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Title: Modeling enantiomeric separations as an interfacial process using amylose tris(3,5-dimethylphenyl carbamate) (ADMPC) polymers coated on amorphous silica
Creator: Wang,Xiaoyu, Jameson, Cynthia, Murad, Sohail
Date: 2020, 2020-01-20
Publisher: ACS Langmuir
Description: In the present study, we present a model to predict the chiral separation results for drug enantiomers by ADMPC chiral stationary phase in...
Show moreIn the present study, we present a model to predict the chiral separation results for drug enantiomers by ADMPC chiral stationary phase in high performance liquid chromatography (HPLC) wherein multiple ADMPC polymer strands are coated on an amorphous silica slab. Both reactive and classical MD are used to prepare the surface. Using various MD techniques, we successfully coat ADMPCs onto the surface without losing the structural character of the backbone in the presence of the solvent system. Not only is this model more representative of the polymer surface on a solid support that is encountered by the enantiomers, it also provides more opportunities for chiral molecules interacting with ADMPC, resulting in a better agreement compared with experiment when we use overall average quantities as the metric. In our previous studies, we had used a single polymer strand of amylose tris(3,5-dimethylphenyl carbamate) (ADMPC) in the solvent system. The new model provides the possibility for large drug molecules to interact with two polymer strands at the same instant, which was not possible to model with only a single polymer strand in the solvent. For a better understanding of why some metrics are better predictors than others, we use charts of the distribution of hydrogen bonding lifetimes in this work to display the hydrogen-bonding information for various donor-acceptor pairs that contribute to the interaction events determining the relative retention times for the enantiomers. We also examine the contribution of the ring-ring interactions to the molecular recognition process and ultimately to differential retention of S and R enantiomers. The results using the new model are more consistent than the previous models and resolves the problematic case of two drugs, thalidomide and valsartan.
Sponsorship: The National Science Foundation (CBET 1545560)
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Title: Leveraging the flexibility of Islandora to create a dual-use digital repository
Creator: Esquivel, Alicia, Fluhr, Tim, Strohm, Adam
Date: 2021, 2021
Publisher: Henry Stewart Publications
Collection: Journal of Digital Media Management

Title: Investigation of Novel Solid Polymer Electrolytes and Lithium Salts for Rechargeable Lithium Batteries
Creator: Zhao, Wendy
Date: 2021
Description: Lithium-ion batteries (LIBs) are extensively used in many consumer electronic products. LIBs have great potential for application in electric...
Show moreLithium-ion batteries (LIBs) are extensively used in many consumer electronic products. LIBs have great potential for application in electric vehicles by virtue of their high power density and charge cycles. Research and development in this area has been focused on all around the globe. The major challenges include high cost, safety issues of the solvent based electrolytes, and low conductivities at ambient temperature of the solid polymer electrolytes (SPEs).This dissertation describes four novel electrolyte systems and a series of low lattice energy lithium salts synthesized and characterized for applications in LIBs. First, a new SPE has been derived from oligomeric poly(ethylene oxide) (PEO)-grafted crosslinked polystyrene (XPS) microspheres containing 1-2 lithium sulfonate moieties. This SPE possesses amorphous character with a glass transition temperature (Tg) around 135 ºC, displayed a good electrochemical stability with excellent ionic conductivity in excess of 10^-4 S/cm at 25ºC, and no significant thermal decomposition until 420 ºC. Second, a hybrid composite polymer electrolyte (CPE) was constructed with a gel matrix formed through hydrogen bonding by incorporating nanoparticles of fumed silica into the nanoscale network of PEO-XPS. Fumed silica with large surface modification group like polysiloxane formed an ideal gel structure offering significant high mechanical strength above 10^4 Pa, and a good ionic conductivity at 25°C. Third, a nonvolatile x-linked gel membrane electrolyte was synthesized with amino methacrylate, to introduce hemi-labile ligands as ionic liquid, into the polymer network. This new material exhibited improved salt solubility and ionic conductivity, due to the fast ligand exchange that facilitates the lithium ion structural transport, and also displayed an excellent electrochemical stability(4.8 V vs, Li/Li+). Fourth, a self-healing and thermal reversible polymer electrolyte designed based on Diels-Alder conjugation between multi-maleimides (2M-3M) and multi-furans (2F-4F) was synthesized. The reversible x-linking was realized through Diels-Alder (DA) and Retro-DA reactions by applying heating (>130°C)/cooling (<90°C) cycles. Last, new lithium salts with star and branch structures containing 1-4 of imide or methide moieties were synthesized and evaluated in PEO electrolyte system. These salts demonstrated good ambient temperature ionic conductivity at low concentrations, and the electrochemical stabilities were equal to or better than the most commonly used lithium salt, lithium bis(trifluoromethanesulfonyl)imide (LiTFSI). Synthesis and characterization, including electrochemical properties, thermal and electrochemical stabilities, mechanical behaviors and surface morphologies of these new materials are described and discussed.
