Era Of Rapid Advances Research Articles

Research on audience news and information behavior in the application on mobile phone in Chongqing

In the era of rapid advancements in mobile phone media, media integration has progressed into a stage where audience-centred market integration prevails, rendering the exploration of audience information behaviour[1] a paramount priority for both communication research and media practice. This paper delves into news information behaviour within the mobile media landscape, leveraging T.D. Wilson's information behaviour theory [2] as a starting point. It integrates theories such as Uses and Gratifications, Japanese information behaviour theory, media dependency theory, innovation diffusion theory, and consumer behaviour theory [3] to devise a communication information behaviour model. Through interdisciplinary theoretical linkages, this study aims to contribute to theoretical innovations in exploring the behaviour of communication audiences. Utilizing a robust foundation of literature reviews, the primary research methods employed are quantitative research and surveys. Data analysis is conducted using statistical software to discern the characteristics of audience news information behaviour in the mobile media environment. Furthermore, the study compares and contrasts the information behaviour patterns among typical users across different news audience segments. By synthesizing interview insights, the key factors influencing audience news information behaviour are identified, leading to the formulation of a communication news information behaviour model. Employing structural equation modelling (SEM)[4] techniques and statistical software, this paper delves into the intricate relationships between variables that influence the adoption behaviour of mobile news, ultimately constructing a mobile news adoption behaviour model.

Rancang Bangun Sistem Informasi Pelayanan Kesehatan Berbasis Website Pada Salvio Medical Information

In an era of rapid advances in Information Technology, health is an important aspect of human life. Clinics and hospitals compete to meet patient expectations, but often patients struggle to find suitable services, wasting valuable time. A common problem faced by many visitors to Bali is the confusion of finding a hospital or clinic that suits their needs. Salvio Medical Information, as a healthcare institution in Bali, faces similar challenges with a lack of a comprehensive information system. This can result in errors in data management, difficulties in accessing information, as well as delays in service to guests who need health care. Therefore, this research aims to design a website-based healthcare information system for Salvio Medical Information. The development approach uses the Extreme Programming model to enable rapid software development. Thus, this research is expected to make a significant contribution to efforts to develop health services that are more efficient and able to better meet the needs of patients. The expected result is a web-based health service information system that is built using the PHP programming language with the help of the Laravel framework and the extreme programming method. Where in the system built custemer can place orders through the website and the admin can manage service content and partner content on the website.

A freeway vehicle early warning method based on risk map: Enhancing traffic safety through global perspective characterization of driving risk

In the era of rapid advancements in intelligent transportation, utilizing vehicle operating data to evaluate the risk of freeway vehicles and study on vehicle early warning methods not only lays a theoretical foundation for improving the active safety of vehicles, but also provides the technical support for reducing accident rate. This paper proposes a freeway vehicle early warning method based on risk map to enhance vehicle safety. Firstly, Modified Time-to-Collision (MTTC), a two-dimensional indicator that describes the risk of inter-vehicle travel, is used as an indicator of road traffic risk. This paper designs a transformation function to probabilistically transform MTTC into Risk Indicators (RI). The single-vehicle risk map is generated based on the mapping relationship between the risk values and the corresponding roadway segments. These single-vehicle risk maps of all vehicles on the road are superimposed to construct the risk map, which is used to describe the risk distribution in the freeway. Then, a vehicle early warning framework is built based on the risk map. The risk values in the risk map are compared with predefined early warning thresholds to alert the vehicle when it enters a high-risk state. Finally, VISSIM is used to carry out simulation experiments. The experiment simulates a freeway accident stopping situation. This scenario includes sub-scenarios such as unplanned stopping and lane-changing, continuous lane-changing, and adjacent lane overtaking. We analyze the risk map and vehicle warning results in different sub-scenarios, evaluate the risk changes of the vehicles before and after receiving the warning, and compare the warning results of the method in this paper with other alternative methods. The method is applied to 17 vehicles in the simulation to adjust their motion states. The results show that the total warning time is reduced by 29.6% and 73.3% of vehicles change lanes away from the accident vehicle. The overall results validate the effectiveness of the vehicle early warning method based on risk map proposed in this paper.

Improved recovery of cardiac auscultation sounds using modified cosine transform and LSTM-based masking.

