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Comparative Area Studies (CAS) emerges as a new approach in which scholars of Latin American Studies engage systematically with scholars working on other world regions. Adopting a focus on intra-, inter- and cross area comparisons, CAS builds on the traditional strengths of area studies. At the same time it enables scholars to have a stronger impact on overarching conceptual debates and it may provide new bridges between area studies scholars and the academic communities in the regions studied. However, a comparative area studies approach requires systematic cooperation among scholars of different world regions, and adequate organizational and institutional structures to support them. Los Estudios Regionales Comparativos (Comparative Area Studies - CAS) surgen como un enfoque nuevo dentro del cual académicos de Estudios Latinoamericanos colaboran sistemáticamente con académicos que investigan sobre otras regiones del mundo. Tomando como punto de partida comparaciones intrarregionales, interregionales y transregionales, los ERC se basan en los puntos fuertes tradicionales de los estudios regionales. Al mismo tiempo, este enfoque permite a los académicos tener un impacto mayor en los debates conceptuales más amplios y puede tender nuevos puentes entre los académicos de estudios regionales y las comunidades académicas de las regiones estudiadas. Sin embargo, un enfoque de estudios regionales comparativos exige una cooperación sistemática entre académicos de distintas regiones del mundo y unas estructuras organizativas e institucionales adecuadas para apoyarles.

Contemporary processes of urbanisation present major challenges for urban research and theory as urban areas expand and interweave. In this process, urban forms are constantly changing and new urban configurations are frequently evolving. An adequate understanding of urbanisation must derive its empirical and theoretical inspirations from the multitude of urban experiences across the various divides that shape the contemporary world. New concepts and terms are urgently required that would help, both analytically and cartographically, to decipher the differentiated and rapidly mutating landscapes of urbanisation that are being produced today. One of the key procedures to address these challenges is the application of comparative strategies. Based on postcolonial critiques of urban theory and on the epistemologies of planetary urbanisation, this paper introduces and discusses the theoretical and methodological framework of a collaborative comparative study of urbanisation processes in eight large metropolitan territories across the world: Tokyo, Hong Kong/Shenzhen/Dongguan, Kolkata, Istanbul, Lagos, Paris, Mexico City and Los Angeles. In order to approach these large territories, a specific methodological design is applied mainly based on qualitative methods and a newly developed method of mapping. After the presentation of the main lines of our theoretical and methodological approach we discuss some of the new comparative concepts that we developed through this process: popular urbanisation, plotting urbanism, multilayered patchwork urbanisation and the incorporation of urban differences. 随着城市地区的扩大和相互交织，当代城市化进程给城市研宄和理论带来了重大挑战。在这个 过程中，城市形态不断变化，新的城市形态在不断演进。要充分理解城市化，我们必须从塑造 当代世界的大量纷纭歧出的城市经验中获得经验和理论层面的启发。如今正在产生的城市化格 局千差万别，并迅速变化，我们迫切需要新的概念和术语，在分析层面和图解层面帮助破译这 些格局。应对这些挑战的关键手段是应用比较策略。本文基于城市理论的后殖民批判和全域城 市化的认识论，介绍并讨论了对世界八大都市圈城市化进程进行协同比较研宄的理论和方法论 框架，这八大都市圈是：东京、香港/深圳/东莞、加尔各答、伊斯坦布尔、拉各斯、巴黎、墨 西哥城和洛杉矶。为着手探讨这些广大的都市圈，我们主要基于定性方法和新开发的测绘方法， 应用了一套特定的方法论设计。在介绍了我们主要的理论和方法论进路之后，我们讨论了在这 个过程中发展起来的一些新的比较概念：大众城市化、小块圈地式城市化、多层拼凑城市化以 及城市差异的纳入。