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Title: BLOCKCHAIN FOR TRANSACTIVE ENERGY MARKET WITH NETWORKED MICROGRIDS
Creator: Yan, Mingyu
Date: 2021
Description: Transactive energy, which allows and incentivizes microgrids (MGs) to trade energy with each other, is regarded as the next-generation energy...
Show moreTransactive energy, which allows and incentivizes microgrids (MGs) to trade energy with each other, is regarded as the next-generation energy management scheme to accommodate the penetration of distributed energy resources (DERs). Blockchain provides an effective and decentralized strategy, which can address the operational challenges introduced by the transactive energy market. This thesis is aimed at providing effective transactive energy markets for incentivizing MGs to trade energy and utilizing blockchain technologies to provide a secure and efficient energy trading environment for all participants.First, this thesis offers a centralized transactive market for networked MGs to transact energy through the centralized distribution system operator (DSO) while ensuring the power network limits. All MGs cooperate in this market and the cooperative behaviors are captured using the cooperative game with externalities. A two-level problem is studied to allocate the total payoff to all participating MGs. Numerical results for a 4-MG system and the IEEE 33-bus show the validity of the centralized transactive energy model. Second, this thesis proposes a two-level network-constrained peer-to-peer (P2P) transactive energy for multi-MGs, which guarantees the distribution power network security and allows MGs to trade energy with each other flexibly. At the lower level, a P2P transactive energy is employed for multi-MGs to trade energy with each other. A multi-leader multi-follower (MLMF) Stackelberg game approach is utilized to model the energy trading process among MGs. At the upper level, the DSO reconfigures the distribution network based on the P2P transactive energy trading results by applying the AC optimal power flow considering the distribution network reconfiguration. If there are any network violations, the DSO requests energy trading adjustments at the lower level for network security. Numerical results for a 4-MG system, the modified IEEE 33-bus, and the 123-bus distribution power systems show the effectiveness of the proposed transactive energy model and its solution technique. Third, this thesis adopts the blockchain for the peer-to-peer transactive energy market among MGs. A two-level integrated blockchain-power system is provided, in which all MGs and the DSO are equipped with blockchain. At the lower level, MGs trade energy with each other through the lower-level MG blockchain, while the DSO manages the network security through the upper level DSO blockchain. We illustrate how to utilize blockchain technologies, i.e., public and private keys and smart contracts, to provide an efficient and secure energy trading environment for all MGs. Last, this thesis applies the blockchain for transacting energy and carbon right for networked MGs. MGs transact energy and carbon right through the centralized DSO while ensuring the power network limits. The introduction of blockchain achieves secure and decentralized market settlements in this centralized market. Numerical results for a 4-MG system and modified IEEE 33-bus systems show the effectiveness of the proposed transactive energy and carbon market.
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Title: IMPROVING DEEP LEARNING BASED SEMANTIC SEGMENTATION USING CONTEXT INFORMATION
Creator: Xia, Zhengyu
Date: 2021
Description: Semantic segmentation is an important but challenging task in computer vision because it aims to assign each pixel a category label accurately...
