Peer-to-peer overlay networks provide a distributed, fault -tolerant, scalable architecture on which wide-area distributed systems and applications can be built. Two fundamental services provided by peer-to-peer overlay networks are a routing protocol to map keys in a large, virtual ID space to values associated with individual hosts in the overlay network, and a storage service to maintain data objects on behalf of higher-level services, applications, and users. In existing peer-to-peer routing protocols and object maintenance strategies, the system typically gives each host equal responsibilities in terms of routing messages and storing object data and metadata. In reality, however, hosts in the system have unequal capabilities. In this thesis, we propose enhancements to peer-to-peer routing protocols and object maintenance strategies that tailor them to take advantage of resource heterogeneity. Using an approach called ̀S̀hortCuts'', we use three caching techniques to improve routing performance while adjusting the overhead of maintaining consistent state to the available bandwidth of individual hosts. Combined, these caches achieve routing performance that approaches the aggressive performance of one-hop schemes, but with an order of magnitude less communication overhead on average. Compared to previous approaches that place data randomly among hosts, we explored refining object maintenance strategies according to host uptimes and lifetimes. As a first step, we performed an extensive measurement study of permanent host failures in the KAD peer-to-peer file sharing system. Our analysis have shown that, while a significant fraction of the entire population has a very short lifetime (e.g., one connection for a few hours), the network contains a very stable subpopulation of peers with lifetimes of months. As a second step, we propose new object maintenance strategies that bias the placement of redundant data on hosts with longer lifetimes and higher availabilities. Using trace- driven simulation of a peer-to-peer storage system and our trace of hosts in the KAD network, we show that peer-to- peer storage systems can reduce object maintenance overheads by biasing placement on long-lived and highly- available hosts

The research focus on adaptivity in complex systems has propelled an exploration of diverse interactions characterized by state transition processes. However, the investigation of functional variances among processes, rooted in fundamental operands, remains insufficient. Recognizing this gap is crucial for unveiling the constituents of state transitions and their functional boundaries during ongoing adaptivity. To address this, our central focus is on quantifying the functional variance in the interactions of fundamental operands. This approach enables a systematic study of complex adaptive networks grounded in the dynamics of cognitive abilities, where elements adapt and evolve based on cognitive processes. To underscore this point, we emphasize translating ontologically irreducible networks into functionally representable ones at the meso-level, which is essential for assessing their effectiveness. Our active investigation during state transitions explores external interventions, aiming to shed light on mutual influences.

Stem cell therapy has emerged as a valuable tool for the treatment of numerous diseases, including those driven by neurodegenerative processes. There are a wide variety of stem cells that have been identified for therapeutic use, including but not limited to embryonic stem cells, induced pluripotent stem cells, mesenchymal stem cells(MSCs), and neural stem cells. In recent years, placental mesenchymal stem cells have been identified as a unique source of therapy that are relatively less difficult to acquire and don’t pose the same ethical concerns regarding harvest and use.

Minimally invasive surgery for gynecologic cancers is associated with fewer postoperative complications including less blood loss and quicker recovery time compared to traditional laparotomy. The robotic platform has allowed patients access to minimally invasive surgery due to its increased utilization by gynecologic oncologists. Many surgeons have embraced the robotic platform due to its technological advances over traditional laparoscopy including high-definition 3D optics, wristed instrumentation, camera stability and improved ergonomics. While robotic surgery continues as a mainstay in the management of gynecologic cancers, it remains controversial in regards to its cost effectiveness and more recently, its long-term impact on clinical and oncologic outcomes. A strong component of the justification of this surgical platform is based on extrapolated data from traditional laparoscopy despite limited prospective randomized trials for robotic-assisted surgery. In this review, we highlight the use of robotic surgery in the management of gynecologic cancers in special populations: fertility sparing patients, the morbidly obese, the elderly, and patients with a favorable response to neoadjuvant chemotherapy.