Obtaining accurate cardiac auscultation signals, including basic heart sounds (S1 and S2) and subtle signs of disease, is crucial for improving cardiac diagnoses and making the most of telehealth. This research paper introduces an innovative approach that utilizes a modified cosine transform (MCT) and a masking strategy based on long short-term memory (LSTM) to effectively distinguish heart sounds and murmurs from background noise and interfering sounds. The MCT is used to capture the repeated pattern of the heart sounds, while the LSTMs are trained to construct masking based on the repeated MCT spectrum. The proposed strategy's performance in maintaining the clinical relevance of heart sounds continues to demonstrate effectiveness, even in environments marked by increased noise and complex disruptions. The present work highlights the clinical significance and reliability of the suggested methodology through in-depth signal visualization and rigorous statistical performance evaluations. In comparative assessments, the proposed approach has demonstrated superior performance compared to recent algorithms, such as LU-Net and PC-DAE. Furthermore, the system's adaptability to various datasets enhances its reliability and practicality. The suggested method is a potential way to improve the accuracy of cardiovascular diagnostics in an era of rapid advancement in medical signal processing. The proposed approach showed an enhancement in the average signal-to-noise ratio (SNR) by 9.6dB at an input SNR of - 6dB and by 3.3dB at an input SNR of 10dB. The average signal distortion ratio (SDR) achieved across a variety of input SNR values was 8.56dB.

Investigating the Implementation of ChatGPT in English Language Education

In the era of rapid advancements in Artificial Intelligence (AI), ChatGPT (Chat Generative Pre-Trained Transformer) emerges as a pivotal tool reshaping educational landscapes. This research, based on self-determination theory, investigates how ChatGPT influences the motivation and academic performance of 35 seventh-semester English education students. Utilizing mixed methods, it contrasts the experiences of 25 ChatGPT users with those of 10 non-users. The quantitative analysis demonstrates notably higher levels of motivation and GPAs among ChatGPT users (with a mean motivation score of 44.88 and a mean GPA of 3.63) compared to non-users (with a mean motivation score of 17.60 and a mean GPA of 3.06). Qualitative insights highlight themes such as 'Improved Comprehension and Independent Learning' and 'Increased Academic Efficiency and Productivity,' illustrating how ChatGPT supports effective and thorough learning experiences. In keeping with the tenets of self-determination theory, these results demonstrate that ChatGPT has a beneficial effect on students' motivation. The study also recommends more experimental studies to investigate how students' motivation and performance can be improved by using ChatGPT.

Shaping the future of advanced automation and control systems for society strategic directions and multidisciplinary collaborations of IFAC's social systems coordinating committee

In an era of rapid advancements in highly intelligent digital systems, blockchain, and other transformative technologies, the role of control and automation in shaping human civilization is of paramount, even critical, importance. This paper examines the strategic significance of IFAC's Social Systems Coordinating Committee (CC), a unique multidisciplinary global community of researchers and practitioners comprising leading universities, research centers, industry partners and international agencies at the forefront of integrating technological and societal progress.This paper reports the results of a strategic "milestone" review, including an extensive meta-analysis of the Social Systems CC's five Technical Committees (TCs) and their activities. It uncovers key themes emphasizing this CC's contributions to models, systems, infrastructures, and operations. Using content analysis and word clouds, 272 keywords were refined to elucidate the main themes of the CC, revealing significant current and future collaborations with other IFAC communities and external organizations. The paper identifies high-potential new cooperation opportunities between this CC and the other IFAC CCs and their TCs, suggesting ways to achieve these collaborations. The findings highlight the Social Systems CC's unique position at the heart of the global automation and control community, where it offers practical applications in planning, management, and sustainability as well as fostering cross-sector cooperation crucial for human progress and effective humanitarian and environmental responses. This paper underscores the Social Systems CC's role in advancing control science and automation systems engineering to tackle pressing societal challenges, advocating for a future where technology and human systems synergize for the global well-being of all living systems.

DataColor: unveiling biological data relationships through distinctive color mapping.

