University of Massachusetts Lowell
  • Lowell, MA, United States
Recent publications
This paper leverages each pixel of a picture acquired from a video camera, in which structural dynamic information is contained, in order to decompose spatiotemporal information from such a non-contact virtual sensor array in the same way as traditional accelerometers to extract structural modal frequencies. Attention-based deep neural network architecture is proposed in this work to better visualize the dynamic properties of structures in the existence of noise with a high resolution. The work combines CNNs and Recurrent Neural Networks (RNNs) to predict modal frequencies of structures from a series of consecutive images. High discriminative features of video frames are firstly extracted using the CNN, and then Conv-Long Short-Term Memory (ConvLSTM) is applied to further process the extracted features to capture the temporal dynamics in videos. The attention mechanisms are embedded in the network to ensure the model learns to focus selectively on those frames containing system dynamics. In particular, the proposed computer vision-based deep learning model takes the video of a vibrating structure as the input and successfully estimates the modal frequencies. Transfer learning is applied to cohere the knowledge learned from publicly available datasets to a much more sophisticated structure and estimate the resonant frequencies. The proposed algorithm optimizes the filter design for video processing in a fully automated way without any human intervention and can generalize and transfer that learned information to more complex structures. The model is trained using publicly available generic baseline data (Dataset A) consisting of several simple beam structures with different material properties and sizes and transferred the learned knowledge to unseen data (Dataset B) consisting of an independent turbine blade. It is concluded that the newly proposed method is more autonomous, accurate, and capable of generalizing the model to a new independent dataset using a transfer learning strategy, and the most advantage of the proposed approach is that the trained deep learning architecture has the capability of estimating the resonant frequencies for independent structures and extending the resonant frequency estimations to higher modes.
Heating and cooling are major resources of Demand Response (DR) to enhance the flexibility and reliability of power grids. In order to maximize their potential, it is necessary to reliably keep track of their operating states in real-time operation. This paper presents a comprehensive state estimation framework for power systems with building thermostats, with a tractable thermodynamic building model and integration of multi-source information from weather, power grid, building systems. Based on the thermodynamic model and state of the buildings, the building temperature trajectories in the next few hours can be accurately predicted, such that the DR potential of the building can be precisely estimated. To jointly estimate the state variables of power grids and state variables in building thermostats with different time scales of dynamics, a holistic estimation framework is developed based on the partial equivalence between the Weighted Least Squares (WLS) estimation problem and the correction stage of the Iterative Extended-Kalman Filter (IEKF). Simulation results show that the proposed framework can accurately track the thermo-electrical states of the system and estimate the DR potential in the presence of measurement noise and bad data.
Reduced-La0.4Sr0.6Co0.2Fe0.7Nb0.1O3-δ (LSCFN) with anchored nanoscale Co-Fe alloy is evaluated as the protective catalyst layer for ethanol-fueled solid oxide fuel cells (SOFCs) in this study. The coking resistance and overall performance of both cells with and without the catalyst layer are systematically studied in ethanol and H2 fuels. Both cells with and without the catalyst layer fueled in H2 fuel exhibit equivalent electrochemical performance, and the peak power density is 1065 and 1098 mW·cm⁻² at 800 °C, respectively. When compared with the conventional cell in ethanol fuel, the cell cracking caused by thermal–mechanical stress can be avoided in the new cell design with an integrated catalyst layer. Also, it exhibits a considerable peak power density of 469 mW·cm⁻² and demonstrates good coking resistance, and is stable during the 76 h test in ethanol at 800 °C. This study shows that the addition of the LSCFN catalyst layer can protect Ni-YSZ from the uneven distributed thermal–mechanical stress and severe coking in ethanol fuel.
Medication treatment for opioid use disorder (MOUD) is an effective evidence-based therapy for decreasing opioid-related adverse outcomes. Effective strategies for retaining persons on MOUD, an essential step to improving outcomes, are needed as roughly half of all persons initiating MOUD discontinue within a year. Data science may be valuable and promising for improving MOUD retention by using "big data" (e.g., electronic health record data, claims data mobile/sensor data, social media data) and specific machine learning techniques (e.g., predictive modeling, natural language processing, reinforcement learning) to individualize patient care. Maximizing the utility of data science to improve MOUD retention requires a three-pronged approach: (1) increasing funding for data science research for OUD, (2) integrating data from multiple sources including treatment for OUD and general medical care as well as data not specific to medical care (e.g., mobile, sensor, and social media data), and (3) applying multiple data science approaches with integrated big data to provide insights and optimize advances in the OUD and overall addiction fields.
