University of Hartford
  • West Hartford, CT, United States
Recent publications
The Markov numbers are the positive integers that appear in the solutions of the equation x2+y2+z2=3xyz. These numbers are a classical subject in number theory and have important ramifications in hyperbolic geometry, algebraic geometry and combinatorics. It is known that the Markov numbers can be labeled by the lattice points (q,p) in the first quadrant and below the diagonal whose coordinates are coprime. In this paper, we consider the following question. Given two lattice points, can we say which of the associated Markov numbers is larger? A complete answer to this question would solve the uniqueness conjecture formulated by Frobenius in 1913. We give a partial answer in terms of the slope of the line segment that connects the two lattice points. We prove that the Markov number with the greater x-coordinate is larger than the other if the slope is at least −87 and that it is smaller than the other if the slope is at most −54. As a special case, namely when the slope is equal to 0 or 1, we obtain a proof of two conjectures from Aigner's book “Markov's theorem and 100 years of the uniqueness conjecture”.
Street vendors are often targeted for removal from city streets and sidewalks in the name of beautification, sanitation or (re)development. These removals are commonly described as conflicts over the use of urban public space. However, focusing on conflicts over the use of public space provides an incomplete picture. In addition to contention over the use of space, street vending also involves debates over the users of public space. Through the lens of street vending in Mumbai, this research shows that conflicts over vending are often tied to who is vending, reflecting a local political atmosphere concerned with preventing ‘outsiders’ from working (and living) in the city. However, vendors are not helpless, and try to capitalise on informal institutions, specifically hafta, and intermediaries, to make claims regarding their urban belonging status. While informal institutions may mediate questions of urban citizenship and belonging, they provide only limited opportunities, leaving vendors often with a de facto rather than de jure vending, and urban belonging, status.
Most recommendation systems utilize personal data to device personalized recommendations for users. Even though it seems favorable, security risks like data breaches are inevitable. This research proposes a novel reinforcement learning ‘approach’ to recommend users without collecting identifiable data. With only user activity on a session, our proposed method can model and track user behavior and formulate a recommendation system. We conclude that our algorithms demonstrate positive results in capturing user behavior without collecting private data of any kind from the user. The research is two folds. On one hand, we experiment using traditional reinforcement learning techniques (MDP, Q-learning), and on the other hand, we use deep reinforcement learning algorithms (DQN, DDQN, and D3QN) on a movie recommendation scenario. Interestingly, we observe that MDP and D3QN works comparatively better on movie recommendations.
Autologous blood-patch pleurodesis (ABPP) is a common technique used to manage patients with persistent pleural air leaks caused by pneumothorax. Other treatment options for persistent air leak (PAL) include chemical pleurodesis or placement of endobronchial valves, though severity of illness, risk of complications such as infection, or patient comorbidities may impact treatment decisions. The use of ABPP in patients with HIV and AIDS has not been reported in the literature. We present a case of a 32-year-old man with a history of AIDS (noncompliant with medications) and schizophrenia who presented with acute hypoxemic respiratory failure complicated by pneumothorax and PAL. He safely underwent ABPP without complications and eventually had resolution of PAL.
Introduction: Plastic waste in freshwater ecosystems is increasingly recognized as an economic, ecological, and environmental problem with potential health consequences. This article shares the results of a project to train local stakeholders to collect debris in their communities using scientific methods, then share the results with policymakers. Methods: Workshops were held in Uganda, Indonesia, and the United States in the spring of 2022. This article presents baseline data from collections on the Aturukuku River in Uganda, the Ayung River in Indonesia, and the Connecticut River in the United States as well as survey results measuring participant attitudes, behaviors, and their perceptions around plastic waste and policy. Surveying participants sheds light on the nuances of perception of the problem and policies to combat pollution at each locale. Results: We found deposited debris at each riverbank location: Aturukuku River, 0.45 pieces/m2 of which 89.4% was plastic; Ayung River, 7.62 pieces/m2 of which 91.1% was plastic, and the Connecticut River 0.29 pieces/m2 of which 63% was plastic. Environmental attitudes and behaviors were comparable among countries. Participants in all three countries expect plastic will be the most frequently found material. Discussion: In all cases, perceptions about the kind of debris in their communities corresponds well with collection results. Perceptions around policy solutions included a wide range of solutions, though countries differed in whether solutions addressed the source or the symptoms of the problem; solutions focused more on waste management in Uganda and Indonesia.
