherence. MethodsPatients with a UIA were identified from our institution's database from 2011-2021. Follow-up imaging (CT/MR Angiogram) was advised at specific intervals. Patients were categorized into compliant and non-compliant groups based on first-year compliance. Factors contributing to compliance were assessed through multivariate logistic regression. Phone interviews were conducted with non-compliant patients to understand reasons for non-adherence. ResultsAmong 923 UIA diagnosed patients, 337 were randomly selected for analysis. The median follow-up period was 1.4 years, with a 42% first-year compliance rate. The mean aneurysm size was 3.3 mm. Five patients had a rupture during follow-up, of which 4 died. Compared with patients consulting specialists at the initial diagnosis, those seen by non-specialists exhibited lower compliance (OR 0.25, p < 0.001). Loss to follow-up was greatest during transition from emergency service to specialist appointments. Patients who spoke languages other than English exhibited poorer compliance than those speaking English (OR 0.20, p = 0.01). ConclusionsSignificant amounts of UIA patients at low rupture risk were lost to follow-up before seeing UIA specialists. Main non-compliance factors include inadequate comprehension of follow-up instructions, poor care transfer from non-specialists to specialist, and insurance barriers.

Effect of the storage process on quality characteristics of hemp-enriched "tsoureki" a rich-dough baked Greek product.

The effects of the storage process on the quality characteristics of a hemp-enriched "tsoureki" (a rich-dough baked Greek product, rich-dough baked product [RDBP]) were investigated. The wheat flour was substituted with defatted hemp flour at selected ratios (0%-50% hemp:wheat flour). The baked products were stored at 25°C and at specific time intervals (0, 1, 4, 7, 10, and 14 days), and their properties were determined, including moisture content, water activity, structure, texture, color, total phenolic content (TPC), and antioxidant activity. Moreover, analyses of phenolic compounds were performed using quadrupole time of flight liquid chromatography-mass spectroscopy, identifying 14 compounds. Both the first-order kinetic model and modified Avrami equation, including the hemp-to-wheat ratio effect in the rate constant, well described the changes in the quality characteristics. The results showed that storage time and hemp incorporation significantly affected the quality of the product. Water activity decreased from 0.901 to 0.859, whereas moisture content decreased from 30.52%-32.33% (0 days) to 26.97%-27.02% w.b. (14 days) with storage time for all hemp additions. Hardness was greatly affected by hemp flour addition and approached 14.72 and 17.85 N after 14 days of storage for 30% and 50% substitutions, respectively. Springiness and cohesiveness decreased with hemp addition and storage time. The color difference of the hemp-enriched products compared to the control sample increased during storage. TPC increased due to the addition of hemp flour, whereas 14 compounds were identified. Based on property correlation, the hemp-enriched RDBP-tsoureki held its high-quality characteristics for 7 days of storage and contained a significant amount of bioactive compounds. PRACTICAL APPLICATION: Industrially produced, defatted hemp is a promising byproduct that can be used to nutritionally enhance baked goods. Modeling results can be used for the prediction of the properties that define product storage ability and also that the hemp-enriched, rich dough-baked Greek "tsoureki" could be produced while maintaining total phenolic content and antioxidant activity during 7 days of storage. These findings are expected to be used in the future in baked goods industry applications to produce goods with an improved nutritional profile.

Risk Analysis of Electricity Demand at Public Electric Vehicle Charging Stations (SPKLU): CVaR Model Approach

The electricity demand at Public Electric Vehicle Charging Stations (SPKLUs) exhibits significant volatility, which is driven by several aspects including electricity demand patterns at specific time intervals, load variability, SPKLU capacity, and other related factors. The variability of these swings can present hazards for SPKLU operators in relation to energy administration as well as operational and financial hazards. The objective of this study is to assess the risk associated with energy demand fluctuation at SPKLUs by employing the Conditional Value-at-Risk (CVaR) model technique. CVaR, or Conditional Value at Risk, is a quantitative measure of risk that calculates the predicted loss value in the most unfavorable situation. It is commonly employed to enhance the risk management approach of SPKLUs. The electricity demand at SPKLU exhibits significant volatility, with an average fluctuation of 10.15% and a standard deviation of 49.67%. The CVAR, calculated at -121.19% for a confidence interval of 1%, represents the maximum potential loss that could be experienced during worst-case electrical demand conditions, highlighting the substantial fluctuations in demand. The study initially implemented the CVaR model to analyze power demand at SPKLU, providing novel perspectives on risk reduction for critical infrastructure and proposing unique strategies for managing demand fluctuations in a reliable and efficient manner. The results also offer comprehensive insights into risk exposure and facilitate the formulation of well-informed and strategic risk management plans.

Monitoring the Geopolymerization Reaction of Geopolymer Foams Using 29Si and 27Al MAS NMR

This study aims to investigate the geopolymerization reaction of geopolymer foams produced with three different foaming agents: aluminum powder, zinc powder, and hydrogen peroxide. The geopolymerization reaction of geopolymer foam was monitored using the 27Al and 29Si magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectroscopy technique. 27Al MAS-NMR was used to monitor the reaction at an early stage, while 29Si and 27Al MAS-NMR analyses were employed at specific time intervals of 3, 6, 10, 15, and 28 days to examine the changes that occurred in the formed gel over time. We discussed in detail how the type of foaming agent used and the duration of the reaction both influence the quantity of gel formed and the amount of remnant fly ash. Our findings indicate that the type of foaming agent used affects the formation and structure of the gel, with aluminum powder leading to the highest gel formation. Additionally, the duration of the reaction plays a significant role in determining the quantity of remnant fly ash, with longer reaction times resulting in decreased fly ash content. This study sheds light on the relevance of understanding the role of foaming agents in the geopolymerization reactions of geopolymer foams and the influence of reaction time on the formed gel properties.

Privacy-Preserving Breast Cancer Prediction Based on Logistic Regression

Abstract With the increasing strain on today’s healthcare resources, there is a growing demand for pre-diagnosis testing. In response, researchers have suggested diverse machine learning models for disease prediction, among which logistic regression stands out as one of the most effective models. Its objective is to enhance the accuracy and efficiency of pre-diagnosis testing, thereby alleviating the burden on healthcare resources. However, when multiple medical institutions collaborate to train models, the untrusted cloud server may pose a risk of private data leakage, enabling participants to steal data from one another. Existing privacy-preserving methods often suffer from drawbacks such as high communication costs, long training times and lack of security proofs. Therefore, it is imperative to jointly train an excellent model collaboratively and uphold data privacy. In this paper, we develop a highly optimized two-party logistic regression algorithm based on CKKS scheme. The algorithm optimizes ciphertext operations by employing ciphertext segmentation and minimizing the multiplication depth, resulting in time savings. Furthermore, it utilizes least squares to approximate sigmoid functions within specific intervals that cannot be handled by homomorphic encryption. Finally, the proposed algorithm is evaluated on a breast cancer dataset, and simulation experiments demonstrate that the model’s prediction accuracy, after machine learning training, exceeds 96% for two-sided encrypted data.