Show moreSemantic segmentation is an important but challenging task in computer vision because it aims to assign each pixel a category label accurately. Nowadays, applications such as autonomous driving, path navigation, image search engine, or augmented reality require accurate semantic analysis and efficient segmentation mechanisms. In this thesis, we propose multiple models to improve the performance of semantic segmentation. In the first part, we focus on the single-task network, which aims to improve the performance of semantic segmentation. Our research includes exploiting context information using mixed spatial pyramid pooling to extract dense context-embedded features in FCN-based semantic segmentation. We also propose a GAF module to generate a global context-based attention map to guide the shallow-layer feature maps for better pixel localization. In the second part, we focus on a multi-task network that incorporates semantic segmentation to improve other computer vision tasks such as object detection. Specifically, a multi-task network, along with a learning strategy is designed to let semantic segmentation and object detection assist each other since they are highly correlated. Also, we include weakly-supervised multi-label semantic segmentation learning to deal with the shortage of high-quality training examples and to improve the performance of cross-domain object detection. In the third part, we focus on improving the performance of video panoptic segmentation, which is a unified network that incorporates semantic segmentation and instance segmentation using video streams. We design a new ConvLSTM pyramid to transmit spatio-temporal contextual information in our video panoptic segmentation network. Specifically, we propose a modified ConvLSTM to generate temporal contextual information. Also, we design an MSTPP module to obtain mixed spatio-temporal context-embedded feature maps. Experimental results on different datasets show that our proposed method achieves better performance compared with the state-of-the-art methods.
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Title: ANALYTIC STUDY OF THE CELLULAR FUNCTIONS OF UBL4A
Creator: Zhang, Huaiyuan
Date: 2021
Description: Ubiquitin-like protein 4A (Ubl4A) is a small protein encoded by a “housekeeping” gene that locates on the X chromosome. As a multi-functional...
Show moreUbiquitin-like protein 4A (Ubl4A) is a small protein encoded by a “housekeeping” gene that locates on the X chromosome. As a multi-functional protein, it has roles in a variety of cellular events including anti-tumorigenesis, response to DNA damage, inhibiting the fusion between autophagosome and lysosome, and docking of the tail-anchored proteins to the endoplasmic reticulum. We have previously reported that the newborns from Ubl4A-deficient mice had a high rate of mortality due to defect of AKT-dependent glucose metabolism. At the molecular level, Ubl4A directly binds with the actin related protein (Arp) 2/3 complex to accelerate the building up of the actin branching network, which further promotes the translocation and activation of the Akt, a key kinase for multiple cellular processes, from the cytosol to the plasma membrane.In further exploration of the molecular basis of Ubl4A in cell survival, here, we demonstrated that Ubl4A is critical for mitochondrial fusion and cell survival under nutrient depletion. In WT (wild-type) cells, the association of Ubl4A and the Arp2/3 complex serves as a primed “pool” of the actin branching network near mitochondria and enables mitochondria to fuse quickly for energy conservation upon starvation insult. However, such a “ready-to-go pool” of mitochondria was significantly decreased in the Ubl4A-deficient cells. As the result, the mitochondria became fragmentated, exhibited decreased trans-membrane potential, and accumulated ROS (reactive oxygen species), consequently, initiated mitochondria-mediated apoptosis. In this study, we also observed that Ubl4A-deficient mice displayed type II diabetic phenotype under a high-fat diet feeding. The preliminary results showed that these Ubl4A-deficient mice were more sensitive to glucose intolerance than their WT littermates, most likely owing to a delay in glucose uptake, and/or insulin secretion, both of which require the Arp2/3-actin branching network. We speculated that Ubl4A might be involved in cellular vesicle formation and/or secretion, but further investigation is needed to approve this hypothesis. Taken together, these findings provide a novel function of Ubl4A and further insight into the multi-functional roles of Ubl4A in mammalian cells, as well as the molecular basis for understanding the clinical relevance of Ubl4A in related human diseases.
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Title: Fate of Listeria Monocytogenes on Hard-cooked Eggs Treated With Citric Acid
Creator: Zeng, Hui
Date: 2021
Description: Commercially-prepared hard-cooked eggs are available for foodservice and to the public in retail grocers. Potential contamination with...