In the era of rapid advancements in high-throughput omics technologies, the visualization of diverse data types with varying orders of magnitude presents a pressing challenge. To bridge this gap, we introduce DataColor, an all-encompassing software solution meticulously crafted to address this challenge. Our aim is to empower users with the ability to handle a wide array of data types through an assortment of tools, while simultaneously streamlining parameter selection for rapid insights and detailed enhancements. DataColor stands as a robust toolkit, encompassing 23 distinct tools coupled with over 600 parameters. The defining characteristic of this toolkit is its adept utilization of the color spectrum, allowing for the representation of data spanning diverse types and magnitudes. Through the integration of advanced algorithms encompassing data clustering, normalization, squarified layouts, and customizable parameters, DataColor unveils an abundance of insights that lay hidden within the intricate relationships embedded in the data. Whether you find yourself navigating the analysis of expansive datasets or embarking on the quest to visualize intricate patterns, DataColor stands as the comprehensive and potent solution. We extend the availability of DataColor to all users at no cost, accessible through the following link: https://github.com/frankgenome/DataColor.

External carotid artery-radial artery graft-posterior cerebral artery bypass for complex vertebrobasilar aneurysms: efficacy and analysis of outcome in a single center.

The purpose of this research was to demonstrate the effectiveness and clinical outcome of an external carotid artery-radial artery graft-posterior cerebral artery (ECA-RAG-PCA) bypass in the treatment of complex vertebrobasilar artery aneurysms (VBANs) in a single-center retrospective study. An ECA-RAG-PCA bypass may be a last and very important option in the treatment of complex VBANs when conventional surgical clipping or endovascular interventions fail to achieve the desired outcome. This study retrospectively analyzed the clinical presentation, case characteristics, aneurysm location, size and morphology, choice of surgical strategy, complications, clinical follow-up, and prognosis of the patients enrolled. The data involved were analyzed by the appropriate statistical methods. A total of 24 patients with complex VBANs who met the criteria were included in this study. Eighteen (75.0%) were male and the mean age was 54.1 ± 8.83years. The aneurysms were located in the vertebral artery, the basilar artery, and in the vertebrobasilar artery with simultaneous involvement. All patients underwent ECA-RAG-PCA bypass surgery via an extended middle cranial fossa approach, with 8 (33.3%) undergoing ECA-RAG-PCA bypass only, 3 (12.5%) undergoing ECA-RAG-PCA bypass combined with aneurysm partial trapping, and 12 (50.0%) undergoing ECA-RAG-PCA bypass combined with proximal occlusion of the parent artery. The average clinical follow-up was 22.0 ± 13.35months. The patency rate of the high-flow bypass was 100%. At the final follow-up, 15 (62.5%) patients had complete occlusion of the aneurysm, 7 (29.2%) patients had subtotal occlusion of the aneurysm, and 2 (8.3%) patients had stable aneurysms. The rate of complete and subtotal occlusion of the aneurysm at the final follow-up was 91.7%. The clinical prognosis was good in 21 (87.5%) patients and no procedure-related deaths occurred. Analysis of the good and poor prognosis groups revealed a statistically significant difference in aneurysm size (P = 0.034, t-test). Combining the results of this study and the clinical experience of our center, we propose a surgical algorithm and strategy for the treatment of complex VBANs.The technical approach of ECA-RAG-PCA bypass for complex VBANs remains important, even in an era of rapid advances in endovascular intervention. When conventional surgical clipping or endovascular intervention has failed, an ECA-RAG-PCA bypass plays a role that cannot be abandoned and is a very important treatment option of last resort.

Quaternion Attitude Control System of Highly Maneuverable Aircraft

In the era of rapid advancements in manned and unmanned aviation and robotics, there is a need for high-performance, robust attitude control of highly maneuverable fixed-wing aircraft, both manned and unmanned (UAVs). This paper presents an extension to research on spacecraft attitude control. The article extends existing concepts and applies them to the control problem of aircraft operating in Earth’s atmosphere. First, a general concept of quaternions is presented. Next, the attitude controller’s architecture is discussed. The controller synthesis is described using quaternion algebra. The quaternion-based attitude controller is then compared with a classical Euler-based attitude controller. The methodology for comparison and performance evaluation of both controllers is described. Lastly, the results of the simulations and a comparison of the two controllers are presented and discussed. The presented control scheme outperforms classical methods based on Euler angles, particularly at the aircraft’s high pitch and roll angles.