In this paper we develop a novel theory to explain why green stocks should underperform relative to conventional stocks. We assume that investors derive utility from investing in green stocks – what we call “warm-glow” investment. We derive the theoretical implications of these preferences in a model that is an extension of the Consumption-based Capital Asset Pricing Model. We estimate the model using the Generalized Method of Moments. Our estimates of the strength of the preference for warm glow before the financial crisis are statistically significant but economically insignificant; our estimates of it after the crisis are significant both statistically and economically.
Selfish mining is a typical malicious attack targeting the blockchain-based bitcoin system, an emerging crypto asset. Because of the non-incentive compatibility of the bitcoin mining protocol, the attackers are able to collect unfair mining rewards by intentionally withholding blocks. The existing works on selfish mining mostly focused on cryptography design, and malicious behavior detection based on different approaches, such as machine learning or timestamp. Most defense strategies show their effectiveness in the perspective of reward reduced. No work has been performed to design a defense strategy that aims to improve bitcoin dependability and provide a framework for quantitively evaluating the improvement. In this paper, we contribute by proposing two network-wide defensive strategies: the dynamic difficulty adjustment algorithm (DDAA) and the acceptance limitation policy (ALP). The DDAA increases the mining difficulty dynamically once a selfish mining behavior is detected, while the ALP incorporates a limitation to the acceptance rate when multiple blocks are broadcast at the same time. Both strategies are designed to disincentivize dishonest selfish miners and increase the system’s resilience to the selfish mining attack. A continuous-time Markov chain model is used to quantify the improvement in bitcoin dependability made by the proposed defense strategies. Statistical analysis is applied to evaluate the feasibility of the proposed strategies. The proposed DDAA and ALP methods are also compared to an existing timestamp-based defense strategy, revealing that the DDAA is the most effective in improving bitcoin’s dependability.
The yield strength, ultimate strength, and elongation/ductility properties of a series of palladium–copper alloys were characterized as a function of the temperature at which each alloy underwent absorption and desorption of hydrogen. The alloys studied ranged in copper content from 5 weight percent copper to 25 wt.% copper. Compared to alloy specimens that had been well-annealed in a vacuum and never exposed to hydrogen, alloys with copper content up to 15 wt.% showed strengthening and loss of ductility due to hydrogen exposure. In these alloys, it was found that the degree of strengthening and loss of ductility was dependent on the hydrogen exposure temperature, though this dependence decreased as the copper content of the alloy increased. For alloys with copper contents greater than 15 wt.%, hydrogen exposure had no discernible effect on the strength and ductility properties compared to the vacuum-annealed alloys, over the entire temperature range studied.
Objectives We investigated whether trait mindfulness from both partners in a social interaction was associated with two critical relational processes—self-disclosure and responsiveness—during conversations between new acquaintances.Method Participants (n = 140, 70 dyads) were randomly assigned to engage in a guided conversation with a high or low level of self-disclosure. The conversation was video-recorded and videos were coded by trained research assistants for the relational behaviors of self-disclosure (how much personal information was shared about oneself) and responsiveness (how much understanding, caring, and validation was demonstrated towards one’s partner). Using a longitudinal actor-partner interdependence model, we analyzed the relationship between the five facets of mindfulness (Observing, Nonreactivity, Acting with Awareness, Describing, and Nonjudging) and self-disclosure and responsiveness. We also examined whether people’s behaviors were associated with their own mindfulness and the mindfulness of their partners.ResultsTwo key findings emerged. First, people who were higher on the mindfulness facet of Observing were more likely to self-disclose and to be responsive. Second, people were also more likely to self-disclose and be responsive when they interacted with partners who themselves were higher on the mindfulness facet of Observing.Conclusions These findings suggest that mindfulness plays a role in initial social interaction. Our results indicate that one’s own trait mindfulness is linked with the relational processes of self-disclosure and responsiveness in conversations with new acquaintances and that even the mindfulness of people’s interaction partners who they have just met may shape their own social behaviors.
