The Following Robot

The objective of this project is to design, build, and test an autonomous robot with an associated Android application. The robot uses on board inertial measurement sensors (magnetometer, accelerometer, gyroscope) and coordinates itself through Bluetooth communication with the similar built­in measurement sensors on the Android phone to mimic and follow movement. The Following Robot incorporates the same basic movement functionality as a typical RC car. The robot follows the user’s phone through an application on one’s phone. This application accesses the phone’s accelerometer and gyroscope data and translates into appropriate conversions. Methods of tracking and calculating distance or angular displacement includes numeric integration. Once a certain turning angle or certain distance has reached a predefined threshold, the application sends a command to the robot via Bluetooth indicating which movement to execute: left, right, forward, or backward. The Following Robot has its own sensors to accurately match the threshold of the phone. Combining these two interfaces, the Following Robot can mimic the movements of the user hence the name “following”. Additionally, the application accesses its magnetometer to send the current direction and/or orientation of the phone. The robot uses this information and aligns its direction to match the phone with a click of a button on the application

Down-regulation of myeloid cell leukemia 1 by epigallocatechin-3-gallate sensitizes rheumatoid arthritis synovial fibroblasts to tumor necrosis factor Α–induced apoptosis

Objective Overexpression of the antiapoptotic protein myeloid cell leukemia 1 (Mcl-1) in rheumatoid arthritis (RA) synovial fibroblasts is a major cause of their resistance to tumor necrosis factor Α (TNFΑ)–induced apoptosis. This study was undertaken to evaluate the efficacy of epigallocatechin-3-gallate (EGCG) in down-regulating Mcl-1 expression and its mechanism of RA synovial fibroblast sensitization to TNFΑ-induced apoptosis. Methods EGCG effects on cultured RA synovial fibroblast cell morphology, proliferation, and viability over 72 hours were determined by microscopy and a fluorescent cell enumeration assay. Caspase 3 activity was determined by a colorimetric assay. Western blotting was used to evaluate the apoptosis mediators poly(ADP-ribose) polymerase (PARP), Mcl-1, Bcl-2, Akt, and nuclear translocation of NF-ΚB. Results In RA synovial fibroblasts, EGCG (5–50 Μ M ) inhibited constitutive and TNFΑ-induced Mcl-1 protein expression in a concentration- and time-dependent manner ( P < 0.05). Importantly, EGCG specifically abrogated Mcl-1 expression in RA synovial fibroblasts and affected Mcl-1 expression to a lesser extent in osteoarthritis and normal synovial fibroblasts or endothelial cells. Inhibition of Mcl-1 by EGCG triggered caspase 3 activity in RA synovial fibroblasts, which was mediated via down-regulation of the TNFΑ-induced Akt and NF-ΚB pathways. Caspase 3 activation by EGCG also suppressed RA synovial fibroblast growth, and this effect was mimicked by Akt and NF-ΚB inhibitors. Interestingly, Mcl-1 degradation by EGCG sensitized RA synovial fibroblasts to TNFΑ-induced PARP cleavage and apoptotic cell death. Conclusion Our findings indicate that EGCG itself induces apoptosis and further sensitizes RA synovial fibroblasts to TNFΑ-induced apoptosis by specifically blocking Mcl-1 expression and, hence, may be of promising adjunct therapeutic value in regulating the invasive growth of synovial fibroblasts in RA.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62991/1/24488_ftp.pd

Incident and long-term opioid therapy among patients with psychiatric conditions and medications: a national study of commercial health care claims

There is growing evidence that opioid prescribing in the United States follows a pattern in which patients who are at the highest risk of adverse outcomes from opioids are more likely to receive long-term opioid therapy. These patients include, in particular, those with substance use disorders (SUDs) and other psychiatric conditions. This study examined health insurance claims among 10,311,961 patients who filled prescriptions for opioids. Specifically, we evaluated how opioid receipt differed among patients with and without a wide range of preexisting psychiatric and behavioral conditions (ie, opioid and nonopioid SUDs, suicide attempts or other self-injury, motor vehicle crashes, and depressive, anxiety, and sleep disorders) and psychoactive medications (ie, antidepressants, benzodiazepines, hypnotics, mood stabilizers, antipsychotics, and medications used for SUD, tobacco cessation, and attention-deficit/hyperactivity disorder). Relative to those without, patients with all assessed psychiatric conditions and medications had modestly greater odds of subsequently filling prescriptions for opioids and, in particular, substantially greater risk of long-term opioid receipt. Increases in risk for long-term opioid receipt in adjusted Cox regressions ranged from approximately 1.5-fold for prior attention-deficit/hyperactivity disorder medication prescriptions (hazard ratio [HR] = 1.53; 95% confidence interval [CI], 1.48-1.58) to approximately 3-fold for prior nonopioid SUD diagnoses (HR = 3.15; 95% CI, 3.06-3.24) and nearly 9-fold for prior opioid use disorder diagnoses (HR = 8.70; 95% CI, 8.20-9.24). In sum, we found evidence of greater opioid receipt among commercially insured patients with a breadth of psychiatric conditions. Future studies assessing behavioral outcomes associated with opioid prescribing should consider preexisting psychiatric conditions

