Synthesizing efficacious genistein in conjugation with superparamagnetic Fe₃O₄ decorated with bio-compatible carboxymethylated chitosan against acute leukemia lymphoma

Abstract Background Genistein (C15H10O5) is a soy isoflavone with anti-cancer properties such as inhibition of cell growth, proliferation and tumor invasion, but effective dosage against hematopoietic malignant cells was not in non-toxic range. This property cause to impede its usage as chemotherapeutic agent. Therefore, this hypothesis raised that synthesizing biocompatible nanoparticle could assist to prevail this struggle. Methods Genistein covalently attached on Fe3O4 nanoparticles decorated with carboxymethylated chitosan to fabricate Fe3O4-CMC-genistein in alkaline circumstance. This obtained nanoparticles were evaluated by TEM, DLS, FTIR, XRD and VSM and its anti-cancer effect by growth rate and MTT assays as well as flow cytometer on ALL cancer cell lines. Results Different evaluations indicated that the drug delivery vehicle had a mean diameter size around 12ƞm with well bounded components. This system presented high degree of magnetization and superparamagnetic properties as well as good water solubility. In comparison with pure genistein, significant growth inhibition on hematopoietic cancer cells in lower dose of genistein nano-conjugated onto Fe3O4-CMC. It increased long lasting effect of genistein in cancer cells also. Conclusion This delivery system for genistein could be remarkably promised and futuristic as biocompatible chemotherapeutic agent against hematopoietic malignant cells

Role of slanted reinforcement on bending capacity SS beams

The wide application range of simply supported beams in building construction, has always caused an attraction to somehow increase their bending capacity with high ductility. In this research, for the very purpose, the reinforcement bars under compression are bent at 45° from 1/3 of the beam length from the two ends and led to the tension zone. A sealed rubber tube of diameter twice that of the reinforcement bar covers the slanted part to separate it from the beam’s concrete. This will in fact reduce the stress intensity created in the bars above and below the neutral plane and increase the beam’s bending capacity considerably through making the two tensile and compressive forces acting opposite to each other. Actually, the proposed system can be specified by applying a superposition of the sum of the effects of the compressive stresses of the reinforcement bars above the beam’s 1/3 ends plus the sum of the effects of the tensile stresses created at 1/3 of the beam midpoint. The compressive stress created in the upper part tends to pass through the slanted part and reach the tensile part, and an opposite act for the tensile stress created in the lower part. Therefore, it is obvious that a compressive force found by the solution of the first superposition equation is applied at the middle 1/3 of the lower part and causes up to 25 % increase in the beam bending capacity

REFER: An End-to-end Rationale Extraction Framework for Explanation Regularization

Human-annotated textual explanations are becoming increasingly important in Explainable Natural Language Processing. Rationale extraction aims to provide faithful (i.e., reflective of the behavior of the model) and plausible (i.e., convincing to humans) explanations by highlighting the inputs that had the largest impact on the prediction without compromising the performance of the task model. In recent works, the focus of training rationale extractors was primarily on optimizing for plausibility using human highlights, while the task model was trained on jointly optimizing for task predictive accuracy and faithfulness. We propose REFER, a framework that employs a differentiable rationale extractor that allows to back-propagate through the rationale extraction process. We analyze the impact of using human highlights during training by jointly training the task model and the rationale extractor. In our experiments, REFER yields significantly better results in terms of faithfulness, plausibility, and downstream task accuracy on both in-distribution and out-of-distribution data. On both e-SNLI and CoS-E, our best setting produces better results in terms of composite normalized relative gain than the previous baselines by 11% and 3%, respectively

Comparative Study of Attorney's Intervention in Pre-Trial Stage and Its Influence on Fair Judgment in Iran and the United States of America

In the legal system of Iran and United States of America Attorney possesses the most important position in the Criminal Procedure. This position in Iran and United States of Americaplays a key role in the pre-trial stage. Legal system in the United States of America is called “common law”, and Criminal Procedure in this system is “adversarial”. The court does not exist in this system. Iran's legal system which is almost similar to the French system, has the court body. Despite this difference, in the two criminal justice systems, there are similarities within the pre-trial arrangements (Yousefi, 2011). Therefore, in this study, the influence ofattorney’s intervention in pre-trial stage, on three elements of the most important principles of a fair trial, including the principle of neutrality, equality of arms, not giving judicative role to a pursued person have been reviewed. Finally, it was found that attorney's intervention in the preliminary investigation can have negative effects on the principles of fair trial

Optimal Design of Passive and Active Control Systems in Seismic-excited Structures Using a New Modified TLBO

