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Abstract This research paper investigates discrete predator-prey dynamics with two logistic maps. The study extensively examines various aspects of the system’s behavior. Firstly, it thoroughly investigates the existence and stability of fixed points within the system. We explores the emergence of transcritical bifurcations, period-doubling bifurcations, and Neimark-Sacker bifurcations that arise from coexisting positive fixed points. By employing central bifurcation theory and bifurcation theory techniques. Chaotic behavior is analyzed using Marotto’s approach. The OGY feedback control method is implemented to control chaos. Theoretical findings are validated through numerical simulations.

Abstract Neuronal activity-dependent transcription directs molecular processes that regulate synaptic plasticity, brain circuit development, behavioral adaptation, and long-term memory. Single cell RNA-sequencing technologies (scRNAseq) are rapidly developing and allow for the interrogation of activity-dependent transcription at cellular resolution. Here, we present NEUROeSTIMator, a deep learning model that integrates transcriptomic signals to estimate neuronal activation in a way that we demonstrate is associated with Patch-seq electrophysiological features and that is robust against differences in species, cell type, and brain region. We demonstrate this method’s ability to accurately detect neuronal activity in previously published studies of single cell activity-induced gene expression. Further, we applied our model in a spatial transcriptomic study to identify unique patterns of learning-induced activity across different brain regions in male mice. Altogether, our findings establish NEUROeSTIMator as a powerful and broadly applicable tool for measuring neuronal activation, whether as a critical covariate or a primary readout of interest.

The development of new techniques for anti-cancer therapy has become a very active area of research in recent years. One of the promising directions of anti-cancer therapy aims at using the genetically engineered macrophages as killers of tumor cells. The present work introduces a new fractional-order mathematical model to simulate the nonlinear interaction between genetically engineered macrophages and tumor cells. The proposed model incorporates the pro-tumor impacts and anti-tumor impacts which are triggered by the macrophages. The existence and uniqueness of positive solutions of the model are proved. Then, the stability conditions for the equilibrium points are obtained. The bifurcation diagrams explore the impacts of crucial parameters on the dynamical behaviors of the model. Finally, the optimal control scheme is employed to efficiently eliminate tumor cells and inhibit their prevalence in the body. Using Adms-Bashforth-Moulton method, numerical experiments are carried out to validate theoretical analysis.

This research explores bifurcation of a nonlinear model concerning with the telecommunication strait. Possible all phase plane diagrams due to various parametric conditions are found. Derivation of analytical tangled wave propagating solutions following all phase orbits of the corresponding phase portraits are established. As a results, the soliton, shock wave, singular soliton, periodic wave and singular periodic solutions are obtained by direct integration from Hamiltonian energy function. The periodic solutions of the model are formulated in the form of generalized Jacobi elliptic functions, which also provide the solitonic solution setting the value of beta is unity. Additionally, chaotic and quasi-periodic behaviors have been found for a range of parameter values after adding the perturbed term. The perturbed system’s quasi-periodic and chaotic behavior have been demonstrated using sensitivity analysis. Finally, picturesque explorations are delivered exposing effects of exist parameters of the gained wave solutions. The majority of the achieved results are derived for the first time. Moreover, the solutions show that the novel schemes are very simple, outright, fruitful and successful and that they can be used in wide range of other nonlinear partial differential equations (NLPDEs), which create different kinds of dynamical features of other wave model.

This study introduces a newly modified Lorenz model capable of demonstrating bifurcation within a specified range of parameters. The model demonstrates various bifurcation behaviors, which are depicted as distinct structures in the diagram. The study aims to discover and analyze the existence and stability of fixed points in the model. To achieve this, the center manifold theorem and bifurcation theory are employed to identify the requirements for pitchfork bifurcation, period-doubling bifurcation, and Neimark–Sacker bifurcation. In addition to theoretical findings, numerical simulations, including bifurcation diagrams, phase pictures, and maximum Lyapunov exponents, showcase the nuanced, complex, and diverse dynamics. Finally, the study applies the Ott–Grebogi–Yorke (OGY) method to control the chaos observed in the reduced modified Lorenz model.

A new four-dimensional chaotic system with four cross-terms is investigated in this study. The dynamical behaviors of the system and codimension-one bifurcations are analyzed both theoretically and numerically. The influences of the system’s parameters on its nonlinear dynamics are explored. Then, a proposed four-dimensional blinking system is introduced based on the new chaotic system. More interestingly, the possible occurrence of ghost attractors in the phase space of the blinking system is verified and has been illustrated through several examples. The encryption keystream was generated dynamically using pre-treated chaotic mixed sequences and was used to mask the voice bitstream to protect voice data integrity. Finally, a voice encryption example employing the 4-D blinking chaotic system of the proposed system is presented.

