Adaptive Neural Networks Accounted for by Five Instances of “Respondent-Based” Conditioning

Neural Networks may be made much faster and more efficient by reducing the amount of memory and computation used. In this paper, a new type of neural network called an Adaptive Neural Network is introduced. The proposed neural network is comprised of five unique pairings of events. Each pairing is a module and the modules are connected within a single neural network. The pairings are a simulation of respondent conditioning. The simulations do not necessarily represent conditioning in actual organisms. In the theory presented here, the pairings in respondent conditioning become aggregated together to form a basis for operant conditioning. The specific pairings are as follows. The first pairing is between the reinforcer and the neural stimulus that elicits the behavior. This pairing strengthens and makes salient that eliciting neural stimulus. The second pairing is that of the now salient neural stimulus with the external environmental stimulus that precedes the operant behavior. The third is the pairing of the environmental stimulus event with the reinforcing stimulus. The fourth is the pairing of the stimulus elicited by the drive with the reinforcement event, changing the strength of the reinforcer. The fifth pairing is that after repeated exposure the external environmental stimulus is paired with the drive stimulus. This drive stimulus is generated by an intensifying drive. Within each module, a “0” means no occurrence of a pairing A of Stimuli A and a “1” means an occurrence of a pairing A of Stimuli A. Similarly, a “0” means no occurrence of a pairing Band a “1” means an occurrence of a pairing B, and so on for all 5 pairings. To obtain an output one multiplies the values of pairings through E. In one trial or instance, all 5 pairings will occur. The results of the multiplications are then accumulated and divided by the number of instances. The use of these simple respondent pairings as a basis for neural networks reduces errors. Examples of problems that may be addressable by such networks are included.

Adaptive Neural Networks Accounted for by Five Instances of “Respondent-Based” Conditioning

Neural Networks may be made much faster and more efficient by reducing the amount of memory and computation used. In this paper, a new type of neural network called an Adaptive Neural Network is introduced. The proposed neural network is comprised of five unique pairings of events. Each pairing is a module and the modules are connected within a single neural network. The pairings are a simulation of respondent conditioning. The simulations do not necessarily represent conditioning in actual organisms. In the theory presented here, the pairings in respondent conditioning become aggregated together to form a basis for operant conditioning. The specific pairings are as follows. The first pairing is between the reinforcer and the neural stimulus that elicits the behavior. This pairing strengthens and makes salient that eliciting neural stimulus. The second pairing is that of the now salient neural stimulus with the external environmental stimulus that precedes the operant behavior. The third is the pairing of the environmental stimulus event with the reinforcing stimulus. The fourth is the pairing of the stimulus elicited by the drive with the reinforcement event, changing the strength of the reinforcer. The fifth pairing is that after repeated exposure the external environmental stimulus is paired with the drive stimulus. This drive stimulus is generated by an intensifying drive.  Within each module, a “0” means no occurrence of a pairing  A of Stimuli A and a “1” means an occurrence of a pairing  A of Stimuli A. Similarly, a “0” means no occurrence of a pairing  B and a “1” means an occurrence of a pairing  B , and so on for all 5 pairings. To obtain an output one multiplies the values of pairings through E . In one trial or instance, all 5 pairings will occur. The results of the multiplications are then accumulated and divided by the number of instances. The use of these simple respondent pairings as a basis for neural networks reduces errors. Examples of problems that may be addressable by such networks are included. &nbsp

Do increased levels of progesterone and progesterone/estradiol ratio on the day of human chorionic gonadotropin affects pregnancy outcome in long agonist protocol in fresh in vitro fertilization/intracytoplasmic sperm injection cycles?

Background: The effect of elevated levels of serum progesterone (P 4 ) and estradiol (E 2 ) on the day of human chorionic gonadotropin and their cut-off value on in vitro fertilization (IVF) outcomes is still not clear. Aims: The aim was to evaluate the association between serum P 4 , E 2 and progesterone/estradiol ratio (P 4 /E 2 ) on pregnancy outcome in IVF/intracytoplasmic sperm injection (ICSI) cycles with long agonist protocol. Setting and Design: Retrospective, single center, cohort study. Materials and Methods: A review of complete data of 544 women undergoing fresh IVF/ICSI cycles (539 cycles) with long agonist protocol from January 2012 to February 2014 was done. Data were stratified into Three groups according to the number of oocytes retrieved: low (≤4 oocytes obtained), intermediate (5-19 oocytes obtained), and high ovarian response (≥20 oocytes obtained). Statistical Analysis: Fishers exact test/Chi-square was carried for comparing categorical data. Receiver operating characteristics analysis was performed to determine the cut-off value for P 4 and P 4 /E 2 detrimental for pregnancy. Results: A negative association was observed between pregnancy rate (PR) and serum P 4 and P 4 /E 2 levels with no effect on fertilization and cleavage rate. The overall cut-off value of serum P 4 and P 4 /E 2 ratio detrimental for pregnancy was found to be 1.075 and ≥0.35, respectively. Different P 4 threshold according to the ovarian responders were calculated, 1.075 for intermediate and 1.275 for high responders. Serum E 2 levels were not found to be significantly associated with PR. Conclusion: Serum P 4 levels and P 4 /E 2 ratio are a significant predictor for pregnancy outcome without affecting cleavage and fertilization rate while serum estradiol levels do not seem to affect PR