Vibration control devices have recently been used in structures subjected to wind and earthquake excitations. The optimal design problems of the passive control device and the feedback gain matrix of the controller for the seismic-excited structures are some attractive problems for researches to develop optimization algorithms with the advancement in terms of simplicity, accuracy, speed, and efficacy. In this paper, a new modified teaching–learning-based optimization (TLBO) algorithm, known as MTLBO, is proposed for the problems. For some benchmark optimization functions and constrained engineering problems, the validity, efficacy, and reliability of the MTLBO are firstly assessed and compared to other optimization algorithms in the literature. The undertaken statistical indicate that the MTLBO performs better and reliable than some other algorithms studied here. The performance of the MTLBO will then be explored for two passive and active structural control problems. It is concluded that the MTLBO algorithm is capable of giving better results than conventional TLBO. Hence, its utilization as a simple, fast, and powerful optimization tool to solve particular engineering optimization problems is recommended

An Efficient Entropy-Based Method for Reliability Assessment by Combining Kriging Meta-Models

Meta-models or surrogate models are convenient tools for reliability assessment of problems with time-consuming numerical models. Recently, an adaptive method called AK-MCS has been widely used for reliability analysis by combining Mont-Carlo simulation method and Kriging surrogate model. The AK-MCS method usually uses constant regression as a Kriging trend. However, other regression trends may have better performance for some problems. So, a method is proposed by combining multiple Kriging meta-models with various trends. The proposed method is based on the maximum entropy of predictions to select training samples. Using multiple Kriging models can reduce the sensitivity to the regression trend. So, the propped method can have better performance for different problems. The proposed method is applied to some examples to show its efficiency

Intelligent Decentralized Adaptive Controller Design for a Class of Large Scale Nonlinear Non-affine Systems: Nonlinear Observer-based Approach

Abstract: In this study, an observer based decentralized Fuzzy Adaptive Controller (FAC) is designed for a class of large scale non-affine nonlinear systems with unknown functions of the subsystems and interactions. The proposed controller has the following main characteristics: 1) On-line adaptation of both controller and observer parameters, 2) stabilization of the closed loop system, 3) convergence of both tracking and observer errors to zero, 4) boundedness of all signals involved, 5) being prone to employing experts' knowledge in controller design procedure, 6) chattering avoidance. An illustrative example is given to show the promising performance of the proposed method

COVID-19 associated acute transverse myelitis unresponsive to steroid therapy

A 63-year-old female presented to hospital with nausea, vomiting and abdominal pain. After primary evaluation, SARS-CoV-2 infection was suspected and confirmed via polymerase chain reaction (PCR) assay. She was started on broad spectrum antibiotics and remdesivir. After 12 days of hospitalization, she reported bilateral weakness and numbness of lower extremities and increased shortness of breath in the absence of fever. MRI with contrast was performed which showed intrinsic spinal cord lesion at the C7-T3 levels suggestive of transverse myelitis. She was started on IV steroids and was transferred to tertiary hospital for higher level of care. On neurological exam, there was an obvious reduction in the power of lower extremities and hyperreflexia was noted. Due to increasing weakness, MRI of cervical and thoracic spine was repeated and subsequently was started on Solu-Medrol 1-gram IV daily for 5 days. She was unresponsive to steroid therapy and refused plasmapheresis. Her course of hospitalization was complicated with acute on chronic renal failure and obstructive uropathy

Energy inputs – yield relationship and sensitivity analysis for tomato greenhouse production in Iran

This paper studies the energy balance between the input and the output energies per unit area for greenhouse tomato production.  For this purpose, the data on 30 tomato production greenhouses in Isfahan province, Iran were collected and analyzed.  The results indicated that a total specific input energy of 116,768.4 MJ ha-1 was consumed for tomato production.  Diesel fuel (with 40%) and chemical fertilizers and manure (with 30%) were amongst the highest input energies for tomato production.  The energy productivity was estimated to be 1.16 kg MJ-1.  The ratio of output energy to input energy was approximately 0.92. 19% and 81% of total energy input was in renewable and non-renewable forms, respectively.  The regression results revealed that the contribution of input energies on crop yield for human power, machinery, pesticides and electricity inputs was significant.  The human power energy had the highest impact (1.45) among the other inputs in greenhouse tomato production.  The marginal physical productivity of diesel fuel, seed and total chemical fertilizer with manure was negative.  It can be because of applying the inputs more than required or improperly applying.  The highest shares of expenses were found to be 34% and 21% for human power and total diesel fuel and machinery, respectively.  Cost analysis revealed that total cost of production for 1 ha greenhouse tomato production was around US$34939.  Accordingly, the benefit-cost ratio was estimated as 2.74.  Results of greenhouse gas emission indicated that tomato production is mostly depended on diesel fuel sources.  Diesel fuel had the highest share (2,719.98 kg CO2eq.ha-1) followed by electricity (729.6 kg CO2eq.ha-1) and nitrogen fertilizer (409.5 kg CO2eq.ha-1).   Keywords: tomato, greenhouse, energy productivity, economic analysis, Cobb-Douglas functio