Show moreCommercially-prepared hard-cooked eggs are available for foodservice and to the public in retail grocers. Potential contamination with Listeria monocytogenes during or after the cooking and peeling steps is of concern since this pathogen can proliferate at refrigeration temperatures. Citric acid is a common preservative used in the food industry to treat hard-boiled eggs (HBEs). The purpose of this project was to evaluate the efficacy of citric acid treatment of HBEs to reduce the population levels of L. monocytogenes during 24 h (treatment trials) and 28 d storage (storage trials) at 5 or 25°C. Fresh eggs were boiled for 12 min, cooled to 4°C, peeled, and stored at 5°C for 24 h prior to experiments. In treatment trials, HBEs were dip inoculated with a 4-strain cocktail of rifampicin-resistant L. monocytogenes resulting in either 4 (low) or 7 (high) log CFU/egg. Eggs were air-dried 10 min, followed by treatment with pH 2.5 citric acid (PHCA) or 0.2 M citric acid (calculated as the molarity resulting in pH 2.5: MCA) at 5 or 25°C for 24 h. In treatment-storage trials, citric acid treatment of HBEs occurred before or after inoculation, followed by 28-d storage at 5 or 25°C. L. monocytogenes populations were enumerated by homogenization of eggs with BLEB and cultivation on BHI/rifampicin agar. Enrichment in BLEB was conducted if the pathogen was below the level of enumeration. Significant differences in the populations of L. monocytogenes due to temperature of the acid treatment (5 or 25°C) or the two citric acids (MCA and PHCA) were determined using Student’s T-test and ANOVA with Tukey’s post-test, p ≤ 0.05. Overall, the largest L. monocytogenes reduction occurred after 6 h treatment of HBEs with PHCA at 25°C (1.59 ± 0.00 log CFU/egg) and after 24 h with MCA at 5°C (1.23 ± 0.54 log CFU/egg) when the pathogen was inoculated at the low and high levels, respectively. In treatment-storage trials, citric acid treatment after HBE contamination resulted in a fewer number of samples where the pathogen was detected compared to when treatment occurred before contamination. Citric acid treatment for 24 h also resulted in a greater number of samples where L. monocytogenes was not detected than the 1 h treatment. The results of this study determined that L. monocytogenes could survive on HBEs treated with citric acid, regardless of treatment or storage temperature and acid concentration (PHCA or MCA).
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Title: Using population-level data to examine between-group health differences among transgender and cisgender United States military veterans
Creator: Woodward, Honor
Date: 2021
Description: Some subgroups of military veterans, including those with marginalized identities, may be especially vulnerable to poor health. This...
Show moreSome subgroups of military veterans, including those with marginalized identities, may be especially vulnerable to poor health. This hypothesis is supported by the Minority Stress Theory framework, which posits that disparities in health can be attributed to the stress that minority individuals experience as a result of discrimination, prejudice, and oppression (Meyer, 1995; Meyer, 2003). A specific, potentially marginalized group of veterans that is under-explored regarding health is transgender veterans. Using data from the 2019 U.S. Behavioral Risk Factor Surveillance System (BRFSS), the current study hypothesized that transgender U.S. military veterans will report worse health than cisgender U.S. military veterans. Using case control matching, groups of transgender veterans (n = 124) and cisgender veterans (n = 104) were compared on several population-relevant health outcome measures. Chi-square tests of independence were conducted to test for significant differences between transgender and cisgender military veterans on the likelihood of experiencing certain health conditions, engaging in certain health behaviors, and utilizing health care services. Independent samples t-tests were used to test continuous health outcomes, such as self-reported mental health, physical health, and access to health care services. Gender identity was significantly associated with only one health outcome variable, with transgender veterans being more likely than cisgender veterans to have received a formal depression diagnosis (p = .01, phi = .17). No significant differences emerged between transgender and cisgender veterans on continuous health outcome variables. This suggests that previous literature on health disparities between transgender and cisgender individuals may not be generalizable to transgender veterans.
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Title: MACHINE VISION NAVIGATION SYSTEM FOR VISUALLY IMPAIRED PEOPLE
Creator: Yang, Guojun
Date: 2021
Description: Visually impaired people are often challenged in the efficient navigation of complex environments. Moreover, helping them navigate intuitively...
Show moreVisually impaired people are often challenged in the efficient navigation of complex environments. Moreover, helping them navigate intuitively is not a trivial task. Cognitive maps derived from visual cues play a pivotal role in navigation. In this dissertation, we present a sight-to-sound human–machine interface (STS-HMI), a novel machine vision guidance system that enables visually impaired people to navigate with instantaneous and intuitive responses. This proposed system extracts visual context from scenes and converts them into binaural acoustic cues for users to establish cognitive maps. The development of the proposed STS-HMI system encompasses four major components: (i) a machine vision–based indoor localization system that uses augmented reality (AR) markers to locate the user in GPS-denied environments (e.g., indoor); (ii) a feature-based object detection and localization system called the simultaneous localization and mapping (SLAM) algorithm, which tracks the mobility of users when AR markers are not visible; (iii) a path-planning system that creates a course towards a destination while avoiding obstacles; and (iv) an acoustic human–machine interface to navigate users in complex navigation courses. Throughout the research and development of this dissertation, each component is analyzed for optimal performance. The navigation algorithms are used to evaluate the performance of the STS-HMI system in a complicated environment with difficult navigation paths. The experimental results confirm that the STS-HMI system advances the mobility of visually impaired people with minimal effort and high accuracy.