256 Comparative Analysis of Emergency Department Visits for Breast Injuries Pre- and Post-COVID

OBJECTIVES/GOALS: Studies show a decrease in injury-related emergency department (ED) visitsduring COVID.There is a gap in the literature regarding the effect of the pandemic on breast injury-related ED visits. We aim to compare these visits pre- and post-COVID, and whether this subset reflects the same trends seen in overall injury-related ED visits. METHODS/STUDY POPULATION: A retrospective study of breast injuries was conducted between 2018 and 2022, using the National Electronic Injury Surveillance System. Patients were categorized into pre-COVID and post-COVID groups, for visits occurring before and after January 20, 2020. A total of 1077 breast injuries were stratified into pre-COVID (n = 444) and post-COVID (n = 633) groups. Clinical data on patient demographics, diagnosis, disposition, location, and alcohol use were collected. RESULTS/ANTICIPATED RESULTS: Mean age was significantly different: pre-COVID mean age was 37.29; post-COVID’s was 40.40 (p = 0.0338). >90% of patients were female (p = 0.4066). White patients accounted for 36.0% of pre-COVID visits and 47.2% of post-COVID; BIPOC patients were 32.88% and 31.75% respectively. There was significant difference between race and COVID groups (p = 0.0013). No significant differences were found when considering all diagnoses (p = 0.3841) or the top three diagnoses (other, contusions/abrasions, and burns/scald) (p = 0.6176). Incident location showed a weak evidence of association (α = 0.1), when including unrecorded data (p = 0.1365) and removing those entries (p = 0.0832). Alcohol use did not reveal a significant association (p = 0.2110). DISCUSSION/SIGNIFICANCE: There are more breast injuries reported post-COVID. No significant difference was identified in the types of injuries diagnosed, the location these injuries took place, and how these injuries were treated. However, the demographics (age, race) of patients seeking care were significantly different

Chitosan Nanoparticle-Mediated Delivery of Curcumin Suppresses Tumor Growth in Breast Cancer

Curcumin is a nutraceutical known to have numerous medicinal effects including anticancer activity. However, due to its poor water solubility and bioavailability, the therapeutic impact of curcumin against cancer, including breast cancer, has been constrained. Encapsulating curcumin into chitosan nanoparticles (CHNPs) is an effective method to increase its bioavailability as well as antitumorigenic activity. In the current study, the effects of curcumin-encapsulated CHNPs (Cur-CHNPs) on cell migration, targeted homing and tumor growth were examined using in vitro and in vivo breast cancer models. Cur-CHNPs possessed a monodispersed nature with long-term colloidal stability, and demonstrated significant inhibition of cell viability in vitro, which was potentiated by 5-Fluorouracil (5-FU). Outcomes of the in vivo imaging studies confirmed effective tumor targeting and retention ability of Cur-CHNPs, thereby suppressing breast tumor growth in mice models. Overall, the results demonstrated that Cur-CHNPs could be an effective candidate drug formulation for management of breast cancer

Proceedings of International Conference on Women Researchers in Electronics and Computing

This proceeding contains articles on the various research ideas of the academic community and practitioners presented at the international conference, “Women Researchers in Electronics and Computing” (WREC’2021). WREC'21 was organized in online mode by Dr. B R Ambedkar National Institute of Technology, Jalandhar (Punjab), INDIA during 22 – 24 April 2021. This conference was conceptualized with an objective to encourage and motivate women engineers and scientists to excel in science and technology and to be the role models for young girls to follow in their footsteps. With a view to inspire women engineers, pioneer and successful women achievers in the domains of VLSI design, wireless sensor networks, communication, image/ signal processing, machine learning, and emerging technologies were identified from across the globe and invited to present their work and address the participants in this women oriented conference. Conference Title: International Conference on Women Researchers in Electronics and ComputingConference Acronym: WREC'21Conference Date: 22–24 April 2021Conference Location: Online (Virtual Mode)Conference Organizers: Department of Electronics and Communication Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, INDI