Association of Mental Health Conditions and Treatments With Long-term Opioid Analgesic Receipt Among Adolescents

Importance: Adults with mental health conditions are more likely than those without to receive long-term opioid therapy. Less is known about opioid therapy among adolescents, especially those with mental health conditions. Objective: To examine associations between preexisting mental health conditions and treatments and initiation of any opioid and long-term opioid therapy among adolescents. Design, Setting, and Participants: A cohort of 1 224 520 incident opioid recipients without cancer diagnoses aged 14 to 18 years at first receipt was extracted from nationwide commercial health care claims data from January 1, 2003, to December 31, 2014. Analysis was conducted from August 19, 2016, to November 16, 2017. Associations between preexisting mental health conditions and treatments and any opioid receipt were examined by comparing recipients with nonrecipients matched on sex, calendar year and years of age of first enrollment, and months of enrollment (prior to the index month for recipients, ever for nonrecipients). Associations between preexisting mental health conditions and treatments and subsequent long-term opioid therapy were examined among recipients with at least 6 months' follow-up using Cox proportional hazards regressions adjusted for demographics. Exposures: Mental health condition diagnoses and treatments recorded in inpatient, outpatient, and filled-prescription claims prior to opioid receipt. Main Outcomes and Measures: Opioid receipt, defined as any opioid analgesic prescription claim, and long-term opioid therapy, defined as more than 90 days' supply within a 6-month window having no gaps in supply of more than 32 days. Results: Of the 1 224 520 new opioid recipients included, the median age at first receipt was 17 years (interquartile range, 16-18 years), and 51.1% were female. Median follow-up after first receipt was 625 days (interquartile range, 255-1268 days). Adolescents with anxiety, mood, neurodevelopmental, sleep, and nonopioid substance use disorders and most mental health treatments were significantly more likely to receive any opioid (odds ratios from 1.13 [95% CI, 1.10-1.16] for nonopioid substance use disorders to 1.69 [95% CI, 1.58-1.81] for nonbenzodiazepine hypnotics). Among the 1 000 453 opioid recipients (81.7%) who had at least 6 months' follow-up, the cumulative incidence of long-term opioid therapy was 3.0 (95% CI, 2.8-3.1) per 1000 recipients within 3 years after first opioid receipt. All preexisting mental health conditions and treatments were strongly associated with higher rates of long-term opioid therapy (adjusted hazard ratios from 1.73 [95% CI 1.54-1.95] for attention-deficit/hyperactivity disorder to 8.90 [95% CI, 5.85-13.54] for opioid use disorder). Conclusions and Relevance: Commercially insured adolescents with many types of preexisting mental health conditions and treatments were modestly more likely to receive any opioid and were substantially more likely to subsequently transition to long-term opioid therapy relative to those without, although overall rates of long-term opioid therapy were low

A 5G Automated Guided Vehicle SME testbed for resilient future factories

Factory automation design engineers building the Smart Factory can use wireless 5G broadband networks for added design flexibility. 5G New Radio builds upon previous cellular communications standards to include technology for “massive machine-type communication” and “ultra-reliable and low-latency communication”. In this work, the authors augment an automated guided vehicle with 5G for additional capabilities (e.g., streaming high-resolution video and enabling long-distance teleoperation), increasing the mobile applications for industrial equipment. Such use cases will provide valuable knowledge to engineers examining 5G for novel smart manufacturing solutions. Our 5G private network testbed is a platform for wireless performance research in industrial locations and provides a development mule for flexible smart manufacturing systems. The rival wireless technology to 5G in industrial settings is Wi-Fi and it is included in the testbed. Furthermore, the authors noted challenges, often unconsidered, facing the move to digital manufacturing technologies. Therefore, the authors summarise the emerging challenges when implementing new digital factory systems, including challenges linked to societal concerns around sustainability and supply chain resilience. The new Smart Factory technologies, including 5G communications, will have their roles to play in alleviating these challenges and ensuring economies have resilient future factories

A defensive strategy against beam training attack in 5G mmWave networks for manufacturing