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Title: Frictional behavior of bronze-graphite composite as sliding element in the base isolation system
Creator: You, Da
Date: 2021
Description: There are many calamities around the world, one of the most dangerous disasters is earthquake which threatens the safety of people and the...
Show moreThere are many calamities around the world, one of the most dangerous disasters is earthquake which threatens the safety of people and the structures. Almost every year, there are a lot of property losses and casualties caused by earthquakes. To mitigate the bad effect of the earthquake, the base isolation system was proposed by previous researchers. With the contribution of many researchers, several seismic isolations have been developed. Until now, many structures have installed seismic isolations to resist seismic energy and vibration. The seismic isolation system works well during the earthquake period, and it does help reduce the casualty and property loss induced by earthquakes. There are two main types of bearings used in the seismic isolation system. One is the elastomeric bearings and the other is the sliding bearings. The mechanics of the seismic isolation system preventing the influence of the earthquake and reducing the horizontal acceleration of the structure is to elongate the natural frequency of structure. As for the sliding bearings, the simplest way to increase the period is to reduce the friction coefficient of the two sliding elements. In conventional, two stainless steel plates are commonly used in the pure flat sliding bearing. This study tries to use bronze-graphite composite in the sliding bearing to decrease the friction coefficient.Consequently, the testing results suggest that the bronze-graphite composite has a lower friction coefficient, especially the graphite acting as a lubricant. The friction coefficient of the bronze-graphite plate is in the range of 0.12 to 0.23 under the load of 160 kg - 800kg. With a higher ratio of graphite to bronze at the sliding surface, the effect of reducing the friction coefficient more obviously. And the friction coefficient changes during the increasing loads period. It decreases at the beginning, and starts to increase at a certain load applied on it. Finally, it is reasonable to bronze-graphite composite in a low rise structure which has a relatively low weight. Because the load applied in the test is not high enough, the consequence may not work for high or heavy structure. Taken together, the use of new material with similar properties in the seismic isolation system can help improve the performance of resisting the earthquake. It should be accounted for further research in this field.
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Title: EVENT-BASED NONINTRUSIVE LOAD MONITORING
Creator: Yan, Lei
Date: 2021
Description: Non-Intrusive Load Monitoring (NILM) is an important application to monitor household appliance activities and provide related information to...
Show moreNon-Intrusive Load Monitoring (NILM) is an important application to monitor household appliance activities and provide related information to house owner or/and utility company via a single sensor installed at the electrical entry of the house. With this information, utilities can perform many tasks such as energy conservation, planning gen-eration more wisely, and demand response (DR) study. For house owners, they can un-derstand their bill more clearly and make better budget plan. For researchers, NILM sys-tem is a good foundation for energy management in buildings and can provide valuable power information for smart homes design. This dissertation aims to develop and demon-strate a complete and accurate event-based NILM system, which includes (1) an edge-cloud framework for event-based NILM, (2) an adaptive event detection method, (3) a two-stage event-based load disaggregation method; and (4) a high-resolution (50Hz) NILM dataset. Event detection is the first step in event-based NILM and it can provide deter-ministic transient information to identify appliances. However, existing methods with fixed parameters suffer from unpredictable and complicated changes in smart meter data such as long transition, high fluctuation and near-simultaneous events in both power and time domains. This dissertation presents an adaptive method to detect events based on home appliance load data with high sampling rate (>1Hz) by flexibly tuning the parame-ters according to the data being processed. The proposed method runs fast over the data stream and captures the transient process by multi-timescales searching as well. The mi-cro-timescale and macro-timescale window could deal with near-simultaneous events and long-transition events, respectively. Transient load signatures are extracted from detected events and stored in a sequential tree struct that can be used for NILM and load recon-struction, etc. Case studies on a 20Hz dataset, the LIFTED dataset of 50Hz, and the BLUED dataset of 60Hz demonstrate that the proposed method is able to work on data of different sampling rates and outperforms other methods in event detection. The ex-tracted load signatures could also improve the efficiency of NILM and help develop oth-er applications. This dissertation presents an online transient-based electrical appliance state track-ing method for NILM. The proposed Factorial Particle based Hidden Markov Model (FPHMM) method takes advantage of transient features in high-resolution data to infer states in the transient process and conducts steady state verification to rectify falsely identified appliances. The FPHMM method can overcome the common feature similarity problem in NILM by combining particle filter method and Markov Chain Monte Carlo sampling method, and by mining the intra-relationship of states inside a single appliance and the inter-relationship of states among multiple appliances. The FPHMM method is tested on the LIFTED dataset with appliance-level details and high sampling rates. Test-ing results demonstrate that the FPHMM method is effective in resolving the feature similarity issue. A modified mean shift algorithm with different levels of bandwidth is proposed as well to cluster the extracted features from event detection. Based on the clustered fea-tures, another solution is proposed to decode the states of appliance in two stages. The first stage uses Bayesian Inference Factorial HMM (BI-FHMM) solver to accelerate com-putational speed and improve accuracy by integrating the load signatures and statistical inference. The second stage then verifies and rectifies the results obtained from the first stage. Test results demonstrate that the proposed approach achieves good performance and can be applied to existing smart meters.