Human-robot collaboration: A multilevel and integrated leadership framework

In an era of rapid advances in artificial intelligence, the deployment of robots in organizations is accelerating. Further, robotic capabilities are expanding to serve a broader range of leadership behaviors related to task accomplishment and relationship support. Despite the increasing use of robots in various roles across different industries, research on human-robot collaboration in the workplace is lagging behind. As such, the current research aims to provide a state-of-the-science review and directions for future work in this underdeveloped area. Drawing on current leadership paradigms, we review human-robot collaboration studies from four academic disciplines with a history of publishing such work (i.e., management, economics, psychology, engineering) and propose that the research trajectory of human-robot collaboration parallels the evolution of leadership research paradigms (i.e., leader centric, relational view, and follower centric). Given that leadership is an inherently multilevel phenomenon, we apply a levels-of-analysis framework to integrate and synthesize human-robot collaboration studies from cross-disciplinary research areas. Based on our findings, we offer suggestions for future research in terms of conceptualization, theory building and testing, practical implications, and ethical considerations.

Different Timing of Intrauterine Insemination and Pregnancy Outcome in Patients with Unexplained Infertility: A Randomized Controlled Study

Background: In this era of rapid advancements in assisted reproductive technologies, intrauterine insemination (IUI) is still widely offered to subfertile couples, as a cheaper and less invasive treatment option before proceeding to IVF. Objective: To determine the most suitable timing of hCG administration prior to intrauterine insemination for optimizing pregnancy outcome and success rate. Patients and methods: A randomized controlled study conducted in Obstetrics and Gynecology Department, Sohag University from 30 June 2018 to 30 June 2019 and included couples with unexplained infertility. A total of 110 patients were recruited in our study, 30 patients dropped out; where 20 patients were due to inadequate stimulation, bad endometrium or more than 3 follicles were present, 6 patients did not show up for folliculometry after being given treatment and 4 patients did not show up for the procedure after being given the hCG trigger. Results: This study showed an improved pregnancy rate when IUI was performed with a time interval of 24–36 h (13 case with positive pregnancy test). Conclusion: IUI after ovulation induction can be done any time between 24 and 48 h after hCG injection without significant differences in pregnancy rates.

Different Timing of Intrauterine Insemination and Pregnancy Outcome in Patients with Unexplained Infertility: A Randomized Controlled Study

Background: In this era of rapid advancements in assisted reproductive technologies, intrauterine insemination (IUI) is still widely offered to subfertile couples, as a cheaper and less invasive treatment option before proceeding to IVF. Objective: To determine the most suitable timing of hCG administration prior to intrauterine insemination for optimizing pregnancy outcome and success rate. Patients and methods: A randomized controlled study conducted in Obstetrics and Gynecology Department, Sohag University from 30 June 2018 to 30 June 2019 and included couples with unexplained infertility. A total of 110 patients were recruited in our study, 30 patients dropped out; where 20 patients were due to inadequate stimulation, bad endometrium or more than 3 follicles were present, 6 patients did not show up for folliculometry after being given treatment and 4 patients did not show up for the procedure after being given the hCG trigger. Results: This study showed an improved pregnancy rate when IUI was performed with a time interval of 24–36 h (13 case with positive pregnancy test). Conclusion: IUI after ovulation induction can be done any time between 24 and 48 h after hCG injection without significant differences in pregnancy rates.

Gaining a deeper understanding of social determinants of preterm birth by integrating multi-omics data.

In the US, high rates of preterm birth (PTB) and profound Black-White disparities in PTB have persisted for decades. This review focuses on the role of social determinants of health (SDH), with an emphasis on maternal stress, in PTB disparity and biological embedding. It covers: 1) PTB disparity in US Black women and possible contributors; 2) The role of SDH, highlighting maternal stress, in the persistent racial disparity of PTB; 3) Epigenetics at the interface between genes and environment; 4) The role of the genome in modifying maternal stress-PTB associations; 5) Recent advances in multi-omics studies of PTB; and 6) Future perspectives on integrating multi-omics with SDH to elucidate the Black-White disparity in PTB. Available studies have indicated that neither environmental exposures nor genetics alone can adequately explain the Black-White PTB disparity. Preliminary yet promising findings of epigenetic and gene-environment interaction studies underscore the value of integrating SDH with multi-omics in prospective birth cohort studies, especially among high-risk Black women. In an era of rapid advancements in biomedical sciences and technologies and a growing number of prospective birth cohort studies, we have unprecedented opportunities to advance this field and finally address the long history of health disparities in PTB.