ABSTRACT BACKGROUND Depression contributes to disability and there are ethnic/racial disparities in access and outcomes of care. Quality improvement (QI) programs for depression in primary care improve outcomes relative to usual care, but health, social and other community-based service sectors also support clients in under-resourced communities. Little is known about effects on client outcomes of strategies to implement depression QI across diverse sectors. OBJECTIVE To compare the effectiveness of Community Engagement and Planning (CEP) and Resources for Services (RS) to implement depression QI on clients’ mental health-related quality of life (HRQL) and services use. DESIGN Matched programs from health, social and other service sectors were randomized to community engagement and planning (promoting inter-agency collaboration) or resources for services (individual program technical assistance plus outreach) to implement depression QI toolkits in Hollywood-Metro and South Los Angeles. PARTICIPANTS From 93 randomized programs, 4,440 clients were screened and of 1,322 depressed by the 8-item Patient Health Questionnaire (PHQ-8) and providing contact information, 1,246 enrolled and 1,018 in 90 programs completed baseline or 6-month follow-up. MEASURES Self-reported mental HRQL and probable depression (primary), physical activity, employment, homelessness risk factors (secondary) and services use. RESULTS CEP was more effective than RS at improving mental HRQL, increasing physical activity and reducing homelessness risk factors, rate of behavioral health hospitalization and medication visits among specialty care users (i.e. psychiatrists, mental health providers) while increasing depression visits among users of primary care/public health for depression and users of faith-based and park programs (each p  < 0.05). Employment, use of antidepressants, and total contacts were not significantly affected (each p  > 0.05). CONCLUSION Community engagement to build a collaborative approach to implementing depression QI across diverse programs was more effective than resources for services for individual programs in improving mental HRQL, physical activity and homelessness risk factors, and shifted utilization away from hospitalizations and specialty medication visits toward primary care and other sectors, offering an expanded health-home model to address multiple disparities for depressed safety-net clients.

Multi-criteria decision-making is important and it affects the efficiency of a mechanical processing process as well as an operation in general. It is understood as determining the best alternative among many alternatives. In this study, the results of a multi-criteria decision-making study are presented. In which, sixteen experiments on turning process were carried out. The input parameters of the experiments are the cutting speed, the feed speed, and the depth of cut. After conducting the experiments, the surface roughness and the material removal rate (MRR) were determined. To determine which experiment guarantees the minimum surface roughness and maximum MRR simultaneously, four multi-criteria decision-making methods including the MAIRCA, the EAMR, the MARCOS, and the TOPSIS were used. Two methods the Entropy and the MEREC were used to determine the weights for the criteria. The combination of four multi-criteria making decision methods with two determination methods of the weights has created eight ranking solutions for the experiments, which is the novelty of this study. An amazing result was obtained that all eight solutions all determined the same best experiment. From the obtained results, a recommendation was proposed that the multi-criteria making decision methods and the weighting methods using in this study can also be used for multi-criteria making decision in other cases, other processes.

Restoration programs require long-term monitoring and assessment of vegetation growth and productivity. Remote sensing technology is considered to be one of the most powerful technologies for assessing vegetation. However, several limitations have been observed with regard to the use of satellite imagery, especially in drylands, due to the special structure of desert plants. Therefore, this study was conducted in Kuwait’s Al Abdali protected area, which is dominated by a Rhanterium epapposum community. This work aimed to determine whether Unmanned Aerial Vehicle (UAV) multispectral imagery could eliminate the challenges associated with satellite imagery by examining the vegetation indices and classification methods for very high multispectral resolution imagery using UAVs. The results showed that the transformed difference vegetation index (TDVI) performed better with arid shrubs and grasses than did the normalized difference vegetation index (NDVI). It was found that the NDVI underestimated the vegetation coverage, especially in locations with high vegetation coverage. It was also found that Support Vector Machine (SVM) and Maximum Likelihood (ML) classifiers demonstrated a higher accuracy, with a significant overall accuracy of 93% and a kappa coefficient of 0.89. Therefore, we concluded that SVM and ML are the best classifiers for assessing desert vegetation and the use of UAVs with multispectral sensors can eliminate some of the major limitations associated with satellite imagery, particularly when dealing with tiny plants such as native desert vegetation. We also believe that these methods are suitable for the purpose of assessing vegetation coverage to support revegetation and restoration programs.

The coronavirus disease (COVID-19) outbreak in December has seen more than 76,000 cases in China, causing more than 3,000 medical staff infections. As the disease is highly contagious, can be fatal in severe cases, and there are no specific medicines, it poses a huge threat to the life and health of nurses, leading to a severe impact on their emotional responses and coping strategies. Therefore, this study will investigate nurses' emotional responses and coping styles, and conduct a comparative study with nursing college students. This study was conducted through the online survey 'questionnaire star' from February 1st to February 20th, 2020 in Anhui Province, using the snowball sampling method to invite subjects. The results found that women showed more severe anxiety and fear than men. Participants from cities exhibited these symptoms more than participants from rural areas, however rural participants experienced more sadness than urban participants. The nearer a COVID-19 zone is to the participants, the stronger the anxiety and anger. The COVID-19 outbreak has placed immense pressure on hospitals and those nurses at the frontline are more seriously affected. Hospitals should focus on providing psychological support to nurses and training in coping strategies.

