This invention provides a method to improve the functionality and/or fertility of sperm by subjecting the isolated sperm to a starvation protocol and/or ionophore. Said sperm can be used to increase artificial insemination by reducing the number of sperm needed as well as improving conception rates.

Pablo Visconti is a Professor in the Department of Veterinary and Animal Sciences at the University of Massachusetts Amherst. His research focuses on understanding how the sperm acquire fertilizing capacity at the molecular level.

High-Speed Computational System for Big Data Processing

Computational architecture to address the challenge of large data volume in search engines.
Problem:
Executing big data applications such as search engines is energy expensive and requires high throughput data processing. Part of the inefficiency data comes from accessing data between local storage and memory and cloud storage. Additionally, the ratio of processing units to memory storage is fixed by the computer architecture and is, therefore, not customizable for big data applications.
Solution:
The system reconfigures the architecture of memory and storage in a computer to offload functions away from the central and intelligence processing units (CPU and IPU). This allows direct access to both local and remote memory, with high bandwidth and low latency. This reduces both software and hardware efficiency limitations and allows for application-dependent CPU/Memory ratios application.
Technology:
A set of logically disaggregated interconnections supports indices that cannot fit into local storage and memory (CPU and IPU). The network consists of Peripheral Component Interconnect Express (PCIe) switches, allowing the field-programmable gate array to access both local and remote memory. Similarly, the memory network serves local and remote requests, however, it uses a point-to-point connection instead of the switch-based network to reduce latency.
Advantages:

The system architecture is shown where the Intelligence Processing Unit (IPU) is connected to a storage and memory pool through a set of interconnections.
Intellectual Property:

Heat Hero Academy

HeatHero Academy is an educational program aimed at youth with the goal of raising awareness and empowering students and their communities to combat urban heat. This program aims to foster climate resilience and inspire students to engage in environmental issues. It combines immersive augmented reality technology with hands-on citizen science projects, in which students can actively engage with and solve real-world urban heat problems.

Background:
Cities tend to be warmer than their surrounding suburban and rural areas, leaving their communities more at risk during heat waves. These risks can be mitigated by adding more vegetation and trees to a city, designing cool roofs and pavements, and making detailed heat response plans. However, another important response that is often overlooked is education: teaching communities about urban heat and empowering them to take action.

Applications:

Eco-Chain Bonds: Revolutionizing Green Bond Investments with AI and Blockchain

EcoChain Bonds is a green bond solution that harnesses the power of blockchain and artificial intelligence. The use of blockchain helps to build trust among stakeholders by providing transparency in a clear and secure record of financial activities. Moreover, the integration of AI algorithms can analyze vast amounts of data with unprecedented speed and accuracy, offering valuable insights into investment opportunities and risks associated with renewable energy projects. By leveraging AI-driven analytics, EcoChain Bonds not only simplifies the investment process but also enhances decision-making capabilities for investors, ultimately driving more sustainable investing practices in green finance and paving the way for more efficient, transparent, and impactful investments in renewable energy initiatives.

Background:
EcoChain Bonds emerges against the backdrop of challenges in the green bond market, aiming to enhance transparency, trust, and efficiency in funding renewable energy projects. Traditional methods often struggle with issues of opacity and complexity, leaving investors hesitant to engage fully. Current solutions include conventional bond offerings, but these lack the transparency and accessibility required to inspire confidence in sustainable investments. Unlike existing methods, which may rely on centralized systems prone to manipulation or lack of transparency, EcoChain Bonds leverages blockchain's inherent security and immutability to provide a trustworthy and transparent environment for investors. Moreover, by employing AI-driven analytics, it offers advanced insights and streamlined processes, addressing the complexities and inefficiencies associated with traditional investment approaches.

Applications:

Heat Smart AI: An Unparalleled Platform for Enhancing Urban Heat Resilience

HeatSmart AI leverages artificial intelligence and machine learning to predict extreme heat risks in urban environments. In times of extreme heat, people living in cities are the most heavily impacted, as urban areas tend to be hotter than surrounding non-urban areas. These impacts can be incredibly dangerous, as heat is the number one weather-related killer in the United States. HeatSmart uses advanced predictive analytics on diverse datasets to analyze and predict urban heat risks, which can allow for advanced warning and time to implement cooling measures to protect city residents and enhance urban heat resilience.

Background:
The rate of global warming since 1982 is approximately three times as fast as the rate from 1850 to the present, and record-high temperatures are being recorded across the globe, with 2023 being the warmest year since global records began in 1850. The impacts of rising temperatures are felt much more strongly in urban environments due to the urban heat island effect, which is a phenomenon in which cities experience significantly higher temperatures than their surrounding suburban and rural areas.

Applications:

Precision Diagnostics: COVID-19 Severity Assessment via Advanced Plasma Biomarkers

24023-05: Precision Diagnostics: COVID-19 Severity Assessment via Advanced Plasma Biomarkers

An inhibitor regulates the activity of NE-alpha-1 anti-antitrypsin (A1AT), which forms a NE-NE-A1AT complex and blocks its activity. Plasma samples from hospitalized patients had approximately 30 times higher NE-A1AT complexes than plasmas from healthy donors, suggesting that such complexes may indicate host tissue damage due to inflammation in respiratory lung infections. Thus, a blood test for this complex could be used to diagnose lung damage or predict long-term lung problems (long COVID) after the acute infection.