This work is devoted to introduce a reliable, fast and highly accurate reservoir computer machine learning scheme to forecast time evolution of COVID-19 pandemic. In particular, the COVID-19 official data related to susceptible cases, confirmed cases, and recovered cases in Egypt and Saudi Arabia are collected. They employed as the training data for suggested reservoir computer (RC) model. Then, detailed simulation experiments are carried out within specified time periods. The evolution of COVID-19 in Egypt and Saudi Arabia are predicted on the subsequent times intervals and compared with real validation test data. The forecasting accuracy is improved by computing the optimal output matrix which minimizes the normalized root mean square errors (NRMSEs). The performance of RC scheme is evaluated when different-size training data, different-size test data, and different number of internal nodes are used. The comparisons with the robust LSTM deep learning techniques are performed. It is shown that the presented RC-based forecasting technique is more accurate for long-time forecasting, faster, and has lower computational cost.

Background This study aimed to assess the safety and efficacy of intravenous granisetron as adjuvant therapy for spinal anesthesia-induced hypotension in type I diabetic parturients undergoing CS.Methods This double-blinded, parallel-group, randomized trial enrolled 68 adult parturients who were scheduled for CS under spinal anesthesia. The patients were randomly allocated to two groups (34 parturients each). In the granisetron (G) group, 1 mg of granisetron diluted in 10 mL of normal saline was administered intravenously 10 minutes prior to spinal anesthesia. While in the control (C) group, 10 mL of normal saline was administered in the same manner. The primary outcomes were total ephedrine consumption and frequency of use. Secondary outcomes included the total atropine consumption and frequency of use, nausea, vomiting, estimated intraoperative blood loss, patient satisfaction, Apgar score, and hemodynamic parameters.Results Group G had a significant reduction in the total ephedrine consumption (P = 0.009) and its frequency of use (P = 0.034). While the total atropine consumption and frequency of use, intraoperative blood loss, and patient satisfaction were not significantly different between the two groups. Nausea and vomiting were significantly reduced in group G. After 5 minutes of delivery, the Apgar score was significantly elevated in group G. The reduction of heart rate and hypotension was significantly lowered in group G.Conclusion In type I diabetic parturients, prophylactic use of granisetron can be effective in reducing ephedrine usage and attenuating the spinal anesthesia-induced hypotension during CS.

Background This study aimed to evaluate endotracheal tube (ETT) cuff inflation pressure (CIP) applied by anesthetists as well as the effect of an interview and feedback on their CIP accuracy.Methods This single-blind, controlled trial involved two series of CIP measurements in intubated patients before and after an interview and feedback of the participating anesthetists who were asked to inflate the cuffs for all intubated patients as per their clinical judgment. The cuff pressures were measured using a manometer and accordingly adjusted to 25 cm H2O by the researchers. For each anesthetist, 3 measurements were recorded, and the mean pressure values were calculated for each setting. The anesthetists were initially blinded, then they were informed about the pressure values and the adjustments. The primary outcome was the anesthetists’ accuracy regarding ETT inflation following the feedback. The secondary outcomes were pressure values in senior and junior anesthetists as well as in scheduled and emergency operations.Results The study enrolled 28 anesthetists; six registrars or senior registrars and 22 residents. Interview and feedback significantly lowered the mean pressure applied by the anesthetists. The cuff inflation pressure decreased from 33.8 ± 1.95 to 30.8 ± 3.24 and from 32.9 ± 2.38 to 29.9 ± 3.44 for emergency and scheduled surgeries, respectively. Furthermore, the frequency of safe CIP increased significantly for both emergency and scheduled surgeries. However, the senior staff showed no significant increase in safety CIP.Conclusion Anesthetists improved their accuracy of CIP after educational feedback. ETT cuff pressures should be routinely measured in intubated patients under general anesthesia.

Background This study aimed to assess the safety and efficacy of intravenous (IV) versus intrathecal (IT) dexmedetomidine as an additive to hyperbaric bupivacaine in spinal anesthesia in adult patients undergoing hip arthroplasty.Methods This randomized, controlled, triple-blinded trial enrolled 90 patients aged 18–65 years, American Society of Anesthesiologists physical status I–II who were scheduled for hip arthroplasty under spinal anesthesia. The study subjects were randomly assigned into three groups. The control group (group C) received IT hyperbaric bupivacaine (0.5%, 12.5 mg) plus 1 ml of normal saline. The IT group received IT hyperbaric bupivacaine (0.5%, 12.5 mg) plus 5 µg of dexmedetomidine diluted in 1 ml of normal saline. The IV group received hyperbaric bupivacaine (0.5%, 12.5 mg) plus 0.5 µg/kg of dexmedetomidine diluted in 20 ml of normal saline administered slowly IV. A modified Bromage scale was used to assess motor blocks. We used the Numerical Pain rating scale (NRS) for pain assessment. We used morphine for postoperative analgesia.Results Groups IT and IV had significantly lower total morphine consumption and higher time to the first analgesic request than group C. Durations to two-segment regression and motor block regression to Bromage 1 were significantly higher in groups IT and IV than in group C. Motor block regression to Bromage 1 showed a significant difference between the IT and IV groups with a more delayed motor recovery in the IT group.Conclusion Both IV and IT dexmedetomidine extend the effect of the sensorimotor impact of subarachnoid anesthesia, but IT dexmedetomidine was superior to IV dexmedetomidine in adult patients undergoing hip arthroplasty.

