Regeneration of Amman center — social acceptance of Syrian migrants in downtown Amman

Several studies discussed attitudes towards migrants; some of the issues pointed out are integration that requires interaction between migrants and the host society. Homogenous social groupings produce stronger communities. As the conflict in Syria entered its fifth year, Jordan hosted about 1.4 million registered Syrians, of whom 646,700 are informal refugees. Eighty-five percent of the refugees live outside camps in some of the poorest areas of Jordan. Consequently, new household’s typologies pressured the supply side. Such non-camp refugees’ migration patterns and housing market conditions formed ethnic homogeneous enclaves in different locations in Amman. Accordingly, non-camp refugees occupied and rented the upper floors of mixed used commercial buildings in downtown Amman. The present study investigated social acceptance of Syrian migrants residing in upper floors of commercial mixed used buildings located in the city center of Amman. The primary purpose of this research is to study how social acceptance of Syrian migrants is influenced by social gating. The hypothesis of the present study states that social acceptance of Syrian migrants in downtown Amman is influenced by sense of merchants’ sense of social gating. The significance of the study stems from that the development of downtown Amman with such rich social context can be informative and useful for strategic planners, local governments, NGO’s, social workers, and psychologists. This paper offers such an opportunity to reflect on an unfolding crisis that is of major social concern with changing urban demographics. The study was conducted using a quantitative and qualitative research strategy; an embedded research design was used. The quantitative method was conducted using a survey with downtown merchants, in addition to supportive qualitative methods of face-to-face interviews. The study was conducted in the central part of Amman, known locally as Wast Al-balad, which is considered the old commercial area that dates back to the second quarter of the twentieth century. Some of these secondary residential units became spaces (enclaves) for migrants that formed ethnic low-income enclaves. In the last five years, low-income Syrian migrants started to rent these units in Amman’s urban center. Outcomes indicated that social cohesion is the strongest motivator for acceptance of outsiders by the local merchants to reside in the upper floors of the commercial buildings of Downtown Amman area

Selection and parallel trends

One of the perceived advantages of difference-in-differences (DiD) methods is that they do not explicitly restrict how units select into treatment. However, when justifying DiD, researchers often argue that the treatment is "quasi-randomly" assigned. We investigate what selection mechanisms are compatible with the parallel trends assumptions underlying DiD. We derive necessary conditions for parallel trends that clarify whether and how selection can depend on time-invariant and time-varying unobservables. Motivated by these necessary conditions, we suggest a menu of interpretable sufficient conditions for parallel trends, thereby providing the formal underpinnings for justifying DiD based on contextual information about selection into treatment. We provide results for both separable and nonseparable outcome models and show that this distinction has implications for the use of covariates in DiD analyses

Thermal performance of High-Efficiency Vortex (HEV) variants: reversed arrays configuration

Convective heat transfer in the Reversed Arrays configuration of the High-Efficiency Vortex (HEV) multifunctional heat exchanger is investigated. An experimental test section constituted of a tube equipped with inclined trapezoidal vortex generators with a constant-flux heating system is designed and constructed. In this configuration, the tab inclination is opposite to the flow direction. Interactions between the tabs and the flow generate coherent structures in the form of longitudinal counter-rotating streamwise vortices enhancing radial particle dispersion, mixing, and ultimately heat transport. The original configuration in which the tabs are inclined in the flow direction is also examined. Recent in-house hydrodynamic and thermal studies have been conducted showing the interest of these configurations in mixing and heat transfer applications. The experimental data are in good agreement with the numerical results. Local Nusselt numbers show an increasing tendency in the longitudinal direction with remarkable cross-sectional variations. Global analysis of convective heat transfer reveals the superiority of the Reversed Arrays. Energy expenditures are assessed through total pressure drop measurements. A comparative analysis based on the thermal enhancement factor and Colburn factor shows that the HEV is energetically less costly than other heat exchangers with similar heat transfer capacity

