CONTEXT-AWARE DEBUGGING FOR CONCURRENT PROGRAMS

Concurrency faults are difficult to reproduce and localize because they usually occur under specific inputs and thread interleavings. Most existing fault localization techniques focus on sequential programs but fail to identify faulty memory access patterns across threads, which are usually the root causes of concurrency faults. Moreover, existing techniques for sequential programs cannot be adapted to identify faulty paths in concurrent programs. While concurrency fault localization techniques have been proposed to analyze passing and failing executions obtained from running a set of test cases to identify faulty access patterns, they primarily focus on using statistical analysis. We present a novel approach to fault localization using feature selection techniques from machine learning. Our insight is that the concurrency access patterns obtained from a large volume of coverage data generally constitute high dimensional data sets, yet existing statistical analysis techniques for fault localization are usually applied to low dimensional data sets. Each additional failing or passing run can provide more diverse information, which can help localize faulty concurrency access patterns in code. The patterns with maximum feature diversity information can point to the most suspicious pattern. We then apply data mining technique and identify the interleaving patterns that are occurred most frequently and provide the possible faulty paths. We also evaluate the effectiveness of fault localization using test suites generated from different test adequacy criteria. We have evaluated Cadeco on 10 real-world multi-threaded Java applications. Results indicate that Cadeco outperforms state-of-the-art approaches for localizing concurrency faults

Wind Tunnel Seven-Hole Pressure Probe Calibration

The project studies and performs the calibration of a miniature seven-hole pressure probe designed to be utilized in the new wind tunnel of the Embry-Riddle Research Park. The seven-hole pressure probe is to measure flow angularity, which has better sensivity than conventional five-hole pressure probe. However, the seven-hole probe requires calibration due to manufacturing tolerance and its small dimensions. The seven-hole pressure probe is attached to a rotary table allowing the probe to change its pitch and yaw angle within the wind tunnel test section. Data is gathered from combinations of pitch and yaw angles between -10 to 10 degrees, with a step of 0.5 degree. Data gathered in initial wind tunnel tests were utilized for zero-angle offset correction for both pith and yaw angle. A time-series samples were recorded to determine how long the flow settles once pitch and yaw angle is altered. Calibration was then done with polynomial curve fit on MATLAB. An application of the wind tunnel test will also be performed to validate the calibration coefficients. A multiple 7-hole sensor rake also will be proposed which can be used to efficiently scan a large-scale wind tunnel test section, such as the new low-speed wind tunnel at the research park

PROTEIN QUALITY CONTROL IN ANIMAL MODELS OF ALS

Efficient and effective protein quality control are crucial components of cellular homeostasis in the presence of misfolded and aggregated proteins. One method for identifying the mechanistic targets of such protein quality control is via appropriate mouse models. Through exogenous alterations via methods such as drug injection on genetically modified mice, various crucial components of the protein quality control system may be identified. Such modulation could be induced in an effort to increase proteasome efficiency in clearing protein aggregates and alleviate dangerous levels of protein cytotoxicity. Thus in this experiment, a drug targeting the protein quality control system was administered to SOD1G93A transgenic mice to observe the potential alleviation of ALS symptoms. Drug efficacy was gauged based off of a rotarod balance test, grip strength test, and weight measurements. The drug’s efficacy in vivo was the main objective of this research project. Additional research is required to understand the full effects of the drug and any potential confounding mechanisms

ROPEC - ROtary PErcussive Coring Drill for Mars Sample Return

The ROtary Percussive Coring Drill is a light weight, flight-like, five-actuator drilling system prototype designed to acquire core material from rock targets for the purposes of Mars Sample Return. In addition to producing rock cores for sample caching, the ROPEC drill can be integrated with a number of end effectors to perform functions such as rock surface abrasion, dust and debris removal, powder and regolith acquisition, and viewing of potential cores prior to caching. The ROPEC drill and its suite of end effectors have been demonstrated with a five degree of freedom Robotic Arm mounted to a mobility system with a prototype sample cache and bit storage station

De novo reconstruction of satellite repeat units from sequence data

Satellite DNA are long tandemly repeating sequences in a genome and may be organized as high-order repeats (HORs). They are enriched in centromeres and are challenging to assemble. Existing algorithms for identifying satellite repeats either require the complete assembly of satellites or only work for simple repeat structures without HORs. Here we describe Satellite Repeat Finder (SRF), a new algorithm for reconstructing satellite repeat units and HORs from accurate reads or assemblies without prior knowledge on repeat structures. Applying SRF to real sequence data, we showed that SRF could reconstruct known satellites in human and well-studied model organisms. We also found satellite repeats are pervasive in various other species, accounting for up to 12% of their genome contents but are often underrepresented in assemblies. With the rapid progress on genome sequencing, SRF will help the annotation of new genomes and the study of satellite DNA evolution even if such repeats are not fully assembled

Integrating Graceful Degradation and Recovery through Requirement-driven Adaptation

Cyber-physical systems (CPS) are subject to environmental uncertainties such as adverse operating conditions, malicious attacks, and hardware degradation. These uncertainties may lead to failures that put the system in a sub-optimal or unsafe state. Systems that are resilient to such uncertainties rely on two types of operations: (1) graceful degradation, to ensure that the system maintains an acceptable level of safety during unexpected environmental conditions and (2) recovery, to facilitate the resumption of normal system functions. Typically, mechanisms for degradation and recovery are developed independently from each other, and later integrated into a system, requiring the designer to develop an additional, ad-hoc logic for activating and coordinating between the two operations. In this paper, we propose a self-adaptation approach for improving system resiliency through automated triggering and coordination of graceful degradation and recovery. The key idea behind our approach is to treat degradation and recovery as requirement-driven adaptation tasks: Degradation can be thought of as temporarily weakening original (i.e., ideal) system requirements to be achieved by the system, and recovery as strengthening the weakened requirements when the environment returns within an expected operating boundary. Furthermore, by treating weakening and strengthening as dual operations, we argue that a single requirement-based adaptation method is sufficient to enable coordination between degradation and recovery. Given system requirements specified in signal temporal logic (STL), we propose a run-time adaptation framework that performs degradation and recovery in response to environmental changes. We describe a prototype implementation of our framework and demonstrate the feasibility of the proposed approach using a case study in unmanned underwater vehicles.Comment: Pre-print for the SEAMS '24 conference (Software Engineering for Adaptive and Self-Managing Systems Conference

Two-loop Correction to the Instanton Density for the Double Well Potential

Feynman diagrams in the instanton background are used for the calculation of the tunneling amplitude, up to the two-loops order. Some mistakes made in the previous works are corrected. The same method is applied to the next-order corrections to the ground state wave function

Approaches to improving embryo implantation

Embryo implantation represents a complex process vital in ensuring the normal development of pregnancy. Whether embryo implantation is the goal of natural conception or assisted reproductive treatment, the environment within the uterine cavity must be optimised in order to increase the chance of pregnancy. This thesis uses a mixture of research methods to investigate potential approaches to improving embryo implantation. Below are the key findings from this thesis: 1. The vitamin D status in women undergoing assisted reproductive treatment is important. An interventional trial would prove or disprove the merits of vitamin D deficiency treatment in these women. 2. There is not enough evidence to suggest a clear association between vitamin D and recurrent miscarriage, however there is a strong argument for biological plausibility. 3. The use of endometrial fluid collected at the time of embryo transfer in women undergoing assisted reproductive treatments for metabolomics analysis is possible. 4. Women with hydrosalpinx associated tubal infertility should be offered salpingostomy as a treatment option as the natural conception rates are similar to that achieved in in vitro fertilisation treatment