Location Patterns Research Articles

Locational patterns of warehousing facilities in the City of Cape Town municipality

The proliferation of globalisation and e-commerce has led to an increasing number of warehousing facilities in cities and regions, which may contribute to the negative externalities of air pollution, noise pollution, and traffic congestion. Despite the close relationship between logistics and different sectors of the economy, there is a paucity of literature on the connection between warehousing and different land-use categories. Focusing on the City of Cape Town municipality in South Africa, the article aims to analyse the locational patterns of warehousing facilities relative to the transport infrastructure and the industrial, retail, and office land use. The study was based on a descriptive quantitative design wherein kernel density was employed in ArcGIS to analyse the locational patterns of warehousing facilities across the municipality. Data on the floor area of the industrial, retail, and office land use were classified into several ranges to ascertain the intensity of the land use relative to the concentration of the warehousing facilities. It was discovered that warehousing facilities cluster in the highly accessible areas within the municipality, namely the port’s environs, in the vicinity of the main junctions, and adjacent to arterial roads, which provide connections to the national roads. The areas with the highest concentration of warehousing facilities also accommodated the most significant percentage of industrial and retail land use. It is recommended that the existing warehousing clusters be prioritised in future warehousing development or consolidation, and that the future increase of the industrial and retail land use within the City of Cape Town municipality include a commensurate increase of space for warehousing facilities or vice versa.

A 22-Year Study to Assess Disparities in Place of Death Among Patients With Diabetes.

Background This study examines disparities in the place of death in patients in the United States with diabetes mellitus (DM) using data from the CDC WONDER (Centers for Disease Control and Prevention's Wide-Ranging Online Data for Epidemiologic Research) database covering a 22-year period (1999-2020). Looking at age, gender, ethnicity, and census location, among other variables, the study aims to understand trends and determinants of mortality at home or hospice care compared to mortality at a medical or nursing facilities. Materials and methods An online freely accessible mortality database, CDC WONDER database, was used to collect information regarding DM-related mortality, using the International Classification of Diseases, 11th Revision (ICD-11) code range E10-E14. To investigate patterns in location of death, the research population was split by census regions, racial categories, age groups, and gender. Statistical techniques such as univariate logistic regression and graphical representations were employed. Results Based on a study of 1,674,724 DM-related deaths, medical or nursing facilities recorded higher deaths (1,041,602) compared to home or hospice deaths (572,567). The highest number of deaths in home or hospice setting was recorded for the age group of 75-84 years (146,820), male gender (324,325), Census Region 3 (South) (225,636), and white race (458,690). Among the patients with death at home or a hospice center; the odds were highest for the age group of 55-64 years, male gender, Census Region 4 (West), and American Indian or Alaska Native race. Discussion The results showed a general upward trend in DM patients' deaths at home and in hospice care in the United States. Males, white people, and those in the age group of 75-84 years notably had the highest death rates. Regional differences also came into play, with the South showing the biggest trend in mortality. To better understand the underlying causes of these changes and to increase at-risk groups' access to healthcare facilities, more research is required. Conclusion There is an overall rising trend in home and hospice deaths in the United States for patients with DM, but with a steady dip between the years 2005 and 2010. Patient deaths from DM were categorized by age groups, gender, race, and census regions. The highest mortality trends are exhibited in whites, males, and those aged 75-84 years. Out of the census regions, the South has the highest mortality trend. Further studies could be carried out to determine the reasons for the rising trends in home or hospice deaths in the aforementioned groups and how to provide these groups with better access to healthcare facilities.

Investification in the housing market: exploratory study in Santiago de Chile

This study uses a quantitative methodological approach with geographically weighted regressions to address the phenomenon of investification in the Greater Santiago rental market. Using the collection and analysis of transaction data and urban indicators, the location patterns of residential investments are explored for specific urban functions at the census tract level. The analysis reveals that proximity to higher education institutions, stability in rental prices, and the presence of older adults are determining factors in the selection of investment properties. These findings evidence the transformation of the urban landscape as rental spaces for capital and highlight the growing socio-spatial segmentation, thus underlining the need for regulations that address the implications of investification in the urban dynamics of Greater Santiago.