Air pollution is an immense problem due to its detrimental health effects on human populations. This study investigates the distribution of particle-bound heavy metals and associated health risks in three diverse areas (Durgapur as an industrial complex, Kolkata as an urban area, and Bolpur as a semi-urban region) in West Bengal, India. Twenty-one (84 samples) sampling sites were chosen, covering industrial, traffic, residential, and sensitive zones. The respirable suspended particulate matter (RSPM) samples were collected using a portable Mini-Vol Tactical Air Sampler, and heavy metal concentrations (Cd, Cr, Mn, Ni, Pb, and As) were analyzed using ICP-OES. The non-carcinogenic and carcinogenic health risks were assessed using exposure concentration (EC), hazard quotient (HQ), hazard index (HI), and additional lifetime cancer cases. The results highlight variations in heavy metal concentrations across the regions, with industrial areas exhibiting higher levels. Principal component analysis (PCA) unveiled distinct metal co-variation patterns, reflecting sources such as industrial emissions, traffic, and natural contributors. The sum of non-carcinogenic risks (HI) of all heavy metals exceeded the US EPA’s risk limit (HI<1) in both Kolkata and Durgapur, except for Bolpur. Similarly, the sum of cancer risk in three distinct areas exceeded the USEPA limits (1.00E-06). The Monte Carlo simulation revealed the 5th and 95th percentile range of cancer risk was 9.12E-06 to 1.12E-05 in Bolpur, 3.72E-05 to 4.49E-05 in Durgapur and 2.13E-05 to 2.57E-05 in Kolkata. Kolkata had the highest additional lifetime cancer cases compared to Bolpur and Durgapur. This study provides information on the complex connections between heavy metal pollution and possible health risks in industrial, urban, and semi-urban regions.

We investigate the role of deeply rooted pre-colonial ethnic institutions in shaping comparative regional development within African countries. We combine information on the spatial distribution of ethnicities before colonization with regional variation in contemporary economic performance, as proxied by satellite images of light density at night. We document a strong association between pre-colonial ethnic political centralization and regional development. This pattern is not driven by differences in local geographic features or by other observable ethnic-specific cultural and economic variables. The strong positive association between pre-colonial political complexity and contemporary development also holds within pairs of adjacent ethnic homelands with different legacies of pre-colonial political institutions.

To evaluate the diagnostic ability of the ratio of anterior and posterior corneal surface areas (As/Ps) comparing with other keratoconus screening indices in distinguishing forme fruste keratoconus (FFKC) from normal eyes. In this comparative study, 13 eyes of 13 patients with FFKC, 29 eyes of 29 patients with keratoconus (KC) and 88 eyes of 88 patients with normal subjects were involved. The As/Ps measured by the anterior segment optical coherence tomography (AS-OCT) and other indices measured by AS-OCT and rotating Scheimpflug-based corneal tomography were evaluated. The area under receiver-operating-characteristics (AU-ROC) was calculated to assess the diagnostic ability in discriminating FFKC from normal eyes. The As/Ps, the Belin/Ambrosio display enhanced ectasia total derivation value (BAD-D) and posterior and anterior elevation values showed the AU-ROC 0.9 or more in differentiating FFKC from normal eyes (0.980, 0.951, 0.924 and 0.903, respectively). The sensitivity and specificity were 0.92 and 0.96 for the As/Ps, 1.00 and 0.90 for BAD-D, 0.85 and 0.86 for posterior elevation value, and 0.85 and 0.96 for anterior elevation value, respectively. Among the several indices for keratoconus screening which we evaluated, the As/Ps obtained by AS-OCT had the large AU-ROC with high sensitivity and specificity in detecting FFKC, which was comparable with BAD-D obtained by rotating Scheimpflug-based corneal tomography. The As/Ps may provide information for improving the diagnostic accuracy of KC, even in the initial stage of the disease.