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Title: Algorithms for Discrete Data in Statistics and Operations Research
Creator: Schwartz, William K.
Date: 2021-11-19, 2021-12
Publisher: ProQuest, https://www.proquest.com/docview/2622985712
Description: Sponsorship: The Air Force Office of Scientific Research's grant FA9550-14-1-0141 supported Prof. Petrović's and my initial work on this project.

Title: IIT film, ca. 1975
Creator: Sharp, Charles Dee
Date: 1975
Description: Film (color and sound) of Illinois Institute of Technology campus and classroom scenes with shots of Chicago. Per Sharp, the film was made...
Show moreFilm (color and sound) of Illinois Institute of Technology campus and classroom scenes with shots of Chicago. Per Sharp, the film was made around 1975, most likely produced at the request of the President's Office. Credits read, "A Film by Charles Dee Sharp, Produced at ID." Sharp taught filmmaking at the Institute of Design from 1965 to 1980.
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Collection: Charles Dee Sharp film, ca. 1975

Title: IIT/V
Creator: Illinois Institute of Technology
Date: 1976-1981
Description: A promotional booklet for IIT/V (also known as IITV), one of the first televised course delivery services. IITV offered distance learning...
Show moreA promotional booklet for IIT/V (also known as IITV), one of the first televised course delivery services. IITV offered distance learning classes at the graduate and upper-division undergraduate levels to corporate and public audiences.
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Collection: IITV courses collection, 1976-1987

Title: IIT 1956-1957
Creator: Illinois Institute of Technology
Date: 1956-1957
Description: Black-and-white, silent film identified as "IIT 1956-1957" with images of Illinois Institute of Technology campus and buildings, classroom...
Show moreBlack-and-white, silent film identified as "IIT 1956-1957" with images of Illinois Institute of Technology campus and buildings, classroom scenes, and students working in laboratories. Extended sequences feature architecture and Institute of Design students with models of their work and students dining in the Commons Building. Original format is 16mm film. Exact date of filming is unknown, but some evidence indicates at least smoe of the film was shot in spring, 1957.
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Collection: IIT 1956-1957 film, 1956-1957

Title: EXPERIMENTAL AND STRUCTURAL STUDIES OF FDA APPROVED EXON SKIPPING TREATMENT DRUGS
Creator: Zhang, Jingwen
Date: 2021
Description: DMD is an X-chromosome related genetic disease caused by loss of dystrophin protein expression, and which impacts 1 in 5000 boys born in the...