Personalized PV system recommendation for enhanced solar energy harvesting using deep learning and collaborative filtering

Electricity is a crucial aspect of modern life, and with the increasing population and industrialization, energy demand has risen significantly. A swift transition to renewable energy sources such as wind and solar is essential for saving the planet. Solar energy is one of the most widely used renewable energy solutions, but choosing a PVSC poses a challenging problem that involves considering various factors, such as geographical location and energy consumption patterns. In this study, we investigate the effectiveness of using machine learning techniques to assist users in selecting the most suitable PVSC for their needs. We propose a new framework for PVSC recommendation, which encompasses a PV power forecasting model and a PV configuration recommendation system.We propose two forecasting models, one based on LSTM and the other based on CNN architecture. These two elements are responsible for extracting relevant features from time-series meteorological data, which are then passed to a feed-forward MLP layer that predicts the monthly energy production for different PVSCs. Subsequently, the prediction results are utilized to determine the optimal Residential scale PVSC for households, taking into account location and historical consumption data. The system was trained on simulated data and then tested on both a hold-out simulated test set and a real-world dataset. Our experiments show that the proposed framework is effective for long-term PV power forecasting and PVSC recommendation.

Climate change and cooling equity: Spatial dynamics of vulnerable populations

AbstractClimate change disproportionately affects low‐income and minority populations. This study identified vulnerable populations to extreme heat, focusing on home air conditioning. State and municipal laws and regulations usually consider home air conditioning an amenity rather than a requirement for habitability such as heat, water, and electricity. Using the historical census data and the American Housing Survey data, this study identified the vulnerable populations to extreme heat and their spatial dynamic in Los Angeles County, CA. This study found that low‐income minority populations are more likely to live without home air conditioning, and they are more likely to be exposed to extreme heat in the coming years if their residential location patterns continue. Changing spatial patterns of low‐income and minority populations need to be incorporated into urban and regional planning for climate change. State regulations and municipal codes should require air conditioning as a habitability requirement for cooling equity. Also, cooling stations that provide immediate relief for those without home air conditioning need strategic placements based on the locational concentration of the vulnerable populations.

Location Patterns and Drivers of Coworking Spaces in European Regions

AbstractThe location patterns of new working spaces and the factors driving their emergence have been widely studied in Europe. However, research has mainly focused on specific countries and very local areas. We widen this perspective to a regional one and conduct a cross‐country study of the location patterns and determinants of today's main new working spaces, specifically coworking spaces that facilitate collaboration and knowledge sharing. Coworking spaces are traditionally associated in the literature with vibrant urban places, but they are also found in non‐metropolitan regions. Drawing on a unique data set of coworking space locations in four large European countries (Spain, France, Germany and Poland), we test how demographic, economic, structural, technological and accessibility‐related determinants affect the location of these spaces. We then investigate whether the identified determinants vary between metropolitan and non‐metropolitan and between countries, controlling for spatial effects.

MODL-24. NEUROIMMUNE-COMPETENT HUMAN BRAIN ORGANOID MODEL FOR STUDYING BRAIN TUMOR INVASION

Abstract INTRODUCTION Diffuse intrinsic pontine glioma (DIPG) is a highly aggressive pediatric brain tumor with a very poor prognosis (< 12 months survival). There is currently no effective treatment for DIPG. Complete surgical resection of DIPG is difficult due to its skull base location and infiltrative growth pattern. Gaining insights into the invasion process of the DIPG cells and their interaction with brain cells in the tumor microenvironment, such as microglia - the brain's primary immune cells, may guide the development of effective treatment strategies to halt or even reverse disease progression. To build a clinically relevant model for studying the microglia/tumor interaction in a 3D human tissue context, we developed a neuroimmune-competent brain organoid/DIPG fusion model system. METHODS Human embryonic stem cell derived-neural progenitor cells (NPCs) and -GFP-labelled human myeloid precursor cells were combined to form microglia-containing organoids (MiCBOs) through self-assembly and co-development over two months. Using two-photon live imaging, we characterized the distribution and motility of microglia in MiCBOs and corroborated these results with immunofluorescence staining and single-cell RNA-Sequencing (scRNA-Seq). Tumor cell invasion and interaction with microglia in the brain organoids were assessed by confocal microscopy as well as immunofluorescence stainings. RESULTS The human microglia in MiCBOs are viable, widely distributed, actively motile, and highly resemble those in the human brain. Confrontation experiments of the MiCBO with DIPG spheroids enable quantitative characterization of the invasion patterns for different cell lines under various conditions. CONCLUSION Our MiCBOs represent a valuable model for studying tumor cell invasion within a neuroimmune-competent human tissue context. Ongoing experiments with different primary DIPG cell lines as well as genetically engineered microglia will deliver more detailed insights into the invasion patterns of tumor cells into brain tissue and shed light on tumor cell/microglia interplay during the DIPG invasion process.

