School Psychology Trainer Shortage in the USA: Current Status and Projections for the Future

2009 ◽  
Vol 30 (1) ◽  
pp. 24-42 ◽  
Author(s):  
Kerri L. Clopton ◽  
Charlotte W. Haselhuhn
Keyword(s):  
School Psychology ◽  
Current Status ◽  
The Future ◽  
The Usa

Nonmuscle-Invasive Bladder Cancer: What's Changing and What has Changed

2017 ◽  
Vol 84 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Ramanitharan Manikandan ◽  
Oscar Rodriguez ◽  
Rubén Parada ◽  
Joan Palou Redorta
Keyword(s):  
Bladder Cancer ◽  
Best Practice ◽  
Disease Recurrence ◽  
Invasive Bladder Cancer ◽  
Current Status ◽  
Optimal Care ◽  
Medline Search ◽  
Select Group ◽  
The Future ◽  
Nonmuscle Invasive Bladder Cancer

Purpose Nonmuscle-invasive bladder cancer (NMIBC) is a challenging disease to manage primarily due to its varied clinical course. The management of NMIBC has witnessed a widespread change with respect to its diagnosis and treatment. Although transurethral resection (TUR) and adjuvant bacillus Calmette–Guerin (BCG) stills remain the cornerstone, newer protocols has come into vogue to achieve optimal care. On the basis of a literature review, we aimed to establish ‘what changes has already occurred and what is expected in the future’ in NMIBC. Methods A Medline search was performed to identify the published literature with respect to diagnosis, treatment and future perspectives on NMIBC. Particular emphasis was directed to determinants such as the quality of TUR and the newer modifications, Re-TUR, current status of newer macroscopic and microscopic imaging, role of urinary biomarkers, clinical, histologic and molecular predictors of high-risk disease, administration of intravesical agents, salvage therapy in BCG recurrence and the current best practice guidelines were analyzed. Results and Conclusions Optimal TUR, restaging in select group, incorporation of newer endoscopic imaging and judicious administration of intravesical chemo-immunotherapeutic agents can contribute to better patient care. Although there is a plethora of urinary markers, there is insufficient evidence for their use in isolation. The future probably lies in identification of genetic markers to determine disease recurrence, nonresponders to standard treatment and early institution of alternative/targeted therapy.

scholarly journals Predicting the Dynamics of the COVID-19 Pandemic in the United States Using Graph Theory-Based Neural Networks

2021 ◽  
Vol 18 (7) ◽  
pp. 3834
Author(s):  
Mohammad Reza Davahli ◽  
Krzysztof Fiok ◽  
Waldemar Karwowski ◽  
Awad M. Aljuaid ◽  
Redha Taiar
Keyword(s):  
United States ◽  
Neural Networks ◽  
Graph Theory ◽  
Predictive Model ◽  
Short Term Memory ◽  
The United States ◽  
Graphical Analysis ◽  
Economic Consequences ◽  
Current Status ◽  
The Usa

The COVID-19 pandemic has had unprecedented social and economic consequences in the United States. Therefore, accurately predicting the dynamics of the pandemic can be very beneficial. Two main elements required for developing reliable predictions include: (1) a predictive model and (2) an indicator of the current condition and status of the pandemic. As a pandemic indicator, we used the effective reproduction number (Rt), which is defined as the number of new infections transmitted by a single contagious individual in a population that may no longer be fully susceptible. To bring the pandemic under control, Rt must be less than one. To eliminate the pandemic, Rt should be close to zero. Therefore, this value may serve as a strong indicator of the current status of the pandemic. For a predictive model, we used graph neural networks (GNNs), a method that combines graphical analysis with the structure of neural networks. We developed two types of GNN models, including: (1) graph-theory-based neural networks (GTNN) and (2) neighborhood-based neural networks (NGNN). The nodes in both graphs indicated individual states in the US states. While the GTNN model’s edges document functional connectivity between states, those in the NGNN model link neighboring states to one another. We trained both models with Rt numbers collected over the previous four days and asked them to predict the following day for all states in the USA. The performance of these models was evaluated with the datasets that included Rt values reflecting conditions from 22 January through 26 November 2020 (before the start of COVID-19 vaccination in the USA). To determine the efficiency, we compared the results of two models with each other and with those generated by a baseline Long short-term memory (LSTM) model. The results indicated that the GTNN model outperformed both the NGNN and LSTM models for predicting Rt.

Application of Probabilistic and Interactive Information in Verifying Machine System and Kernels Based on Relational Modality

2010 ◽  
Vol 143-144 ◽  
pp. 67-71 ◽  
Author(s):  
Dong Ping Li ◽  
Zhi Ming Qu
Keyword(s):  
World Wide Web ◽  
World Wide ◽  
Position Paper ◽  
Current Status ◽  
Moore’S Law ◽  
Moore's Law ◽  
Machine System ◽  
The World ◽  
The Future

The networking approach to the World Wide Web is defined not only by the exploration of architecture, but also by the confirmed need for interrupts. Given the current status of authenticated archetypes, steganographers dubiously desire the analysis of scatter/gather I/O. the focus in this position paper is not on whether Moore's Law can be made concurrent, distributed, and pervasive, but rather on proposing an analysis of 32 bit architectures (Grange). It is concluded that, using probabilistic and interactive information and based on relational modality, the machine system and kernels are verified, which is widely used in the future.

State-of-the-art literature review on inventory models for perishable products

2018 ◽  
Vol 15 (3) ◽  
pp. 306-346 ◽  
Author(s):  
Vaibhav Chaudhary ◽  
Rakhee Kulshrestha ◽  
Srikanta Routroy
Keyword(s):  
Inventory Management ◽  
Systemic Review ◽  
Current Status ◽  
Future Research ◽  
Inventory Models ◽  
Research Gaps ◽  
Content Type ◽  
Perishable Items ◽  
Perishable Inventory ◽  
The Future

PurposeThe purpose of this paper is to review and analyze the perishable inventory models along various dimensions such as its evolution, scope, demand, shelf life, replenishment policy, modeling techniques and research gaps.Design/methodology/approachIn total, 418 relevant and scholarly articles of various researchers and practitioners during 1990-2016 were reviewed. They were critically analyzed along author profile, nature of perishability, research contributions of different countries, publication along time, research methodologies adopted, etc. to draw fruitful conclusions. The future research for perishable inventory modeling was also discussed and suggested.FindingsThere are plethora of perishable inventory studies with divergent objectives and scope. Besides demand and perishable rate in perishable inventory models, other factors such as price discount, allow shortage or not, inflation, time value of money and so on were found to be combined to make it more realistic. The modeling of inventory systems with two or more perishable items is limited. The multi-echelon inventory with centralized decision and information sharing is acquiring lot of importance because of supply chain integration in the competitive market.Research limitations/implicationsOnly peer-reviewed journals and conference papers were analyzed, whereas the manuals, reports, white papers and blood-related articles were excluded. Clustering of literature revealed that future studies should focus on stochastic modeling.Practical implicationsStress had been laid to identify future research gaps that will help in developing realistic models. The present work will form a guideline to choose the appropriate methodology(s) and mathematical technique(s) in different situations with perishable inventory.Originality/valueThe current review analyzed 419 research papers available in the literature on perishable inventory modeling to summarize its current status and identify its potential future directions. Also the future research gaps were uncovered. This systemic review is strongly felt to fill the gap in the perishable inventory literature and help in formulating effective strategies to design of an effective and efficient inventory management system for perishable items.

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