Millimeter-wave (mmWave) carriers are an essential building block of fifth-generation (5G) systems. Satisfactory performance of the communications over the mmWave spectrum requires an alignment between the signal beam of the transmitter and receiver, achieved via beam training protocols. Nevertheless, beam training is vulnerable to jamming attacks, where the attacker intends to send jamming signals over different spatial directions to confuse legitimate nodes. This paper focuses on defending against this attack in smart factories where a moving Automated Guided Vehicle (AGV) communicates with a base station via a mmWave carrier. We introduce a defensive strategy to cope with jamming attacks, including two stages: jamming detection and jamming mitigation. Developed based on autoencoders, both algorithms can learn the characteristics/features of the received signals at the AGV. They can be employed consecutively before performing the downlink data transmission. In particular, once a jamming attack is identified, the jamming mitigation can be utilized to retrieve the corrupted received signal strength vector, allowing a better decision during the beam training operation. In addition, the proposed algorithm is straightforward and fully compliant with the existing beam training protocols in 5G New Radio. The numerical results show that not only the proposed defensive strategy can capture more than 80% of attack events, but it also improves the average signal-to-interference-plus-noise-ratio significantly, i.e., up to 15 dB

Rapid beam training at terahertz frequency with contextual multi-armed bandit learning

Terahertz (THz) frequency technology holds great promise for enabling high data rates and low latency, essential for manufacturing applications within Industry 4.0. To achieve these, beam training is necessary to enable MIMO communications without the need for explicit channel state information (CSI). In this context, the Multi-Armed Bandit (MAB) algorithms are able to facilitate online learning and decision-making in beam training, eliminating the necessity for extensive offline training and data collection. In this paper, we introduce three algorithms to investigate the applications of MAB in beam training at Terahertz frequency: UCB, Loc-LinUCB, and Probing-LinUCB. While UCB builds upon the well-established Upper Confidence Bound algorithm, Loc-LinUCB and Probing-LinUCB utilize the location of the user equipment (UE) and probing information to enhance decision-making, respectively. The beam training protocols for each algorithm are also detailed. We evaluate the performance of these algorithms using data generated by the DeepMIMO framework, which simulates abrupt changes and various challenging characteristics of wireless channels encountered in realistic scenarios as UEs move. The results illustrate that Loc-LinUCB and Probing-LinUCB outperform UCB, showing the potential of leveraging contextual MAB for beam training in Terahertz communications

In-Space Assembly Capability Assessment for Potential Human Exploration and Science Applications

Human missions to Mars present several major challenges that must be overcome, including delivering multiple large mass and volume elements, keeping the crew safe and productive, meeting cost constraints, and ensuring a sustainable campaign. Traditional methods for executing human Mars missions minimize or eliminate in-space assembly, which provides a narrow range of options for addressing these challenges and limits the types of missions that can be performed. This paper discusses recent work to evaluate how the inclusion of in-space assembly in space mission architectural concepts could provide novel solutions to address these challenges by increasing operational flexibility, robustness, risk reduction, crew health and safety, and sustainability. A hierarchical framework is presented to characterize assembly strategies, assembly tasks, and the required capabilities to assemble mission systems in space. The framework is used to identify general mission system design considerations and assembly system characteristics by assembly strategy. These general approaches are then applied to identify potential in-space assembly applications to address each challenge. Through this process, several focus areas were identified where applications of in-space assembly could affect multiple challenges. Each focus area was developed to identify functions, potential assembly solutions and operations, key architectural trades, and potential considerations and implications of implementation. This paper helps to identify key areas to investigate were potentially significant gains in addressing the challenges with human missions to Mars may be realized, and creates a foundation on which to further develop and analyze in-space assembly concepts and assembly-based architectures

Sub-6 GHz channel modelling and evaluation in indoor industrial environments

This paper presents sub-6 GHz channel measurements using a directional antenna at the transmitter and a directional or omnidirectional antenna at the receiver at 4.145 GHz in sparse and dense industrial environments for a line-of-sight scenario. Furthermore, the first measured over-the-air error vector magnitude (EVM) results depending on different 5G new radio modulation and coding schemes (MCSs of16 QAM, 64 QAM and 256 QAM) are provided. From the measurement campaigns, the path loss exponents (PLE) using a directional and an omnidirectional antenna at the receiver in the sparse and the dense environment are 1.24/1.39 and 1.35/1.5, respectively. PLE results are lower than the theoretical free space PLE of 2, indicating that indoor industrial environments have rich multipaths. The measured power delay profiles show the maximum root mean square (RMS) delay spreads of 11 ns with a directional antenna and 34 ns with an omnidirectional antenna at the receiver in a sparse industrial environment. However, in a dense industrial environment the maximum RMS delay spreads are significantly increased: maximum RMS delay spreads range from 226 to 282 ns for the omnidirectional and the directional antenna configuration. EVM measurements show that to increase coverage and enable higher MCS modes to be used for reliable data transmission, in both industrial environments using a directional antenna at the transmitter and the receiver is required. The large-scale path loss models, multipath time dispersion characteristics and EVM results provide insight into the deployments of 5G networks operating at sub-6 GHz frequency bands in different industrial environments