Early life exposure to broccoli sprouts confers stronger protection against enterocolitis development in an immunological mouse model of inflammatory bowel disease.

To our knowledge, IL-10-KO mice have not previously been used to investigate the interactions of host, microbiota, and broccoli, broccoli sprouts, or broccoli bioactives in resolving symptoms of CD. We showed that a diet containing 10% raw broccoli sprouts increased the plasma concentration of the anti-inflammatory compound sulforaphane and protected mice to varying degrees against disease symptoms, including weight loss or stagnation, fecal blood, and diarrhea. Younger mice responded more strongly to the diet, further reducing symptoms, as well as increased gut bacterial richness, increased bacterial community similarity to each other, and more location-specific communities than older mice on the diet intervention. Crohn's disease disrupts the lives of patients and requires people to alter dietary and lifestyle habits to manage symptoms. The current medical treatment is expensive with significant side effects, and a dietary intervention represents an affordable, accessible, and simple strategy to reduce the burden of symptoms.

Nitric oxide synthase and its function in animal reproduction: an update.

Nitric oxide (NO), a free radical labile gas, is involved in the regulation of various biological functions and physiological processes during animal reproduction. Recently, increasing evidence suggests that the biological role and chemical fate of NO is dependent on dynamic regulation of its biosynthetic enzyme, three distinct nitric oxide synthase (NOS) according to their structure, location and function. The impact of NOS isoforms on reproductive functions need to be timely elucidated. Here, we focus on and the basic background and latest studies on the development, structure, importance inhibitor, location pattern, complex functions. Moreover, we summarize the exactly mechanisms which involved some cell signal pathways in the regulation of NOS with cellular and molecular level in the animal reproduction. Therefore, this growing research area provides the new insight into the important role of NOS male and female reproduction system. It also provides the treatment evidence on targeting NOS of reproductive regulation and diseases.

Value of Non-Contrast-Enhanced Vessel Wall MR Imaging in Assessing Vascular Invasion of Retroperitoneal Tumors.

Due to their location and growth patterns, retroperitoneal tumors often involve the surrounding blood vessels. Clinical decisions on a proper treatment depend on the information on this condition. Evaluation of blood vessels using non-contrast-enhanced vessel wall MRI may provide noninvasive assessment of the extent of tumor invasion to assist clinical decision-making. To investigate the performance and potential of non-contrast-enhanced vessel wall MRI in evaluating the degree of vessel wall invasion of retroperitoneal tumors. Prospective. Thirty-seven participants (mean age: 60.59 ± 11.77 years, 59% male) with retroperitoneal tumors close to vessels based on their diagnostic computer tomography. 3 T; vessel wall MRI sequences: two-dimensional T2-weighted MultiVane XD turbo spin-echo (2D-T2-MVXD-TSE) and three-dimensional T1-weighted motion sensitized driven equilibrium fat suppression turbo spin-echo (3D-T1-MSDE-TSE) sequences; conventional MRI sequences: T2-weighted fat suppression turbo spin-echo (T2-FS-TSE), T2-weighted turbo spin-echo (T2-TSE), modified Dixon T1-weighted fast field echo (T1-mDixon-FFE), and diffusion-weighted echo planar imaging (DWI-EPI) sequences. All patients underwent preoperative imaging using both non-contrast conventional and vessel wall MRI sequences. Images obtained from conventional and vessel wall MRI sequences were evaluated independently by three junior radiologists (3 and 2 years of experience in reading MRI) and reviewed by one senior radiologist (25 years of experience in reading MRI) to assess the degree of vessel wall invasion. MRI were validated results from the clinical standard diagnosis based on surgical confirmation or histopathological reports. Interobserver agreement was determined based on the reports from three readers with similar years of experiences. Intraobserver variability was assessed based on categorizing and recategorizing the vessels of 37 patients 1 month apart. Intra-class correlation efficient (ICC), Chi-square test, McNemar test, area under the receiver-operating characteristic curve (AUC), Delong test, P < 0.05 was considered significant. The accuracy of vessel wall MRI (91.96%, 95% CI: 85.43-95.71; 103 of 112) in detecting the degree of vessel wall invasion was significantly higher than that of conventional MRI (75%, 95% CI: 66.24-82.10; 84 of 112). The interobserver variability or reproducibility in categorization of the degree of vascular wall invasion was good in evaluating images from conventional and vessel wall MRI sequences (ICC = 0.821, 95% CI: 0.765-0.867 and ICC = 0.881, 95% CI: 0.842-0.913, respectively). Diagnosis of vessel wall invasion of retroperitoneal tumors and assessment of its severity can be improved by using non-contrast-enhanced vessel wall MRI. 1 TECHNICAL EFFICACY: Stage 3.

