Transformation of Public Spaces and Changing Pattern of Mobility in a Historic City, Case Study: Isfahan, Iran

Esfahan is one of the central and historic cities of Iran, which dates back to 2000 years ago. The city is enriched with crafts and folk art, which has lead to it being registered as part of the Creative Cities Network of UNESCO. The centerpiece of the city, NaghsheJahan Square, was inscribed as a UNESCO World Heritage Site in 1979, and it well represents the brand of the city Esfahan; its intricate mixture of historic architecture, viable urban space for work and recreation for its citizens, and a welcoming landmark on tourists’ maps. The variety of typologies used to build the urban spaces has lead to strong pedestrian patterns throughout a coherence network. Hence, these areas have a powerful potential to change structure, mobility patterns and people’s perception. In spite of this, in recent decades, new developments and urban changes such as mega malls and recreational sites have resulted in new poles in design and architecture in the outside areas of the urban city. This phenomenon is leading to movement of people, energy and resources as well as changes in life styles, the image of the city and its mobility patterns. The objective of this article is to further analyze and discuss how urban transformation and urban changes in a micro and macro scale affect the mobility pattern and pedestrian flow. In order to this, methodology used is based on analysis of literature and environment in two levels; first, urban transformation analysis based on public urban space’s typology and urban space analysis; and second, mobility patterns based on space character and pedestrian flows. The results show that emergence of structures such as megamalls City Center or Dreamland Project create daily driving flows, which decrease urban space’s perception. In conclusion, in historic cities, such as Esfahan, urban changes should be planned and centered around its historic fabric, and public urban spaces should be designed and controlled with mobility’s patterns in mind

Detection of eight foodborne bacterial pathogens by oligonucleotide array hybridization

Background: Simultaneous and rapid detection of multiple foodborne bacterial pathogens is important for the prevention of foodborne illnesses. Objective: The aim of this study was to evaluate the use of 16S rDNA and 23S rDNA sequences as targets for simultaneous detection of eight foodborne bacterial pathogens. Methods: Nineteen bacterial oligonucleotide probes were synthesized and applied to nylon membranes. Digoxygenin labeled 16S rDNA and 23S rDNA from bacteria were amplified by PCR using universal primers, and the amplicons were hybridized to the membrane array. Hybridization signals were visualized by NBT/BCIP color development. Results: The eight intestinal bacterial pathogens including Salmonella enterica, Escherichia coli, Bacillus cereus, Vibrio cholerae, Shigella dysenteriae, Staphylococcus aureus, Listeria monocytogenes, and Enterococcus faecalis were appropriately detected in a panel of oligonucleotide array hybridization. The experimental results showed that the method could discriminate the bacterial pathogens successfully. The sensitivity of oligonucleotide array was 103 CFU/ml. Conclusion: This study showed that 16S rDNA and 23S rDNA genes had sufficient sequence diversity for species identification and were useful for monitoring the populations of foodborne pathogenic bacteria. Furthermore, results obtained in this study revealed that oligonucleotide array hybridization had a powerful capability to detect and identify the bacterial pathogens simultaneously

Synthesis, Characterization and in Vitro Antibacterial Activities of CdO Nanoparticle and Nano-sheet Mixed-ligand of Cadmium(ІІ) Complex

Here, we report the synthesis of a Schiff-base mixed-ligand complex of cadmium(ІІ) in bulk and nano-scales via the precipitation and sonochemical methods, respectively. The complex formula is [Cd(3-bpdh)(3-bpdb)Cl2]n (1), where the ligands are 3-bpdh = 2,5-bis(3-pyridyl)-3,4-diaza-2,4-hexadiene and 3-bpdb = 1,4-bis(3-pyridyl)-2,3-diaza-1,3-butadiene. The structure of mixed-ligand complex (1) was characterized by IR, 1H NMR and elemental analyses. Cadmium(ІІ) oxide nanoparticles were prepared by direct thermolysis from nanosheet of complex (1). The cadmium(ІІ) oxide structure was characterized by X-ray Diffraction (XRD) and Energy Dispersive X-ray  analyses (EDAX). Size, morphology and structural dispersion of all obtained nanostructures were characterized by Scanning Electron Microscopy (SEM). The Schiff-base ligands, bulk and nano-scales of complex (1) and cadmium(ІІ) oxide nanoparticles were analyzed for antibacterial activities against Bacillus alvei (bacteria causing the honey bee European foulbrood disease). The Minimum Inhibitory Concentrations (MIC) has been shown moderate antibacterial activities compared with some other standard drugs. Known antibiotics like penicillin and SXT (Trimethoprim/sulfamethoxazole) were used as positive control

Zingiber officinale (Ginger) as a treatment for inflammatory bowel disease: A review of current literature