The COVID-19 pandemic has affected millions of people worldwide with severe health, economic, social, and political implications. Healthcare Policy Makers (HPM) and medical experts are at the core of responding to this continuously evolving pandemic situation and are working hard to restrain the spread and severity of this relatively unknown virus. Biomedical researchers are continually discovering new information about this virus and communicating the findings through scientific articles. As such, it is crucial for HPM and funding agencies to monitor the COVID-19 research trend globally on a regular basis. However, given the influx of biomedical research articles, monitoring COVID-19 research trends has become more challenging than ever, especially when HPMs want on-demand guided search techniques with a set of topics of interest in their minds. Unfortunately, existing topic trend modeling techniques are unable to serve this purpose as 1) Traditional topic models are unsupervised, and 2) HPMs in different regions may have different topics of interest that they want to track. To address this problem, we introduce a novel computational task in this paper called Ad-Hoc Topic Tracking , which is essentially a combination of zero-shot topic categorization and the Spatio-temporal analysis task. We then propose multiple zero-shot classification methods to solve this task by extending upon the state-of-the-art language understanding techniques. Next, we picked the best-performing method based on its accuracy on a separate validation data set and then applied it to a corpus of recent biomedical research articles to track Covid-19 research endeavors across the globe using a Spatio-Temporal analysis. A demo website has also been developed for HPMs to create custom Spatio-Temporal visualizations of COVID-19 research trends. The research outcomes demonstrate that the proposed zero-shot classification methods can potentially facilitate further research on this important subject matter, and at the same time, the Spatio-temporal visualization tool will greatly assist HPMs and funding agencies in making well-informed policy decisions for advancing scientific research efforts.
This study highlights the impact of digital financial services as enhancing the capacity of development goals as well as social sustainability. The selected emerging markets are Ghanaian financial service providers (FSP)s and microenterprise customers (CME)s, where we examine how “Ubuntu”, an African philosophy of humanism, legitimizes spaces for a more democratic, egalitarian, and ethical engagement of human beings. This study adopts a grounded theory methodology for investigation of the phenomena with a sample size of 70 relationship managers. The findings further existing sustainability literature pertaining to social sustainability and consumer wellbeing. We contribute to theory by presenting a psychological perspective which be leveraged for digital financial services branding to expand usage within communal systems. This leverage of Ubuntu becomes especially relevant when there is the need to compensate for deficits in weak business infrastructures in low-income but expanding markets. Our study highlights digital financial services can be used to improve the emotional and psychological consumer wellbeing and to strengthen business relationships, meeting joint goals of market share expansion, brand image enhancement and profitability. This perspective also contributes to social sustainability on a global scale since the Western world depends on quality products from emerging markets.
Drug-resistant breast cancers such as Triple negative breast cancer (TNBC) do not respond successfully to chemotherapy treatments because they lack the expression of receptor targets. Drug-resistant anti-cancer treatments require innovative approaches to target these cells without relying on the receptors. Intracellular self-assembly of small molecules induced by enzymes is a nanotechnology approach for inhibiting cancer cell growth. In this approach, enzymes will induce the self-assembly of small molecules to nanofibers, which leads to cell death. Here, we investigate the self-assembly of a modified small peptide induced by two different phosphatases: alkaline phosphatase (ALP) and eye absent tyrosine phosphatase (EYA). ALPs are expressed in many adult human tissues and are critical for many cellular functions. EYAs are embryonic enzymes that are over-expressed in drug-resistant breast cancers. We synthesized a small diphenylalanine-based peptide with a tyrosine phosphate end group as the substrate of phosphatase enzymes. Peptides were synthesized with solid phase techniques and were characterized by HPLC and MALDI-TOF. To characterize the self-assembly of peptides exposed to enzymes, different techniques were used such as scattering light intensity, microscopes, and phosphate detection kit. We then determined the toxicity effect of the peptide against normal breast cancer cells, MCF-7, and drug-resistant breast cancer cells, MDA-MB-231. The results showed that the EYA enzyme is able to initiate self-assembly at lower peptide concentration with higher self-assembling intensity compared to ALP. A significant decrease in the TNBC cell number was observed even with a low peptide concentration of 60 μM. These results collectively support the exploration of enzyme self-assembly to treat TNBC.