This study presents an optimal control strategy through a mathematical model of the Covid-19 outbreak without lock-down. The pandemic model analyses the lock-down effect without control strategy based on the current scenario of second wave data to control the rapid spread of the virus. The pandemic model has been discussed with respect to the basic reproduction number and stability analysis of disease-free and endemic equilibrium. A new optimal control problem with treatment is framed to minimize the vulnerable situation of the second wave. This system is applied to study the effects of vaccines and treatment controls. Numerical solutions and the graphical presentation of the results predict the fate of India’s second wave situation on account of the control strategy. Lastly, a comparative study with control and without control has been analysed for the exposed phase, infective phase, and recovery phase to understand the effectiveness of the controls. This model is used to estimate the total number of infected and active cases, deaths, and recoveries in order to control the disease using this system and studying the effects of vaccines and treatment controls.

Abstract Background Tomato mosaic virus (ToMV) is a dangerous disease of tomato (Lycopersicon esculentum) that reduces dramatically the yield. To reduce ToMV infection, microalgal isolates were utilized. Microalgal species (Chlorella vulgaris, Anabaena oryzae, Spirulina platensis, Nostoc linckia and Dunaliella salina) were shown to be responsible for the stimulation of tomato resistance against ToMV. Results Initial signs of discoloration and mosaic in ToMV-inoculated plants were detected and identified on inoculated leaves at 6 and 12 dpi in control and treated plants, respectively, suggesting that microalgae may inhibit ToMV growth. Treatment with microalgae resulted in a significant decrease in symptoms (up to 63% reduction in disease severity) and negative ELISA readings, indicating that the microalgae induced resistance in tomato against ToMV infection. The isolates also enhanced the activity of pathogenesis-related enzymes (PPO and POX reaching to 0.033 and 0.054 in D. salina, respectively), as well as tomato growth characters in comparison with the control. Microalgal treatments demonstrated that the salicylic acid (SA) and jasmonic acid (JA) pathways were involved in tomato plant defense responses. The relative gene expressions of PR1 and phenylalanine ammonia lyase (PAL), which are involved in the SA and JA pathways, respectively, were improved in treated plants compared to the control. Conclusion The findings indicated that algal-induced ToMV resistance was mediated via several defense pathways in tomato. The antiviral mechanism was described, which provides a light on the potential of algae in plant viral disease management.

The structure's ability to release energy through inelastic behaviour is reflected in the response reduction factor (R). It results from a combination of redundancy, ductility, and over strength. Thus, determining R with accurate values plays a critical function in the process of seismic design. This study aims to determine the response factor of structures of reinforced concrete (RC). With different structural irregularities, additionally, determine the impact of the interaction between soil and structure (SSI) using non-linear static pushover analysis was adopted in numerical simulation by using SAP2000. The selected irregularities included elevational and in-plan changes It was determined that, in comparison to regular buildings, buildings with irregular vertical geometries had poorer inelastic seismic capacities. Therefore, R is less than that which is stated in the ECP 2020, so it ought to be reduced by 15-40% before the design stage. The outcomes demonstrated that It isn't concluded that irregularity has a considerable effect on weak soil (C). The reduction in R, considering (SSI), reached 20.3% and 13.1% for fixed and isolated supports, respectively, in case of loose soil. Moreover, it became obvious that for the same structure the stiffer the base soil the greater the R's value. [ABSTRACT FROM AUTHOR]

Abstract Background Pathological complete response (pCR) is a surrogate for the efficacy of neoadjuvant chemotherapy (NCT) in locally advanced breast cancer (LABC). We analyzed the predictive clinical factors for pathological responses and survival outcomes in a cohort of Egyptian patients. Methods We evaluated the medical records of patients with breast cancer who received NCT in our academic institute. Survival curves were estimated with the Kaplan-Meier method. Cox proportional models were used for multiple regression analysis. Results Our cohort included 368 patients with a median age of 48 years (range 21–70). The median follow-up time was 3 years. The clinical tumor stage (T3–4) represented 58%, with 80% having positive axillary nodes. The luminal subgroup prevailed by 68%. The objective response rate (ORR) reached 78%, and 16% of patients achieved pCR. The clinical node stage and optimal chemotherapy were associated with higher ORR (p = 0.035 and p = 0.001, respectively). Predictors of pCR were clinical T-stage (p = 0.026), high Ki-67 index > 20 (p = 0.05), and receiving optimal chemotherapy (p = 0.014). The estimated 3-year disease free-survival (DFS) was 53%. Receptor status, achieving ORR, and pCR were associated with better DFS with hazard ratios of 0.56, p = 0.008; 0.38, p = 0.04; and 0.28, p = 0.007, respectively. Conclusions Luminal tumors still draw benefit from neoadjuvant chemotherapy in terms of clinical response and breast conservative surgery. Treatment escalation to those who did not achieve pCR requires more investigation, given a higher recurrence rate in real-world experience.