The elastolytic activity is crucial in exacerbating pulmonary pathogenesis in COVID-19 patients, especially in the pathologic development of pulmonary fibrosis. Dysregulated neutrophil activity and NETosis lead to elastin degradation, ECM remodeling, and fibrotic changes in COVID-19.

Understanding how neutrophils contribute to lung damage in COVID-19 could identify novel therapeutic targets and prevent pulmonary fibrosis in COVID-19 patients. This could improve patient outcomes during acute and long-term COVID-19 phases.

Applications:

1. Diagnostic marker for lung damage and long COVID

2. Therapeutic target for fibrosis and long COVID

3. Potential for personalized medicine

Value Proposition:

1. Improved diagnosis and treatment of lung damage and long COVID.

2. Develop new therapeutic approaches for fibrosis in COVID-19 and other diseases

3. Personalize treatment for patients based on their individual needs.

4. Contribute to the development of new anti-fibrotic drugs.

Publication: Biomolecules

Status: The protocol has been finalized. UTRF is seeking licensees for this tech on a tech-specific or exclusive basis. Further collaboration may be possible.

Improved Optical Atomic Clock In The Telecom Wavelength Range

Notice.Care.Help.

Notice.Care.Help. is an innovative training program that forms an integral part of the “Together We Care” initiative which aims to foster a community-wide approach to mental health, emphasizing that it’s not just an individual concern but a collective responsibility. Notice.Care.Help. specifically equips university staff with essential knowledge and skills to recognize signs of students facing mental health challenges, cultivate a culture of care within the university community, and provide appropriate assistance based on their roles as employees. By sensitizing staff to the needs of struggling students and arming them with the tools to offer support, Notice.Care.Help. contributes to a more compassionate and responsive university environment, ultimately benefiting the mental well-being of students and promoting a holistic approach to mental health within educational institutions.

Background:
Currently, many universities rely on reactive measures, such as counseling centers and crisis hotlines, to address mental health issues. While these services are crucial, they often come into play after a student has already reached a critical point of distress. The problem lies in the lack of early identification and preventative measures, which can lead to delayed intervention and exacerbation of mental health concerns. Notice.Care.Help. distinguishes itself from current approaches by focusing on the proactive training of university staff and faculty. It empowers them to recognize early signs of student distress, create a culture of care within the academic community, and offer appropriate help promptly. This preventive approach is a departure from the traditional reliance on specialized mental health professionals and crisis management. By leveraging existing university personnel as allies in mental health support, Notice.Care.Help. addresses the issue at its roots, potentially reducing the severity and prevalence of mental health challenges among students while fostering a more inclusive and compassionate campus environment.

Applications:

University of Arizona Strategic Alternative Learning Techniques (SALT) Center

The Strategic Alternative Learning Techniques (SALT) Center is an international leader in developing and providing personal, educational, and mental health/wellness services to support higher education students who learn differently. Through direct service, research, and thought leadership the SALT Center provides a replicable model through which to support the success, retention and graduation of neurodiverse individuals with mild to moderate impairments in higher education. The SALT Center has the opportunity to serve a diverse range of students, working to alleviate educational disparities in higher education.

Background:
By some estimates, as many as 15% of college age students have learning and/or attention differences. These students are among those at highest risk for academic failure. Yet, with the right kind of support, degree seeking college students can build their ability to independently meet and exceed university academic performance standards.

While the Americans with Disabilities Act and Section 504 of the Rehabilitation Act require institutions to make academic adjustments to provide equal access, they do not require postsecondary institutions to diminish academic rigor. Ensuring that students have access to both the accommodations to which they may be legally entitled as well as supplemental programming that can strengthen academic outcomes and prepare them for success after graduation.

The institutional commitment to ensure that ALL students, especially those with learning and attention differences, have the personal and academic support can have a significant impact on an institution's overall persistence, retention, and completion outcomes.

Applications:

Microsoft Excel Collegiate Challenge (MECC) Materials 2022 - 2023

The Microsoft Excel Collegiate Challenge (MECC) is a program that engages students with gamified Excel models to encourage extracurricular learning. Walkthrough videos and example answers guide students in completing the training challenges. Students compete in online and in-person competitions to test their abilities and determine the best collegiate Excel modelers. The materials, including training challenges and competition cases, are available, free of charge, to anyone who signs up at mecc.college. The best way to learn Excel is to practice building models in Excel, and the MECC provides such opportunities.

Background:
Educational financial modeling programs are designed to address the challenge of effectively managing and forecasting financial operations and planning within educational institutions. These technologies provide a robust framework for simulating various financial scenarios, aiding in budgeting, resource allocation, and strategic planning. Current solutions often involve generic financial modeling tools or spreadsheets that require significant manual input and are prone to human error. These conventional tools can also lack the specificity and complexity needed to handle the unique financial dynamics of educational settings, such as fluctuating enrollment numbers and variable funding sources.

Applications:

Latest AIM Projects

Artificial Reproduction Technique