Modern (theoretical) PHYSICS seems to be in deep crisis today as many of its core aspects are not empirically well-confirmed. Heated exchanges among physicists on the scientific status of physical theories with little or, at best, a tenuous connection to possible experimental tests is highly visible in the popular scientific literature. Some physicists (e.g., Carroll 2014, 2019; Ijjas et al., 2017) argue that science must discard empirical testability as one of its defining properties and the highly explanatory theories of present-day PHYSICS should be exempted from experimental testing, while others (e.g., Ellis & Silk 2014) spot in these arguments (for softening the testability or falsifiability requirement for modern PHYSICS) a dangerous tendency to undermine science. The philosopher of science who naturally draws most attention in these current debates is Karl Popper (1902-1994). His views, however, are often misrepresented in these debates. The prime objective of this paper is to explain how a more enlightened perspective on the ongoing debates can be obtained by a careful scrutiny of the Popperian criterion of falsifiability. As a first step in achieving this objective we will analyze the two major (conceptual) failures on which the current controversies rest. Our next step will be examining the controversial string theory to see whether the criteria of falsifiability is a ‘blunt instrument’ for determining its scientific status.

Background: Atherosclerosis is a common cardiovascular disease; many factors are effective on its occurrence. There are derangements in lipoprotein and lipid and enzyme level like as (APO)A, (APO)B, (APO)J and (APO)E. (APO)E and (APO)B level assessment and relationship between these lipoproteins and atherosclerosis was investigated to help us, better diagnosis and predication of atherosclerosis related problems. Materials and Methods: A case - control study was performed in cardiology department (Taleghani hospital, Shaheed Beheshti -University), which included 25 atherosclerosis patients and 25 healthy people as control group ( at the range of 35-70 years old) and age, weight, smoking matched. We obtained 6 ml of venous blood from each one and after serum removal, (APO)E and (APO)B level was measured by ELISA method in endocrine and methabolism research center lab. Results: Mean (APO)B level in case group was 1.45 glL and 0.76 mg/L in control group. Mean (APO)E level in case group was 32.5 mg/Lit and 35.4 mg/L in control group. Difference in weight, age, blood pressure between case and control group was not important from statistical point of view The difference between case and control groups for (APO)B was 0.68 (P<0.01) and for (APO)E was 2.9 (P=0.46), the findings that measured are meaningful just for (APO)B trom statistical point of view.Conclusions: Although we consider difference between case and control groups in (APO)B and (APO)E level, and just difference in (APO)B level was considerable from statistical point of view. Former investigations also confirmed the relationship between (APO)B and atherosclerosis. But just some investigations show the relationship between atherosclerosis and (APO)E. These findings depend on different alleles. Therefore, that the increased level of (APO)E is a nonspecific factor for atherosclerosis process, and more investigations are necessary.

In this paper, recommended spiral passive micromixer was designed and simulated. spiral design has the potential to create and strengthen the centrifugal force and the secondary flow. A series of simulations were carried out to evaluate the effects of channel width, channel depth, the gap between loops, and flowrate on the micromixer performance. These features impact the contact area of the two fluids and ultimately lead to an increment in the quality of the mixture. In this study, for the flow rate of 25 μl/min and molecular diffusion coefficient of 1×10-10 m2/s, mixing efficiency of more than 90% is achieved after 30 (approximately one-third of the total channel length). Finally, the optimized design fabricated using proposed 3D printing method.

Application of the network equivalent concept for external system representation for power system transient analysis is well known. However, the challenge to utilize an equivalent network, approximated by a rational function, is to guarantee the passivity of the corresponding model. In this regard, special techniques are required to enforce the passivity of the equivalent model through a post processing approach that minimizes its impact on the original model characteristics. In this paper, the passivity is enforced by expressing the problem in terms of a convex OPTIMIZATION problem that guarantees the global optimal solution. The convex OPTIMIZATION problem is efficiently solved by recently developed numerical interior–point methods. This passivity enforcement is also global which indicates that the passivity enforcement in one region does not lead to passivity violation in other regions.