Show moreDMD is an X-chromosome related genetic disease caused by loss of dystrophin protein expression, and which impacts 1 in 5000 boys born in the world. The usual cause of this at the genetic level is a frame shift due to internal deletions of one or more exons that results in a change of the reading frame. This results in loss of expression of the protein encoded by this gene, dystrophin, which in turn leads to the disease phenotype. Exon skipping is a therapy for DMD which restores dystrophin pre-mRNA reading frame to produce a modified dystrophin. This is done by antisense oligonucleotides, AONs, which disturb the process of exon splicing and exclude targeted exons near the patient’s defect which restore the correct reading frame in the pre-mRNA transcript. In 2016, the first AON was approved for clinical use targeting exon 51, called eteplirsen. This provided the first disease modifying therapy for DMD, but it was only relevant to ~6% of patients who had defects that were correctable by skipping this specific exon. In 2020 two more AONs targeting exon 53 were developed, viltolarsen and golodirsen, providing benefit to an additional 5% of patients, and in 2021 casimersen targeting exon 45 was approved.However, this raises an interesting issue, in that for some patients, with an exon 52 deletion, skipping exon 51 or skipping exon 53 could both restore the reading frame. Which approved exon skipping treatment is better and the differences between them are still unknown. This is the aim of this study: to help patients figure out which AON can have a consequence of less long-term health problems like cardiomyopathy and longer life and get more precise treatment. We selected three exon skipped edits – two that represent exon 53 skipping repair of an underlying Δe52 defect and one targeting exon 51 skipping repair of a Δe52 defect. We then used a panel of biophysical and biochemical including dynamic light scattering, circular dichroism Spectroscopy, thermal denaturation, and protease K challenge to investigate the biophysical characteristics of these different exon skipped edits. From our results we found that Δe51-52 has the more structure (i.e., is less perturbed), compared to e52-53, as assessed by CD or by proteinase K challenge, but it also has lower thermal stability, with a low Tm=48C transition that begins to unfold at the physiological relevant temperature of 37C. On the other hand, e52-53 has less helical structure, but what structure did form had unfolding transitions in the normal range for wild type STRs, Tm> 60C; but this edit also had more non-helical structure. So, the total experimental results of these three edits are very complex, which may be due to the fact that these edits span the normally unfolded H3 region.
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Title: Two Essays on Corporate Finance
Creator: Wang, Bo
Date: 2021
Description: This dissertation is comprised of two essays on finance. In the first chapter, I investigate whether and to what extent unionization would...
Show moreThis dissertation is comprised of two essays on finance. In the first chapter, I investigate whether and to what extent unionization would influence the compensation to the non-executive employees. In the second chapter, I explore how social capital would impact regional innovation performance by private firms.In the first chapter, I examine the effects of unionization on stock options granted to non-executive employees. Adopting a regression discontinuity design, I find that employees receive more stock options after the union election wins. The positive association is more pronounced when unions have more bargaining power and when free-riding problems are less severe. Further, I provide evidence that employees receive more stock options when CEOs are entrenched. Finally, I show that stock options provide risk-taking incentives to non-executive employees. This work provides a potential explanation to the union wage premium puzzle that unions utilize stock options to increase non-executive employees’ total compensation. In the second chapter, I investigate whether and to what extent social capital may affect regional innovation by private firms in the U.S. I document that regional social capital is positively associated with the quantity, quality, and novelty of county-level innovation by private firms. This effect is more prominent in regions with a lower supply of financial capital. My findings further suggest that social capital is complementary to investment in research and development. Using a Spatial Durbin Model, I report that regional social capital has significant spillover effects in boosting the innovation of neighboring counties.
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Title: RESIDENTIAL LOAD DATA COMPRESSION AND LOAD DISAGGREGATION
Creator: Xu, Runnan
Date: 2021
Description: Non-Intrusive Load Monitoring (NILM) for residential applications aims to dis-aggregate the total electricity consumption of a household into...