A Critical Assessment of the Distribution Strategies Employed in the Marketing of Petroleum Products

The distribution of petroleum products holds significant importance within the global energy sector, carrying extensive ramifications for both corporate entities and end-users. The objective of this study is to conduct a thorough assessment of the distribution tactics utilized in the marketing of petroleum products. The research involves several phases of the distribution process, ranging from the supply chain to the ultimate customer. The petroleum sector is characterized by a multitude of intricacies, including aspects such as fluctuating pricing, geopolitical considerations, environmental apprehensions, and the escalating need for sustainable alternatives. Therefore, it is imperative for petroleum businesses to develop and modify their distribution methods to maintain competitiveness and satisfy the changing demands of consumers. This study explores the many strategies employed in the dissemination of petroleum products, encompassing conventional systems involving pipelines, refineries, and gasoline stations, as well as contemporary ways that integrate digital technology, alternative fuels, and ecologically sustainable measures. The key findings of the study suggest that the efficient distribution of petroleum products is contingent upon several elements, including geographical location, infrastructural availability, regulatory frameworks, and consumer behavior patterns. It is apparent that a standardized method is not feasible, and organizations must customize their distribution tactics to accommodate the distinct requirements and limitations of individual markets. This study also investigates the impact of digital technologies, such as data analytics, Internet of Things (IoT), and automation, on the optimization of distribution networks. Moreover, it highlights the growing significance of sustainability and environmental accountability in distribution tactics, namely in response to customer preferences for cleaner and more environmentally friendly fuel alternatives. In summary, this study emphasizes the fluidity of distribution techniques within the petroleum sector. It is imperative for companies to maintain adaptability, ingenuity, and receptiveness towards market fluctuations, while concurrently striving to incorporate technology and sustainability into their distribution procedures. A comprehensive comprehension of the intricacies of distribution within the petroleum industry is vital for enterprises seeking to prosper in an always developing energy milieu.

Global Street Experiment: A Geospatial Database of Pandemic-induced Street Transitions

Street experiment is a tactical urbanism practice that involves implementing temporary changes in street use through regulatory or physical interventions, aimed at people-centric street transition. During the Covid-19 pandemic, cities worldwide implemented street experiments to accommodate the need for socially-distanced physical and commercial activities. However, we know little about the locations and urban environments of these pandemic-induced street experiments on a global scale. This knowledge gap hinders us from understanding where these experiments took place, the conditions of the neighbourhoods involved, and the factors contributing to their longevity beyond the pandemic. We thus developed a geospatial database to document the pandemic-induced street experiments (PISE Database), enabling quantitative analysis of these interventions. We mapped the locations and calculated the neighbourhood environment attributes of 539 street experiments in 333 cities. Our contributions are twofold. Firstly, we enhanced the comparability of built environment indicators between cities, thereby advancing the construction of global geospatial datasets. Specifically, we established a standardised template encompassing unified neighbourhood-level built environment indicators and methodologies, for which we devised relative values to facilitate comparisons between different cities and defined study areas using the 15-minute walking city and Urban Centre concepts. Secondly, we conducted primary analyses based on spatial and temporal visualisations of the street experiment locations and durations, shedding light on locational patterns and development trajectories during times of crisis. This global, quantitative approach complements the growing body of local and often qualitative studies. Our work improves existing global quantitative databases and provides a robust foundation for future research on tactical urbanism.