Inflammatory bowel disease (IBD) is a term used for a variety of conditions involving persistent inflammation of the digestive system. Ulcerative colitis (UC) and Crohn’s disease (CD) are examples of IBD. There were some treatments like Amino salicylates, glucocorticoids, immunosuppressants, antibiotics, and surgery which have been used for treating IBD. However, the short and long-term disabling adverse effects, like nausea, pancreatitis, elevated liver enzymes, allergic reactions, and other life-threatening complications remain a significant clinical problem. On the other hand, herbal medicine, believed to be safer, cheaper, and easily available, has gained popularity for treating IBD. Nowadays, Ginger, the Rizhome of Z. officinale from the Zingiberaceae family, one of the most commonly used fresh spices and herbs, has been proposed as a potential option for IBD treatment. According to upper issues, IBD treatment has become one of the society’s concerns. So, this review aims to summarize the data on the yin and yang of ginger use in IBD treatment

Numerical Solution of Ill-posed Cauchy Problems for Parabolic Equations

Ill-posed mathematical problem occur in many interesting scientific and engineering applications. The solution of such a problem, if it exists, may not depend continuously on the observed data. For computing a stable approximate solution it is necessary to apply a regularization method. The purpose of this thesis is to investigate regularization approaches and develop numerical methods for solving certain ill-posed problems for parabolic partial differential equations. In thermal engineering applications one wants to determine the surface temperature of a body when the surface itself is inaccessible to measurements. This problem can be modelled by a sideways heat equation. The mathematical and numerical properties of the sideways heat equation with constant convection and diffusion coefficients is first studied. The problem is reformulated as a Volterra integral equation of the first kind with smooth kernel. The influence of the coefficients on the degree of ill-posedness are also studied. The rate of decay of the singular values of the Volterra integral operator determines the degree of ill-posedness. It is shown that the sign of the coefficient in the convection term influences the rate of decay of the singular values. Further a sideways heat equation in cylindrical geometry is studied. The equation is a mathematical model of the temperature changes inside a thermocouple, which is used to approximate the gas temperature in a combustion chamber. The heat transfer coefficient at the surface of thermocouple is also unknown. This coefficient is approximated via a calibration experiment. Then the gas temperature in the combustion chamber is computed using the convection boundary condition. In both steps the surface temperature and heat flux are approximated using Tikhonov regularization and the method of lines. Many existing methods for solving sideways parabolic equations are inadequate for solving multi-dimensional problems with variable coefficients. A new iterative regularization technique for solving a two-dimensional sideways parabolic equation with variable coefficients is proposed. A preconditioned Generalized Minimum Residuals Method (GMRS) is used to regularize the problem. The preconditioner is based on a semi-analytic solution formula for the corresponding problem with constant coefficients. Regularization is used in the preconditioner as well as truncating the GMRES algorithm. The computed examples indicate that the proposed PGMRES method is well suited for this problem. In this thesis also a numerical method is presented for the solution of a Cauchy problem for a parabolic equation in multi-dimensional space, where the domain is cylindrical in one spatial direction. The formal solution is written as a hyperbolic cosine function in terms of a parabolic unbounded operator. The ill-posedness is dealt with by truncating the large eigenvalues of the operator. The approximate solution is computed by projecting onto a smaller subspace generated by the Arnoldi algorithm applied on the inverse of the operator. A well-posed parabolic problem is solved in each iteration step. Further the hyperbolic cosine is evaluated explicitly only for a small triangular matrix. Numerical examples are given to illustrate the performance of the method

Numerical Solution of Ill-posed Cauchy Problems for Parabolic Equations

Ill-posed mathematical problem occur in many interesting scientific and engineering applications. The solution of such a problem, if it exists, may not depend continuously on the observed data. For computing a stable approximate solution it is necessary to apply a regularization method. The purpose of this thesis is to investigate regularization approaches and develop numerical methods for solving certain ill-posed problems for parabolic partial differential equations. In thermal engineering applications one wants to determine the surface temperature of a body when the surface itself is inaccessible to measurements. This problem can be modelled by a sideways heat equation. The mathematical and numerical properties of the sideways heat equation with constant convection and diffusion coefficients is first studied. The problem is reformulated as a Volterra integral equation of the first kind with smooth kernel. The influence of the coefficients on the degree of ill-posedness are also studied. The rate of decay of the singular values of the Volterra integral operator determines the degree of ill-posedness. It is shown that the sign of the coefficient in the convection term influences the rate of decay of the singular values. Further a sideways heat equation in cylindrical geometry is studied. The equation is a mathematical model of the temperature changes inside a thermocouple, which is used to approximate the gas temperature in a combustion chamber. The heat transfer coefficient at the surface of thermocouple is also unknown. This coefficient is approximated via a calibration experiment. Then the gas temperature in the combustion chamber is computed using the convection boundary condition. In both steps the surface temperature and heat flux are approximated using Tikhonov regularization and the method of lines. Many existing methods for solving sideways parabolic equations are inadequate for solving multi-dimensional problems with variable coefficients. A new iterative regularization technique for solving a two-dimensional sideways parabolic equation with variable coefficients is proposed. A preconditioned Generalized Minimum Residuals Method (GMRS) is used to regularize the problem. The preconditioner is based on a semi-analytic solution formula for the corresponding problem with constant coefficients. Regularization is used in the preconditioner as well as truncating the GMRES algorithm. The computed examples indicate that the proposed PGMRES method is well suited for this problem. In this thesis also a numerical method is presented for the solution of a Cauchy problem for a parabolic equation in multi-dimensional space, where the domain is cylindrical in one spatial direction. The formal solution is written as a hyperbolic cosine function in terms of a parabolic unbounded operator. The ill-posedness is dealt with by truncating the large eigenvalues of the operator. The approximate solution is computed by projecting onto a smaller subspace generated by the Arnoldi algorithm applied on the inverse of the operator. A well-posed parabolic problem is solved in each iteration step. Further the hyperbolic cosine is evaluated explicitly only for a small triangular matrix. Numerical examples are given to illustrate the performance of the method