Very low frequency (VLF) waves (about 3–30 kHz) in the Earth’s magnetosphere interact strongly with energetic electrons and are a key element in controlling dynamics of the Van Allen radiation belts. Bistatic very low frequency (VLF) transmission experiments have recently been conducted in the magnetosphere using the high-power VLF transmitter on the Air Force Research Laboratory’s Demonstration and Science Experiments (DSX) spacecraft and an electric field receiver onboard the Japan Aerospace Exploration Agency’s Arase (ERG) spacecraft. On 4 September 2019, the spacecraft came within 410 km of each other and were in geomagnetic alignment. During this time, VLF signals were successfully transmitted from DSX to Arase, marking the first successful reception of a space-to-space VLF signal. Arase measurements were consistent with field-aligned propagation as expected from linear cold plasma theory. Details of the transmission event and comparison to VLF propagation model predictions are presented. The capability to directly inject VLF waves into near-Earth space provides a new way to study the dynamics of the radiation belts, ushering in a new era of space experimentation. Graphical Abstract
This work presents a new class of micromachined electrostatic actuators capable of producing output force and displacement unprecedented for MEMS electrostatic actuators. The actuators feature submicron high aspect ratio transduction gaps lined up in two-dimensional arrays. Such an arrangement of microscale actuator cells allows the addition of force and displacements of a large number of cells (up to 7600 in one demonstrated array), leading to displacements ranging in the hundreds of microns and several gram forces of axial force. For 50 µm thick actuators with horizontal dimensions in the 1–4 millimeter range, an out-of-plane displacement of up to 678 µm at 46 V, a bending moment of up to 2.0 µNm, i.e., 0.08 N (~8 gram-force) of axial force over a 50 µm by 2 mm cross-sectional area of the actuator (800 kPa of electrostatically generated stress), and an energy density (mechanical work output per stroke per volume) up to 1.42 mJ/cm ³ was demonstrated for the actuators.
Coffee cultivation is a significant cause of deforestation, water shortages, and loss of habitat for migratory bird species in Central America. Coffee, however, is also one of the few viable industries providing employment to the region. Café Solar® embodies the vision of the founders to address a complex set of issues haunting the coffee industry in Honduras. Drawing from the experience and expertise of ornithologists, engineers, academics, coffee farmers, women activists and an array of partnerships, the nonprofit Mesoamerican Development Institute (MDI) developed innovative sustainable practices for coffee cultivation and processing. Further, in collaboration with the Fair-Trade cooperative, Cooperativa Mixta Subirana Yoro Limitada (COMISUYL), MDI translated the vision into strategy through its for-profit affiliate, MDI Honduras. The case includes specific areas in managing a sustainable enterprise, including creating a sustainable coffee value chain, and the application of budgeting and cash flows in supporting financial viability. Crucial to success was the creation of a brand that attracted a network of global customers desirous of Fair Trade and sustainable coffee. Hence, the case highlights opportunities, problems, and constraints to sustainability in the coffee industry in alignment with United Nations Sustainable Development Goals (UN SDGs). The case was tested in three class sessions (with 45 MBA/MS Accounting students) and was found to meet the pedagogic goals set for the case.
The defect ∼0.8 eV below the conduction band edge of β-Ga 2 O 3 wide bandgap semiconductor is investigated using the matched Arrhenius-equation projection technique that offers substantial improvement over the conventional deep level transient spectroscopy technique. An experimental technique is developed to extract activation energy E a and attempt-to-escape frequency ν 0 of defects bypassing both the rate-window treatment and the Arrhenius plot. Only raw capacitance transients in the time domain are needed with this technique. The capacitance transients are projected between the temperature and time domains as well as to E a and ν 0 domains. Extraction of E a and ν 0 is accomplished by matching the projected and experimental capacitance transients to each other.