Show moreNon-Intrusive Load Monitoring (NILM) for residential applications aims to dis-aggregate the total electricity consumption of a household into the single appliance information. For the customer side, users can change their consumption habit and save more electricity. For the utility, generation scheduling will be more accurate, efficient, and secure. Furthermore, energy management system, demand response and fault diagnosis will benefit from the real time information provided by the NILM. This dissertation first proposes a data compressed method suitable for the NILM data. Then a real time disaggregation based on the Kalman filter is proposed to obtain the appliance state information. A model-free lossless data compression method for time series in smart grids (SGs), namely, Lossless Coding considering Precision (LCP) method is proposed. The LCP method encodes the current datapoint only using the immediate previous datapoint by differential coding, XOR coding, and variable length coding and transmits the encoded data once generated. It does not use the dynamics (e.g., many previous datapoints) or prior knowledge (e.g., mathematical models) of the time series. It considers the patterns, potential applications, and associated precision to preprocess the time series and especially suits high-resolution time series with long steady periods. The LCP method features low-latency and generalizability which enables real-time data communication for different time-critical tasks. Sub-metered load profiles in REDD dataset, high-resolution LIFTED dataset, AMPds dataset and PMU dataset are used to evaluate the performance of the LCP method. The results show that the LCP method demonstrates high compression ratio, low latency, and low complexity compared to state-of-the-art Resumable Data Com-pression (RDC) method, DEFLATE based on LZ77 & Huffman coding, and Lempel-Ziv-Markov Chain Algorithm (LZMA). An online method based on the transient features of individual appliances and system steady-state characteristics is proposed to estimate the appliances’ working states. It determines the number of states for each appliance via Density-based Spatial Clustering of Applications with Noise (DBSCAN) method and models the transition relationship among different states. The states of working appliances are identified from aggregated power signals by implementing the Kalman filtering method into the Factorial Hidden Markov Model (FHMM) and by the verification of system states which are the combination of working states of individual appliances. The proposed method is event based and the use of transient features extracted from event detection could achieve fast state inference and is suitable for online load disaggregation. The proposed method is tested on high-resolution dataset such as LIFTED and outperforms other related methods, including Segment-wise Integer Quadratic Constraint Programming (SIQCP), Combinatorial Optimization (CO), and the exact FHMM (FHMM_EXACT), in terms of accuracy, f1 score, and computational time.
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Title: Testing a pilot intervention aiming to increase transgender allyship among future healthcare providers
Creator: Yoder, Wren
Date: 2021
Description: Transgender individuals often experience poor health outcomes related to a lack of provider knowledge and comfort around transgender issues. ...
Show moreTransgender individuals often experience poor health outcomes related to a lack of provider knowledge and comfort around transgender issues. Ally identity development and cultural humility theories have been used to develop interventions shown to improve attitudes, knowledge, and skills related to being an ally to the transgender community. Additionally, healthcare providers have reported a desire for online tools related to transgender healthcare, and online interventions can be more cost effective than traditional in-person trainings. The current study developed an hour-long online intervention composed of six activities aiming to increase attitudes, knowledge, skills, and identification as an ally to the transgender community. Tests were conducted to assess whether these domains increased significantly from baseline to post in the intervention condition compared to the control condition and whether the increase was maintained at 2-week follow up. The sample included cisgender (i.e., male or female) students studying a subject related to healthcare recruited online through Prolific (N = 78). Results indicated that knowledge and skills increased significantly from baseline to post in the intervention condition compared to the control condition, and increases were maintained at 2-week follow up. However, this was not the case for attitudes and identity. These findings largely replicate existing research on knowledge about transgender individuals and provide new insights into skills, attitudes, and identity related to transgender allyship. Findings can inform future research on transgender allyship intervention design and allyship theory as well as support improvements in clinical practice and policy related to transgender healthcare services.
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Title: HIGH-THROUGHPUT FIRST-PRINCIPLES STUDY ON HIGH-ENTROPY ALLOYS
Creator: Zhang, Jie
Date: 2021
Description: This research thesis discusses the current ecosystem surrounding a new type of alloy: high entropy alloys (HEA) or multi-element crystalline...
Show moreThis research thesis discusses the current ecosystem surrounding a new type of alloy: high entropy alloys (HEA) or multi-element crystalline materials and lays out the high-throughput first-principles calculation as a valuable approach to study these materials. The density function theory (DFT) from computational material science prospect was implemented to investigate the HEAs. Using EMTO-CPA algorithm, high-throughput DFT calculations were conducted. A total of 1958 HEA systems including equimolar and non-equimolar systems were studied with respect to the varies properties, including lattice parameters, bulk moduli, elastic constants, and elastic anisotropy. The first-principles HEA dataset was employed as the training set for the DeepSets a machine learning model. DeepSets, in combination with EMTO-CPA high-throughput calculation, successfully predicted the mechanical properties of specific HEA composition. This paves a promising new path of designing, investigating, and validating the HEA system compared to the time-consuming conventional HEA design method. The doping effect of Vanadium (V) and Titanium (Ti) to NbMoTaW HEA, as well as V or Ti as the fifth element with different molar fraction to the NbMoTaW HEA system, were studied. The phase stability of the new systems was discussed and concluded that all proposed systems tend to form single-phase solid solution. Though the addiction of V only slightly enhances the system’s ductility, the addition of Ti not only enhances the quinary system NbMoTaWTiX (X =0.25, 0.5,0.75, 1.0) ductility, but enables the system to be closer to fully isotropic.
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