Background Previous scoring systems have been proposed to predict COVID19 outcomes, however none have been universally adopted. Two scoring systems of interest are Monoclonal Antibody Screening Score (MASS) and Oral Antiviral and Monoclonal Antibody Screening Score (OMASS). MASS prioritized patients for outpatient monoclonal antibody treatment based on risk of hospitalization, and OMASS was a modified version of MASS used to prioritize outpatient oral antivirals. We created a modified scoring system (UCH2021) incorporating vaccination status. These scores (table 1) have not been used to predict in-hospital clinical outcomes. We investigate these systems’ abilities to predict mortality and oxygen requirements in hospitalized COVID19 patients. They do not require blood tests and allow for more rapid triage. Table 1:MASS, OMASS, UCH2021 Scoring Criteria Methods A retrospective chart review was performed on 133 patients in two tertiary care centers between March and Sept. 2020 with RT-PCR confirmed SARS CoV2. Baseline risk factors were collected and MASS, OMASS, and UCH2021 were calculated. Primary outcomes included mortality, need for intubation, and need for supplemental oxygen >6L during hospitalization. Secondary analysis assessed if any individual risk factors were associated with those outcomes. These systems were evaluated via area under the curve calculations. Two groups based on an outcome were compared using two-sample t-tests for continuous variables and Fisher’s exact tests for categorical variables. Results All three systems demonstrated some discriminative power for mortality (table 2), but not for oxygen and intubation requirements. There was statistically significant difference in age between survivors and deceased (table 3), and BMI for oxygen requirements (table 4). Other risk factors were not predictive of mortality or oxygen requirement. Table 2:MASS, OMASS, UCH2021 Scores and Mortality in Hospitalized COVID19 PatientsTable 3:Age and Mortality in Hospitalized COVID19 PatientsTable 4:BMI and Oxygen Requirements in Hospitalized COVID19 Patients Conclusion The MASS, OMASS, and UCH2021 score all had predictive power in determining in-hospital mortality, with moderate accuracy, however none were predictive of oxygen requirements. Age and BMI were also good predictors of mortality and oxygen requirements respectively. This study was completed prior to vaccine distribution in the US. Further studies would be helpful to assess if UCH2021 score has greater discriminative power in samples with vaccinated patients. Disclosures All Authors: No reported disclosures.
Eating disorder recovery is differently understood in multi-disciplinary healthcare contexts. In this study, we sought to better understand how healthcare providers (HCPs) describe recovery and communicating about recovery. We conducted an anonymous, online, qualitative survey with 41 eating disorder HCPs. In their responses, HCPs noted that communicating about recovery was core to their practice of establishing collaboration and communication with clients, as well as enabling “realistic hope” in clinical encounters. Recovery was described as related to the concept of attaining “normalcy” in life. We identified several tensions across HCP accounts, including what “normalcy” might look like, differences in the role of diagnostic and other contextual factors in determining recovery and different perspectives on how symptom remission figures in recovery. Our findings suggest that attending to differences in communication about recovery is an important direction for eating disorders research and treatment.
Background It is typically assumed in the social scientific study of religion that individuals attend one congregation or none. As such, there is scarce research on individuals who attend more than one congregation yet doing so may affect congregational participation.PurposeThis study theorizes factors affecting whether someone attends multiple congregations and how this might influence congregational volunteering and giving in the context of megachurches. It hypothesizes that parents, those who are single, those of lower socioeconomic status, those who are racially and ethnically minoritized, and those who are not socially embedded in a congregation will be more likely to attend a megachurch and other congregations. It also theorizes competing hypotheses regarding the association between attending multiple congregations and congregational volunteering and giving.Methods This study draws on survey data from 12 representative megachurches to test the proposed hypotheses using logistic and ordinal logistic regression models.ResultsThose who are single, those of lower socioeconomic status, those who are racially and ethnically minoritized, and those who are not socially embedded in the megachurch are more likely to attend multiple congregations simultaneously. Attending multiple congregations is negatively associated with congregational volunteering and giving.Conclusions and ImplicationsThe results demonstrate the need to reconceptualize congregational attendance to recognize that individuals may attend more than one congregation. Accordingly, future surveys should allow respondents to identify attending multiple congregations. The results also highlight how congregations may be negatively impacted by non-exclusive attendees who are less likely to volunteer and give money.
In this introduction to the special issue, we outline primary NASP Standards revisions which afford an opportunity for school psychologists (SP) to take on a more prominent role in school-based consultation grounded in social justice and equity. We point to advocacy in the NASP (2020) Standards for a lower 1:500 SP to student ratio, changes made to the description of particular NASP domains related to equity and schoolwide safety and practices (Domains 8 and 6) and more specific graduate education requirements for consultation training in practica as key changes that could facilitate a broader role of school psychologists in school-based consultation. The five articles in the special series are summarized with a focus on how the authors leverage the new NASP standards to advance training and the delivery of consultation practice to enhance equity and social justice in their respective settings.
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1,665 members
Ivana Milanovic
  • Department of Mechanical Engineering
Colleen X Munoz
  • Department of Health Sciences
Mary E Gannotti
  • Department of Rehabilitation Sciences
Linda M Yamamoto
  • Department of Health Sciences and Nursing
Saeid Moslehpour
  • Department of Electrical and Computer Engineering
200 Bloomfield Avenue, 06117, West Hartford, CT, United States
Head of institution
Walter Harrison