Inmate misconduct is a focal concern among those who live and work in prisons, and is committed primarily by a few offenders with discernable backgrounds. The current study examines the most prolific rule violators (the top 1 and 10%) among a large sample of inmates housed across Ohio correctional facilities. We focus on the characteristics that predict membership into these categories and whether differences in their rates of occurrence exist between males and females. Findings show more similarities than differences between groups. Implication for theory and practice are discussed, as well as suggestions for future research.
Background: There is a lack of consensus among studies on the association between proton pump inhibitor (PPI) use and cognitive impairment. This association is not well studied among minority populations including among Puerto Ricans. Therefore, we sought to examine this association among Boston-area Puerto Ricans. Methods: The Boston Puerto Rican Health Study (BPRHS) is an ongoing longitudinal cohort that enrolled 1499 Boston-area Puerto Rican adults, aged 45-75 y at baseline. 1290 baseline participants had complete outcome and exposure data. Covariate-adjusted linear regression and linear mixed effects models were used to examine the association between PPI use, and global cognition, executive function, and memory cross-sectionally and longitudinally over ~12.7 y of follow-up. Further, we examined cross-sectional association between long-term PPI use (continuous use of ~6.2 y) and global cognition, executive function, and memory. Results: Among 1290 participants at baseline, 313 (24.3%) self-reported PPI use. Baseline PPI use was not associated with baseline global cognition, executive function, or memory. Baseline PPI use also did not alter trajectory of global cognition, executive function, or memory over ~12.7 y of follow-up. Long-term PPI use was not associated with global cognition, executive function, or memory over ~12.7 y of follow-up. Conclusions: In this study of Boston-area Puerto Ricans, we did not observe an association between PPI use and global cognition, executive function, or memory either cross-sectionally or over 12.7 y of follow-up.
Ammonia synthesis at ambient conditions employing intermittent green sources of energy and feedstocks is globally sought to replace the Haber-Bosch (H-B) process operating at high temperature and pressure. We report herein for the first time an effective and sustainable ammonia synthesis pathway from seawater and N2 over a spherical SiO2 and M/SiO2 (M: Ag, Cu, and Co) catalysts driven by non-thermal plasma (NTP). Experimental results indicate that the presence of a catalyst is required for ammonia production from seawater and N2. The Co/SiO2 catalyst delivered the highest ammonia synthesis rate (rate NH3) of 3.7 mmol.gcat-1.h-1 and energy yield of 3.2 g-NH3.kWh-1 at a relatively low input power of 2 W. The extraction of H atom from H2O (seawater) molecules plays an important role in the ammonia synthesis from seawater. This work unfolds a novel platform for the subsequent optimization of sustainable ammonia production from endless resources such as seawater and N2 through catalytic non-thermal plasma potentially powered by renewable sources.
We conducted a Monte Carlo study to examine the performance of level-specific χ2 test statistics and fit regarding their capacity to determine model fit at specific levels in multilevel confirmatory factor analysis with dichotomous indicators. Five design factors—numbers of groups (NG), group size (GS), intra-class correlation (ICC), thresholds of dichotomous indicators (THR), and factor loadings (FL)—were considered in this study. According to our simulation results, we recommend that practitioners should be aware that the performance of between-level-specific (b-l-s) χ2 and fit indices was mainly influenced by ICC and FL, followed by NG. At the same time, THR could slightly weigh in the performance of b-l-s fit indices in some conditions. Both b-l-s χ2 and fit indices were more promising indicators to correctly indicate model fit when ICC or FL increased. A small to medium NG (50–100) might be sufficient for b-l-s χ2 and fit indices only if both ICC and factor loadings were high, while in remaining conditions, an NG of 200 was needed. Moreover, practitioners could use within-level-specific (w-l-s) χ2 and fit indices (except for RMSEAW) along with traditional cut-off values to evaluate within-level models comprising dichotomous indicators. W-l-s χ2 and fit indices were more promising to determine model fit when FL increased. THR had a slight impact and could weigh in the performance of \({\chi}_W^2\), RMSEAW, CFIW, and TLIW. Unfortunately, RMSEAW was heavily affected by FL and THR and could determine model fit only when FL was high and THR was symmetric.