Socio-Demographic Profile and Adherence to Anti-Retroviral Treatment among HIV/AIDS Patients Attending the ART Centre in Tamil Nadu

Background: Epidemiology of HIV infection in India is varied and depends on multitude of factors such as socio-demographic profile, geographic location and behavioural pattern. HIV/AIDS is not only a public health issue in India but also one of the most serious socioeconomic and developmental concerns as nearly 86% of reported cases occur in sexually active and economically productive age group (15-49yrs). Thus, for planning targeted interventions, it is essential to know the socio-demographic and clinical profile of the HIV/AIDS patients in a particular area as important for control of HIV replication, disease progression and ultimately containment of the disease. Hence this study was planned to describe the Socio-demographic profile and ART treatment adherence of People Living with HIV/AIDS attending The ART Centre, KKGMCH, Asaripallam, Kanyakumari District, Tamil Nadu. Objectives: To describe the Socio-demographic profile and ART treatment adherence of People Living with HIV/AIDS attending The ART Centre, KKGMCH, Asaripallam, Kanyakumari District, Tamil Nadu. Materials &amp; Methods: This was a Cross- sectional study conducted among adult people living with HIV/AIDS who were on treatment at ART centre. The study was done during January 2014 to July 2014. The data was collected by using a semi structured questionnaire derived from WHO-BREFQOL. Result: The age of the study population varies from minimum 18 to maximum 59 years with the mean ± SD age of 39.5 ± 8.3 years. Around 69 (46.0%) participants are in the 31 – 40 years age group followed by 51 (39.0%) are in the 41 – 50 years age group. Regarding the Family type, 127 (84.7%) are from nuclear family; 19 (12.7%) are from extended family and another 4 (2.7%) are from the Joint family. The prevalence of opportunistic symptoms among the study participants, around 44% of the study participants developed respiratory related symptoms followed by Skin (24%). Among 150 subjects taking ART, 120 (80.0%) are receiving Regimen 1 and 30 others (20%) are receiving Regimen 2. Around 92 (61.3%) have good adherence to ART. 53 (35.3%) have fair and 5 (3.3%) have poor adherence. Conclusion: Non-adherence as a hindering factor for the success of therapy is well-established. Keywords: HIV/AIDS, Socio-demographic profile, Drug Adherence, Targeted intervention

Genome-wide identification and expression analysis of the GRAS gene family under abiotic stresses in wheat (Triticum aestivum L.)

The GRAS transcription factors are multifunctional proteins involved in various biological processes, encompassing plant growth, metabolism, and responses to both abiotic and biotic stresses. Wheat is an important cereal crop cultivated worldwide. However, no systematic study of the GRAS gene family and their functions under heat, drought, and salt stress tolerance and molecular dynamics modeling in wheat has been reported. In the present study, we identified the GRAS gene in Triticum aestivum through systematically performing gene structure analysis, chromosomal location, conserved motif, phylogenetic relationship, and expression patterns. A total of 177 GRAS genes were identified within the wheat genome. Based on phylogenetic analysis, these genes were categorically placed into 14 distinct subfamilies. Detailed analysis of the genetic architecture revealed that the majority of TaGRAS genes had no intronic regions. The expansion of the wheat GRAS gene family was proven to be influenced by both segmental and tandem duplication events. The study of collinearity events between TaGRAS and analogous orthologs from other plant species provided valuable insights into the evolution of the GRAS gene family in wheat. It is noteworthy that the promoter regions of TaGRAS genes consistently displayed an array of cis-acting elements that are associated with stress responses and hormone regulation. Additionally, we discovered 14 miRNAs that target key genes involved in three stress-responsive pathways in our study. Moreover, an assessment of RNA-seq data and qRT-PCR results revealed a significant increase in the expression of TaGRAS genes during abiotic stress. These findings highlight the crucial role of TaGRAS genes in mediating responses to different environmental stresses. Our research delved into the molecular dynamics and structural aspects of GRAS domain-DNA interactions, marking the first instance of such information being generated. Overall, the current findings contribute to our understanding of the organization of the GRAS genes in the wheat genome. Furthermore, we identified TaGRAS27 as a candidate gene for functional research, and to improve abiotic stress tolerance in the wheat by molecular breeding.