RETHINKING THE ROLE OF ENGLISH LECTURERS IN THE DIGITAL ERA

Along with the era of rapid advancement in the performance of Artificial Intelligence, there have been intense discussions and debates among educationists about the future of human teachers and AI teachers. It is intriguing to listen to students’ perspectives on the roles they expect from their teachers, especially in learning English subjects, when abundant resources are available online at their fingertips. To serve that purpose, 160 students were recruited as research participants. Data were collected through questionnaires and interviews. The results indicated that students perceive their teachers as someone to guide their learning by providing good online resources and immediate feedback.

Retrospective Analysis of Pancreas Transplants in Poland in Years 1998-2015

Transplantation of the pancreas is an established method for the treatment of complicated diabetes mellitus. As the numbers of diabetic patients increase so does the need for efficient treatment methods. Despite significant perioperative risk and complications related to immunosuppression, pancreas transplant remains the best therapeutic option for selected patients. MethodsThe analysis was based on the comparison of characteristics of all organ donors and recipients in years 1998 to 2015. The collected data were divided into 2 periods to facilitate identification of populational changes. ResultsThe total number of pancreas transplants in Poland was 139 in years 1998 to 2006 and 268 in years 2007 to 2015. The largest differences revealed by the comparison of donor-related variables in both periods were those related to the doses of pressor amines, duration of circulatory arrest, and duration of stay at the intensive care unit. The critical finding consisted in the improvement of short-term survival of recipients and organs being observed in contrast to the surprising lack of improvement in long-term survival. Reduced likelihood of transplantation success was observed already in overweight patients (body mass index 25-29.99 kg/m2). ConclusionsNo significant changes were observed with regard to pancreas transplant outcomes over the period of many years. Transplantation success is determined by 1-year survival of the organ, and the therapeutic success is measured by long-term disease-free survival of the patient. In the era of rapid advances in numerous areas of medicine, the lack of significant extension of patient survival times warrants a closer look of our knowledge on pancreas transplants.

Data Assimilation Improves Estimates of Climate-Sensitive Seasonal Snow

As the Earth warms, the spatial and temporal response of seasonal snow remains uncertain. The global snow science community estimates snow cover and mass with information from land surface models, numerical weather prediction, satellite observations, surface measurements, and combinations thereof. Accurate estimation of snow at the spatial and temporal scales over which snow varies has historically been challenged by the complexity of land cover and terrain and the large global extent of snow-covered regions. Like many Earth science disciplines, snow science is in an era of rapid advances as remote sensing products and models continue to gain granularity and physical fidelity. Despite clear progress, the snow science community continues to face challenges related to the accuracy of seasonal snow estimation. Namely, advances in snow modeling remain limited by uncertainties in modeling parameterization schemes and input forcings, and advances in remote sensing techniques remain limited by temporal, spatial, and technical constraints on the variables that can be observed. Accurate monitoring and modeling of snow improves our ability to assess Earth system conditions, trends, and future projections while serving highly valued global interests in water supply and weather forecasts. Thus, there is a fundamental need to understand and improve the errors and uncertainties associated with estimates of snow. A potential method to overcome model and observational shortcomings is data assimilation, which leverages the information content in both observations and models while minimizing their limitations due to uncertainty. This article proposes data assimilation as a way to reduce uncertainties in the characterization of seasonal snow changes and reviews current modeling, remote sensing, and data assimilation techniques applied to the estimation of seasonal snow. Finally, remaining challenges for seasonal snow estimation are discussed.

Lessons from Marias: what the titleness and nameless taught me that elite medical institutions couldn't teach me.

In an era of rapid advancements in healthcare and technology, sophisticated treatments and pressure for speedy recoveries, contemporary physicians are often led to neglect some of the support pillars of medicine: That science, guidelines and protocols should not come before the individual; prescriptions serve little purpose without books and literacy; medications are not a substitute for nourishment. That hearing lamenting stories and watching tears run through despondent, downcast faces are sometimes our only resort. That social justice is a powerful healing instrument. That rather than treating the sickness, we shall treat the sick--helpless, deprived, forsaken and in need.

Prostate cancer cost-of-care and evaluation of traditional cost control measures.