Transport phenomena in chaotic flows: flux recombination HEX reactors

Rapid transport of heat and mass is required in many industrial processes. Mixing is a fundamental issue in chemical engineering applications and when exothermic reactions are involved, heat transfer capabilities of reactors and static mixers become an advantage and a necessity to ensure stable operating conditions and security standards. Enhancement of mixing and heat exchange is possible through turbulence, but vortical structures are often not feasible for highly viscous, non-Newtonian or shear sensitive fluids such as emulsions, pastes and slurries common in pharmaceutical, cosmetic and food industries. An alternative to improve transport within such materials is chaotic advection, where Lagrangian chaotic structures are induced by physical means in low-Reynolds laminar flows. Microfluidics is an increasingly active domain in which small dimensions and velocities render turbulent mixing extremely hard. Mixing by diffusion is one solution where topological mixing schemes exploiting the laminarity the flow to repeatedly fold the flow and exponentially increase the concentration gradients to obtain fast and efficient mixing by diffusion. This paper presents the first results of a study investigating laminar and turbulent mixing qualities of a Flux Recombination Hex reactor by using the chemical probe method. The geometry, exploiting a three-dimensional, steady flow configuration intended to mimic the baker’s map and enhance mixing by chaotic advection. First proposed by Chen & Meiners [1] for a microfluidic chip, it is here reproduced for investigation purposes using a stratified multiple plate manufacturing technique on a mini-scale where laminar and slightly turbulent regimes can be assessed

Kinematic mixing and heat transfer enhancement in chaotic split-and-recombine heat exchangers/reactors

Small system dimensions, low fluid velocity and high viscosity are all factors that hinder the production of turbulence. Enhancing mixing and heat transfer under these conditions, while keeping sufficient residence times and moderate pressure drops, constitutes a real challenge. Adapted to low-Reynolds flow regimes, Split-And-Recombine (SAR) static mixer and heat exchanger configurations are designed to exploit flow energy to produce chaotic advection and promote diffusion at the molecular level. The present work explores the hydrodynamic and thermal character of the SAR flow and compares, through CFD simulations, two such geometries namely SAR-1 and SAR-2, with two other reference configurations: a square three-dimensional continuous flow geometry (3D-Flow) and a plain square channel. Efficient convective heat transfer is achieved in deeply laminar creeping flow. Relative enhancements up to 1700% can be achieved compared to plain square channel flow, with a moderate increase in the pressure drop that does not exceed 17% for the SAR-2 configuration showing the better performance

Data Dependent Randomized Smoothing

Randomized smoothing is a recent technique that achieves state-of-art performance in training certifiably robust deep neural networks. While the smoothing family of distributions is often connected to the choice of the norm used for certification, the parameters of these distributions are always set as global hyper parameters independent of the input data on which a network is certified. In this work, we revisit Gaussian randomized smoothing and show that the variance of the Gaussian distribution can be optimized at each input so as to maximize the certification radius for the construction of the smoothed classifier. This new approach is generic, parameter-free, and easy to implement. In fact, we show that our data dependent framework can be seamlessly incorporated into 3 randomized smoothing approaches, leading to consistent improved certified accuracy. When this framework is used in the training routine of these approaches followed by a data dependent certification, we achieve 9\% and 6\% improvement over the certified accuracy of the strongest baseline for a radius of 0.5 on CIFAR10 and ImageNet.Comment: First two authors contributed equally to this wor

Self-assembly routes towards creating superconducting and magnetic arrays

Using self-assembly from colloidal suspensions of polystyrene latex spheres we prepared well-ordered templates. By electrochemical deposition of magnetic and superconducting metals in the pores of such templates highly ordered magnetic and superconducting anti-dot nano-structures with 3D architectures were created. Further developments of this template preparation method allow us to obtain dot arrays and even more complicated structures. In magnetic anti-dot arrays we observe a large increase in coercive field produced by nanoscale (50–1000nm) holes. We also find the coercive field to demonstrate an oscillatory dependence on film thickness. In magnetic dot arrays we have explored the genesis of 3D magnetic vortices and determined the critical dot size. Superconducting Pb anti-dot arrays show pronounced Little-Parks oscillations in Tc and matching effects in magnetization and magnetic susceptibility. The spherical shape of the holes results in significantly reduced pinning strength as compared to standard lithographic samples. Our results demonstrate that self-assembly template methods are emerging as a viable, low cost route to prepare sub-micron structures