Distributed Energy Systems: Multi-Objective Design Optimization Based on Life Cycle Environmental and Economic Impacts

The distributed energy system (DES) represents an innovative approach to energy generation and distribution that promotes decentralization and diversification of energy sources. DESs can offer numerous benefits, including increased resiliency, reduced transmission losses, improved efficiency, and lower carbon emissions. The optimal design of a DES requires careful consideration of various factors such as geographical location, climate conditions, and energy demand patterns. This paper utilizes a multi-objective genetic algorithm to optimize the combination of technologies and their corresponding sizes in a distributed energy system for three types of commercial buildings—hospitals, large offices, and large hotels across eight different climate zones in the U.S. A range of technologies are considered for integration into the DES. These technologies include photovoltaic systems, wind turbines, combined heat and power systems, solar thermal collectors, and electrical and thermal energy storage. The two objectives considered are maximizing the reduction in carbon dioxide emissions and minimizing the life cycle costs for the DES. The purpose of this study is to optimize and evaluate the multi-objective design of distributed energy systems aimed at decentralizing and diversifying energy sources. The analysis of optimized DES designs across all 24 case scenarios shows that a balance between cost saving and emission reduction has been achieved. Although this study primarily focuses on specific buildings and climate zones, the methods and findings can be adapted for a wider variety of building types across different geographical locations, thus paving the way for more widespread adoption of optimized distributed energy systems.

Imaging Findings and Misdiagnosis of Bronchogenic Cysts: A Study of 83 Cases.

We characterize computed tomography (CT) and magnetic resonance imaging (MRI) features of bronchogenic cysts (BCs) and analyze misdiagnosis. The retrospective study consisted of 83 patients with BCs. CT and MRI images were assessed for mass location, maximum diameter, density, calcification, signal intensity, and enhancement pattern. Eighty-three patients underwent plain CT in which 53 underwent enhanced CT. Thirteen patients received both plain and enhanced MR, and only one received just a plain MR. Eighty-three masses were all solitary, with 71 having a roundish morphology, and twelve having a lobulated or irregular morphology. Sixty-six masses are mediastinal type, four are intrapulmonary type, and 13 are ectopic type. Calcification occurred in 14 lesions. On plain CT, 13 lesions displayed water-like attenuation (-20-20 Hu), and 70 showed soft-tissue attenuation (≥21 Hu). On T1WI, eight masses were hyperintense, three were isointense, and three were hypointense. Fourteen masses were hyperintense on T2WI and (Apparent Diffusion Coefficient) ADC sequence. On (Diffusion Weighted Imaging) DWI, six masses were hypointense and eight were hyperintense. Enhanced T1WI showed seven cases were unenhanced, while six were marginally enhanced. Twenty cases were misdiagnosed as thymomas, eleven as neurogenic tumors, six as lymphangiomas, and two as lung cancer. Five cases were misdiagnosed as other diseases. Patients with BCs underwent MR (42.9%) had a lower rate of misdiagnosis than those who underwent CT alone (53.0%). The imaging findings of BCs in the chest are generally consistent. Misdiagnosis occurs frequently when CT attenuation values exceed 20 Hu. Diagnostic accuracy of BCs tends to improve with preoperative MR examination.