Rice cadmium (Cd) contamination is one of the critical agricultural issues. Breeding of low-Cd-accumulating cultivar is an effective approach to reduce Cd bioaccumulation in rice. To investigate the molecular mechanism underlying Cd transport in rice, the functions of nodes in Cd transport are explored. The results show that different nodes have different functions of Cd transport in the rice plant and the physiological structure of the first node under panicle (N1) determine the Cd accumulation in the brown rice. The upper nodes can redistribute the Cd transport in aboveground tissues. The expressions of Cd-efflux transporter genes (OsLCT1 and OsHMA2) located on the plasma-membrane are the main factors affecting the Cd transport form node to brown rice, which are more depended on the node functions but not the node Cd concentrations. Lower expressions of OsLCT1 and OsHMA2 in N1 result in lower Cd transport from node to brown rice. The size of vascular-bundle (VB) areas in the junctional node with the flag leaf can determine the expression of OsHMA2 and the expression of OsLCT1 positively correlated with the Cd transport ability of first node (N1). The expressions of OsVIT2 and OsABCC1 cannot allow Cd to be immobilized into the vacuoles in node. The VB structure and Cd transporter gene expression level of N1 proved that the Cd concentration of N1 can be used as an important indicator for screening low-Cd-accumulating cultivars. The major implication is that selecting or breeding cultivars with lower Cd accumulations in N1 could be an effective strategy to reduce Cd accumulation in rice grains.
The aim of this case study was to explore the abilities and limitations of trade unions in their response to undeclared work, which has received scant attention in research on working conditions and industrial relations. The authors use power resource theory to examine the outcome of a Swedish government initiative aimed to boost the ability of the social partners to tackle undeclared work. The findings confirm previous literature suggesting cross-sectoral differences in the extent and nature of undeclared work and an association between low levels of power resources and high risk of undeclared work. The authors recommend that future initiatives take account of cross-sectoral differences in the nature and extent of undeclared work and available power resources. Future research should consider how different actors can contribute to the ability of the social partners in different sectors to engage in the battle against undeclared work.
As an epigraph to chapter 2 of Playing in the Dark: Whiteness and the Literary Imagination, Toni Morrison uses a brief quote from a poem by Robert Penn Warren titled: “Penological Study: Southern Exposure.” The excerpted quote reads: “. . . shadows / Bigger than people and blacker than niggers.”¹ I’ve often wondered about Morrison’s use of this quote (colleagues and students have asked me about it as well). Given the poem’s relative obscurity, how did Morrison come across it in the first place? And what were her possible intentions in using it? On the one hand, it fits nicely with the title of the chapter, “Romancing the Shadow,” but given the subject of her book, it also hangs like an accusation, or at least it lets Warren’s reputation hang by these few words. Perhaps the incorporation of the epigraph is a tacit indictment of Warren, both for his reputation from his early career as a pro-segregationist Agrarian and for his seemingly casual, gratuitous use of racist rhetoric in this poem, for Morrison never mentions Warren elsewhere in her book, though his canon of poetry, fiction, and social criticism would surely have provided rich fodder for her argument in Playing in the Dark.
The United States Department of Defense has, for at least 20 years, held the stated intention to enhance active military personnel (“warfighters”). This intention has become more acute in the face of dropping recruitment, an aging fighting force, and emerging strategic challenges. However, developing and testing enhancements is clouded by the ethically contested status of enhancements, the long history of abuse by military medical researchers, and new legislation in the guise of “health security” that has enabled the Department of Defense to apply medical interventions without appropriate oversight. This paper aims to reconcile existing legal and regulatory frameworks on military biomedical research with ethical concerns about military enhancements. In what follows, we first outline one justification for military enhancements. The authors then briefly address existing definitional issues over what constitutes enhancement before addressing existing research ethics regulations governing military biomedical research. Next, they argue that two common justifications for rapid military innovation in science and technology, including enhancement, fail. These justifications are (a) to satisfy a compelling military need and (b) strategic dominance. The authors then turn to an objection that turns on the idea that we need not have these justifications if warfighters are willing to adopt enhancement, and argue that laissez-faire approaches to enhancement fail in the context of the military due to pressing and historically significant concerns about coercion and exploitation. The paper concludes with what is referred to as the “least-worst” justification: Given the rise of untested enhancements in civilian and military life, we have good reason to validate potential enhancements even if they do not satisfy reasons (a) or (b) above.