Summary It is necessary to have enough data from a reservoir to predict its performance and develop it as accurate as possible. Nowadays, it is a common practice to combine direct and indirect methods to achieve the optimal process of data gathering while considering time, cost and precision. Empirical relationships and OPTIMIZATION algorithms are the two most used indirect methods and recently, numerous researches have focused on the latter one. One of the newest and most powerful OPTIMIZATION algorithms is ARTIFICIAL bee colony (ABC) algorithm. In this paper, we have explained its application for reservoir characterization by estimating shear wave velocity (Vs) using some series of recorded well logs. We have carried out a study on a sandstone and a carbonate reservoir using the ABC algorithm and Greenberg-Castagna relationships. We have chosen three logs among the available ones and used a polynomial to derive their relationship with Vs. In both cases, the ABC has acted more efficiently, indicating that it can be employed to estimate Vs in reservoirs with the lithology similar to the one in our cases when we have no recorded data...

The problem of assigning locomotives to trains consists of determining the number of locomotives of different types that provide sufficient power to pull trains on fixed schedules. The objective is to minimize the fixed and operational locomotive costs. The locomotive assignment problem is defined for cyclic and non cyclic problems. In this paper, an approach using a genetic algorithm and a neural network algorithm is presented to find a cyclic solution on a one-week horizon, while satisfying the power demands of all trains. This system was tested using realistic data from the Canadian National (C.N.) North America Company with about 1600 trains and 1300 locomotives.

Software testing is a crucial step in the development of software that guar-antees the dependability and quality of software products. A crucial step in software testing is test case minimization, which seeks to minimize the number of test cases while ensuring maximum coverage of the system being tested. It is observed that the existing algorithms for test case minimization still suffer in efficiency and precision. This paper proposes a new optimiza-tion algorithm for efficient test case minimization in software testing. The proposed algorithm is designed on the base parameters of the metaheuristic algorithms, inspired by scientific principles. We evaluate the performance of the proposed algorithm on a benchmark suite of test cases from the literature. Our experimental results show that the proposed algorithm is highly effective in reducing the number of test cases while maintaining high coverage of the system under test. The algorithm outperforms the existing OPTIMIZATION algorithms in terms of efficiency and accuracy. We also con-duct a sensitivity analysis to investigate the effect of different parameters on the performance of the proposed algorithm. The sensitivity analysis results show that the performance of the algorithm is robust to changes in the parameter values. The proposed algorithm can help software testers reduce the time and effort required for testing while ensuring maximum coverage of the system under test.

The purpose of this study is to reduce the temperature of the attic of the building of department of PHYSICS in university of Tehran. To achieve this goal, eighteen natural ventilators with the area of 0.25 m2 each were installed on the roof. The natural ventilators alone did not decrease the temperature significantly. To help natural ventilation, a laminar flow of air from the floors to the attic was provided. This led to a temperature decrease around 1.5 to 2o C. In addition, a powered ventilation was resulted 3 to 8o C temperature decrease. Since the volume (4533 m3) and area (1416 m2) of the attic are too large, further tests were conducted on two small models (47×33×51 cm3) of the attic, build from the same material as the main attic. The models were used to investigate the effect of covering the roof with aluminum foil and painting the roof with a withe color as a reflector, and installation of polystyrene panels under the roof as an insulator. Covering with aluminum foil, painting in withe, and installation of polystyrene resulted in 3-5, 2-3.5, and 1-2 degrees decrease in temperature, respectively. Reason of these changes was explained by reflection spectrum of UV-Vis-NIR spectrophotometry. Finally, the attic was simulated by the COMSOL MultiPHYSICS software. It showed that a temperature reduction of 10 degrees could be accomplished by installation of six fans as inlet in the gables, three in each gable. Each fan has to generate 4 m/sec air flow velocity.