Multi Detector Computed Tomography and Ultrasound Evaluation of Neck Masses with Pathological Correlation

Introduction: Neck imaging has always been a diagnostic challenge. High-resolution sonography being inexpensive and safe has become the initial investigation of choice for neck pathologies; it provides information regarding the origin and extent of the lesion. Computed tomography (CT) has a unique capacity for displaying soft tissue, bone and airway details and provides critical anatomical information about lesions involving the neck. This study aims to determine the role of USG and CT in neck masses for pre-operative characterization based on location, extent, morphological characteristics and enhancement pattern and to compare USG and CT findings with histopathological diagnosis.&#x0D; Material and Methods: A total number of 60 adult patients with suspected neck masses were studied in the department of Radiodiagnosis, SSIMS&amp;RC, Davanagere and inputs from Dr. B. R. Ambedkar Medical College, Bengaluru over a period of 24 months. Ultrasound was done using GE Voluson E6 machine &amp; Contrast enhanced CT was done using GE Revolution Multidetector CT scan machine. Post processing techniques (like volume rendered techniques) were applied wherever useful.&#x0D; Results: The findings on USG and CT were conclusive in nearly 90% of cases. Enhancement patterns and presence/absence of bony invasion were found to be more specific in differentiating benign/malignant nature.&#x0D; Conclusion: High-resolution sonography can be used as the first-line modality for evaluating cervical soft tissue masses, it helps the clinicians to characterize the lesion. Multi-detector computed tomography is a sensitive diagnostic tool for diagnosing neck masses and differentiating between benign and malignant lesions with high accuracy. The extent of pathology with local/ contiguous spread predicted by CT examination was conclusive. The overall findings suggest that MDCT and Ultrasound, when used in conjunction with pathological correlation, can be effective tools for accurately characterizing and diagnosing the neck masses.

R&amp;D location in dynamic industry environments

Abstract We study firms’ optimal R&amp;D location strategies in a dynamic industry model with competition in product quality. In light of potential future inwards and outwards spillovers firms make their location choices relying on heuristic strategies that are based on the expected present values associated with alternative location patterns. Using a simulation analysis, we show how the strategies of innovators and imitators differ and how they depend on whether firms operate in strongly or weakly innovative industry environments. We also characterize how firms’ location choices should account for the innovativeness of the competitors active in a location.

Is Burning Mouth Syndrome Associated with Extraoral Dryness? A Systematic Review.

Burning mouth syndrome (BMS) is characterized by a persistent intraoral burning sensation, often experienced by postmenopausal women. The etiology of BMS remains partially understood, and consequently, treatments remain suboptimal. Extraoral manifestations of BMS, such as extraoral dryness, are less studied. However, it has been suggested that the identification of the frequency and patterns of extraoral dryness and potential underlying mechanisms are essential to optimize treatment strategies and reduce the burden of disease. Therefore, we conducted this systematic review to provide existing evidence about extraoral dryness in BMS. The guidelines for the conduction and reporting of systematic reviews were followed. An electronic search was conducted in four major databases-PubMed, Web of Science, COCHRANE Library, and EBSCOhost-and the grey literature was assessed through Google Scholar. From each included article, information on extraoral dryness in BMS was extracted, and odds ratios were calculated for extraoral dryness among BMS patients compared with non-BMS controls. The findings demonstrated higher odds of the prevalence of extraoral dryness in BMS, which was found to a high degree in the lips, eyes, skin, and genitalia. The pattern of spread and locations of extraoral dryness propose a potential central mechanism. Based on our findings, we encourage the standardization of the assessment, recording, and reporting of the extraoral characteristics of BMS, including extraoral dryness, which can lead to better management strategies and enhance the quality of life of the affected patients.

Uncovering and modeling the hierarchical organization of urban heavy truck flows

Knowledge of the hierarchical organization of urban heavy truck flows is important for understanding the structure of urban freight system and underlying interactions dynamics, providing insights to assess and develop freight policies. The complexity and dynamic nature of urban freight system pose significant challenges in comprehensively capturing structured arrangement of heavy truck movements. In this paper, we uncover the hierarchical organization of urban heavy truck flows by using complex network theory. We use large-scale heavy truck GPS data and urban freight location point-of-interest (POI) data to construct urban heavy truck mobility networks, and detect their community structure. The empirical results suggest different sets of locations are closely linked to each other to form multiple clusters. By integrating the categories of locations, we reveal the cluster-specific industry concentration and industry-specific location roles, informing evidence-based policy formulation. To capture the interaction dynamics of locations, we develop a spatial network growth model that considers the spatial agglomeration of industrial clusters and interaction pattern of locations. The model provides a mathematical tool to simulate the formation process of real-world networks for logistics planning and management.