Mixing performance in Split-And-Recombine Milli-Static Mixers—A numerical analysis

Heat recovery is the reutilization of lavished thermal energy. This paper proposes a hybrid heat recovery system that utilizes exhaust gases of a generator to heat water and produce electricity using thermoelectric generators. The system is composed of a concentric tank with a copper tube passing through it. At the inner surface of the tube, a layer of TEGs is located. The main purpose of the paper is to study the effect of changing the load of the generator on the water temperature and power generated. Knowing that 100 TEGs are utilized, results show that 47 °C hot water and 141 W are produced when load is 10 kW. It increases to 97 °C hot water and 1412 W when the generator load is 38 kW (14.12 W per TEG)

Real-Time PCR Quantification of Metallothionein Gene Expression in Sprague–Dawley Rats Chronically Exposed to Cd

Toxicologic impact of Cd leads to multiple human pathologic conditions, and its effect on humans and animals has been extensively studied. Physiologic function of metallothionein (MT1) is not completely understood, but it is mainly associated with detoxification of Cd and Hg. Elevated synthesis of MT1 exposed to metals has been observed but data on quantitation in various tissues is limited. We measured MT1 levels in peripheral blood and tissue samples of rats exposed to CdCl2. The objective is to investigate the effect of chronic exposure of Cd on peripheral blood and tissue-specific expression of MT1. This will provide information of MT1 gene transcription regulation and its impact on the heavy metal detoxification process. Rats raised in our animal facility were assigned to 8 experimental groups. Daily dose of 15 mg/ kg body weight CdCl2 in drinking water was administered for 8 wk. The control group received tap water free of Cd. Peripheral blood samples collected at 4 occasions (week 2, 4, 6, and 8) in EDTA tubes by retroorbital bleeding procedure. Liver and kidney tissue samples were collected and weighed. Total RNA/cDNA was prepared and quantified according to manufacturer’s protocol. Premade MT1 gene expression assay was used while β-actin gene was the endogeneous control. Results from week 2 and 4 showed the trend of upregulation of MT1 gene (fold increase) while the sample from all the other occasions showed downregulated response of MT1. Week 4 sample showed the fold increase of 1.11 times compared to week 2 increase of 1.04. Though the recorded 1.1-fold difference in the gene expression is not high, it gives an indication that there was an induction of MT1 gene. The downregulated pattern of MT1 gene might be due to the overaccumulation of repressor apothionein protein which stops MT1 transcription. When the metal binds to the promoter region of the MT1 gene-repressor protein, it becomes inactive and increases the MT1 transcription, but at the same time accumulation of repressor protein downregulates MT1 gene. Our observations suggest that chronic Cd exposure elicits an elevated MT1 gene expression which in turn leads to detoxification. More elaborative study is warranted for further understanding of MT1 gene expression

SynthCLIP: are we ready for a fully synthetic CLIP training?

We present SynthCLIP, a novel framework for training CLIP models with entirely synthetic textimage pairs, significantly departing from previous methods relying on real data. Leveraging recent text-to-image (TTI) generative networks and large language models (LLM), we are able to generate synthetic datasets of images and corresponding captions at any scale, with no human intervention. With training at scale, SynthCLIP achieves performance comparable to CLIP models trained on real datasets. We also introduce SynthCI-30M, a purely synthetic dataset comprising 30 million captioned images. Our code, trained models, and generated data are released at: https://github.com/ hammoudhasan/SynthCLIP