Effekter av tidiga och sena godståg

Förseningsbidrag, kritiska störningar och småförseningar är nya mätetal som skapats för att förtydliga sambandet mellan störningar under ett tågs färd och dess slutliga punktlighet. I denna rapport beskriver vi dels hur man kan generalisera de nya mätetalen till att kunna appliceras på godståg som ofta är före tidtabellen. Resultat visar att för att öka punktligheten för godståg är det också viktigt att beakta de delar av resorna då tågen ligger före sin tidtabell, eftersom tappad tid även då kan göra att tågen till slut ”trillar över punktlighetskanten’’. Vidare belyser vi hur de tidiga (och sena) godstågen påverkar andra tåg genom en fallstudie på Godsstråket Mjölby-Luleå för tåg under oktober 2019, och resultaten indikerar att de tidiga tågen inte bidrar till opunktlighet utan de nyttjas i operativ trafik för att prioritera andra tåg för att snabba upp andra tågs resor.Delay contribution, critical disturbances and minor delays are new metrics created to clarify the connection between disturbances during a train's journey and its punctuality. In this report, we describe how to generalize these new metrics and apply them to freight trains, which are often ahead of their timetable. Results show that to increase punctuality for freight trains, it is also important to consider the parts of the journey when the trains are before their timetable, since prolonged travel-time also when trains are before timetable can cause the trains to eventually "fall over the punctuality edge". Furthermore, we shed light on how the early (and late) freight trains affect other trains through a case study on the Mjölby-Luleå line in October 2019, and the results indicate that early trains do not contribute to delays on other trains but are utilized to prioritize other trains to speed up their travel-time

A Preconditioned GMRES Method for Solving a 1D Sideways Heat Equation

The sideways Heat equation (SHE) is a model of the problem of determining the temperature on the surface of a body from the interior measurements. Mathematically it can be formulated as a non-characteristic Cauchy problem for a  parabolic partial differential equation. This problem is severely ill-posed: the solution does not depend continuously on the data. We use a preconditioned Generalized Minimum Residuals Method (GMRES) to solve a 1D SHE. Regularization is used in the preconditioner as well as truncating the GMRES algorithm. Numerical experiments demonstrate that the proposed method works well

Solving an Ill-Posed Cauchy Problem for a Two-Dimensional Parabolic PDE with Variable Coefficients Using a Preconditioned GMRES Method

The sideways parabolic equation (SPE) is a model of the problem of determiningthe temperature on the surface of a body from the interior measurements. Mathematically it can beformulated as a noncharacteristic Cauchy problem for a parabolic partial differential equation. Thisproblem is severely ill-posed in an L2 setting. We use a preconditioned generalized minimum residualmethod (GMRES) to solve a two-dimensional SPE with variable coefficients. The preconditioner issingular and chosen in a way that allows efficient implementation using the FFT. The preconditioneris a stabilized solver for a nearby problem with constant coefficients, and it reduces the numberof iterations in the GMRES algorithm significantly. Numerical experiments are performed thatdemonstrate the performance of the proposed method

Prediction of academic procrastination based on personality traits with mediator role of self regulation skills

Procrastination refers to the practice of carrying out less urgent tasks or doing pleasurable things in place of more urgent ones, thus putting off impending tasks to a later time. Many studies have addressed the effects of contextual factors and personality traits on procrastination.  The purpose of this study was to predict procrastination based on personality traits with mediating role of self-regulation learning strategies. To do this, 320 students (170 males and 150 females) were selected randomly through multistage cluster sampling among tehran university. The data collection was done through 3 different scales: Solomon & Rathblom procrastination assessment scale-student (PASS), Goldberg Personality scale, and self-regulation learning strategies. These instruments showed appropriate reliability and validity. Path analysis was the major statistical operation run in the study. The results by path analysis technique showed that the relationship between Personality and procrastination was influenced by self-regulation learning strategies. Neuroticism and extraversion had positive direct and indirect effects on procrastination. In addition, conscientiousness and openness to experience had negative direct and indirect effects on procrastination. Cognitive strategies and meta cognitive strategies had negative effects on procrastination. In summary, the results showed that self-regulation learning strategies could have a mediator role in the relationship between personality traits and procrastination. This model provides a good pattern for explaining academic procrastination, which parents, teachers and counselors could use for decreasing academic procrastination