163 Background: In the current era of rapid advances in cancer care, economic burden of these treatments is becoming increasingly apparent. Measures taken by Centers for Medicare & Medicaid Services (CMS) such as closely monitoring length of inpatient stay might be inadequate in their goal to curtail costs. SEER analysis shows a 5-year overall survival for prostate cancer of 98.2 % and incidence of 179.1 in 2000 versus 97.8 in 2015 per 100,000, respectively. This encouraging result comes at the cost of increasing healthcare costs. Methods: We used National Inpatient Sample (NIS) database to extract data for patients hospitalized with primary diagnosis of prostate cancer using ICD-9 code 185. The 15-year time from 2000 till 2014 was analyzed. The metrics focused on were mean length of stay (LOS), mean cost of hospitalization and rate of discharges. Results: Discharge rate was 32.2 +/- 1.3 in 2000 versus 20.4 +/- 0.8 in 2014 per 100,000, respectively. Mean LOS declined from 3.7 +/- 0.115 days in 2000 to 2.2 +/- 0.044 days in 2014. During this same time period mean hospitalization charges increased from $14,680 +/- 466 to $49,464 +/- 1,019. The average annual inflation rate during this time period was 2.26%. After adjusting for inflation, the cost of stay in 2000 was $20,072 versus $49,464 in 2014. This effect is magnified when analyzing the cost per day of hospitalization. Cost per day in 2000 was $5,424 versus $22,483 in 2014. Conclusions: The increase in cost of inpatient stay is likely due to the advances in multi-modality treatment in prostate cancer. With the aging population and focus on cost conscious allocation of resources, this increase in costs will remain a challenge for hospital decision makers and insurance companies. We have to apply models such as the Markov model that are increasingly used to justify exorbitant prices of individual drugs. Also, given the complexity of health care costs, more variables should be included to rationalize health care spending. Cost metrics such as LOS are out dated given costs of treatments will continue to exceed costs such as nursing care and room and board costs. These complex analyses might be feasible with advances in deep learning which enable consideration of multiple variables in the decision-making process.

Social Media and Electronic Networking Use and Preferences among Undergraduate Turf Science Students

Core Ideas University students are increasingly using electronic means for their primary communication methods. University faculty must be aware of these communication methods if they want to continue to promote “learner-centered” environments. Although students spend a large amount of time on electronic social media they do not feel isolated. Most undergraduate students arrive on campus fluent in electronic communication methods and social media (SM). This cultural or communication shift presents both opportunities and challenges in pedagogy. Social media allows users to share and network with geographically diverse individuals and has the potential for engaging students both inside and outside of the classroom. Used inappropriately, SM may be a disruption and distraction to a classroom environment and academic progress. With so many undergraduates using SM, and the potential for engaging students with SM, a survey was conducted to assess student SM utilization and preferences. The survey was administered to >300 undergraduates enrolled in turf science over 2 consecutive years. The results supported the hypothesis that a very high percent, >95%, of students are using electronic technologies and SM to communicate. Students indicated that the SM application they used most was Facebook, but the number using Twitter was rising. Their primary reason for using SM was, “To keep in touch with family and friends” and students were increasingly accessing SM on mobile devices. Although most students are using electronic communication methods, the majority indicated they still “prefer” to communicate with friends and family face-to-face or in person. These results have direct implications on learning environments and provide insight for educators attempting to engage their students, perhaps by incorporating SM into their instructional techniques and content delivery. Impact Statement In this era of rapid advances in electronic technology, the methods by which current undergraduate students, communicate, share and learn continues to evolve rapidly. Students regularly use social media platforms like Twitter (a micro-blogging application) on their mobile devices to communicate and share information and experiences. This study assessed how undergraduates were using technology with a focus on learning. This information can help instructors better connect with their students and enhance the learner-center classroom environments.

Career Opportunities: Connecting Design Students With Industry

Abstract Given an era of rapid advances in communications and graphic techniques, students of design need exposure to the hectic, highly competitive world of design – well before their student days are over. Is the design hub of New York a closed circuit among industries led by alumni from private colleges and universities? Are student opportunities and career outcomes significantly different depending on the type of institution they attend, rather than the type of degree they earn? In looking at five design institutions in New York City (New York City College of Technology (CUNY), Fashion Institute of Technology (SUNY), Pratt Institute, the School of Visual Arts (SVA) and Cooper Union, two public, two private not-for profit and one private for profit) this study investigates college efforts to connect design students with industry, and hopes to shed light on the unique challenges students attending NYC public colleges face within college and upon graduation as they establish careers. Representatives from five colleges were contacted and asked to respond to a brief survey, consisting of six questions relating to what their schools do to connect students with industry. Everyone contacted responded, and the surveys were followed up with informal phone conversations.