Objectives Heat-stressed Mesoamerican workers, such as sugarcane cutters, suffer from high rates of chronic kidney disease of non-traditional origin (CKDnt). We aimed to identify easily available early markers of rapid kidney function decline in a population at high risk of CKDnt. Design The accuracy of different biomarkers measured during harvest for prediction of cross-harvest kidney function decline were assessed in an exploratory study group, and the performance of the most promising biomarker was then assessed in an independent confirmation group. Setting Male sugarcane cutters in El Salvador and Nicaragua. Participants 39 male Salvadoran sugarcane cutters sampled fortnightly at ≤9 occasions before and after work shift during harvest. 371 male Nicaraguan sugarcane cutters were sampled as part of routine monitoring during two harvests. Cutters worked at high physical intensity at wet-bulb globe temperatures mostly above 29°C for 6–8 hours per day 6 days a week during the 5–6 months harvest season. Primary outcomes Change in estimated glomerular filtration rate (CKD Epidemiology Collaboration) across the harvest season (ΔeGFR cross-harvest ). Results Dipstick leukocyturia after work shift in the El Salvadoran group was the most promising marker, explaining >25% of ΔeGFR cross-harvest variance at 8/9 occasions during harvest. Leukocyturia was associated with experiencing fever, little or dark urine, cramps, headache, dizziness and abdominal pain in the preceding 2-week period. Decreasing blood haemoglobin (Hb) and eGFR during harvest were also predictive of ΔeGFR cross-harvest . In the Nicaraguan confirmation dataset, those having ≥++ leukocyturia at any sampling during harvest had a 13 mL/min/1.73 m ² (95% CI 10 to 16 mL/min/1.73 m ² ) worse ΔeGFR cross-harvest than those without recorded leukocyturia. Conclusion Leukocyturia and Hb, both measurable with point-of-care methods, may be early indicators for kidney injury and risk for eGFR decline among heat-stressed male workers, thereby facilitating individual-level prevention and research aiming to understand the causes of CKDnt.
Since the beginning of the 21st century, we have experienced major pandemics and epidemics. However, we believe the COVID-19 pandemic was the first time a certain racial/ethnic group or nationality was blamed for the pandemic/epidemic. Anti-Asian racism and violence worldwide are not new, but they are on the rise during the COVID-19 pandemic. Although the crimes against Asians during the pandemic received substantial media attention, there has been a paucity of empirical research in social science that addresses xenophobic sentiments, racism, and violence against Asians. To bridge the gap, the Korean Society of Criminology in America (KOSCA) invited papers to address the current global issue of anti-Asian racism and violence in mid2021. It was challenging to conduct empirical research because of the lack of data availability, time restrictions, and the narrowed research scope (e.g., Asians). This editorial introduction introduces six articles in this Special Issue of Race and Justice, “Anti-Asian Racism & Violence.” We call for further, continuous attention to anti-Asian racism and violence, and we hope this special issue creates more scholarly discussion on this understudied, often-neglected topic.
Biological perspectives on criminology were widely accepted in the United States in the late 1800s to early 1900s, but quickly fell out of favor due to eugenicists in the field misusing research and sociocriminologists outside of the field vilifying this avenue of investigation. In recent years, the field has rebounded. This review provides a detailed history of biosocial criminology, exploring its development alongside sociocriminology with a focus on the social and personal histories that contributed to the resurgence of biosocial criminology. A brief and selective literature review follows, providing a general overview of methodologies used in the field, key findings, and policy and practice implications. We conclude by discussing the utility of the biosocial perspective in criminology for studying offending and victimization. We also discuss challenges of applying biosocial research to policy and practice, as well as next steps for the field.
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Mahdi Garelnabi
  • Department of Biomedical and Nutritional Sciences
Charles Levenstein
  • Department of Work Environment
Shakil Quayes
  • Department of Economics
Nelson Eby
  • Department of Environmental, Earth and Atmospheric Sciences
Amit Deokar
  • Department of Operations and Information Systems
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