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Simply Unnatural Supersymmetry [article]

Nima Arkani-Hamed, Arpit Gupta, David E. Kaplan, Neal Weiner, Tom Zorawski
2012 arXiv   pre-print
The current measurement of the Higgs mass, the ubiquitous nature of loop-suppressed gaugino masses in gravity-mediated supersymmetry breaking, relic dark matter density from ∼ TeV mass gauginos, together with the success of supersymmetric gauge coupling unification, suggest that scalar superpartner masses are roughly m_sc∼ 100-1000 TeV. Higgsino masses, if not at the Planck scale, should generically appear at the same scale. The gaugino mass contributions from anomaly mediation, with the heavy
more » ... iggsino threshold, generally leads to a more compressed spectrum than standard anomaly mediation, while the presence of extra vector-like matter near m_sc typically leads to an even more compressed spectrum. Heavy Higgsinos improve gauge coupling unification relative to the MSSM. Heavy scalars suggest new possibilities for flavor physics -- large flavor violations in the soft masses are now allowed, yielding interesting levels for new FCNC's, and re-opening the attractive possibility of a radiatively generated fermion mass hierarchy. Gluinos and binos/winos must decay through higher dimension operators, giving a unique handle on the presence of new physics the scale m_sc. Gluino decays should be spectacular, for example yielding events with four tops -- at modestly displaced vertices -- and two Higgses plus missing energy. The high scale m_sc can also be probed in flavor-violating gluino decays, as well as a specific pattern of gluino branching ratios to the third generation. Finally, with heavy Higgsinos, the dominant decay for neutral winos and binos proceeds via the Higgs b̃→w̃ h. The heaviness of the Higgsinos can be inferred from the branching ratio for the rare decay b̃→w̃ Z.
arXiv:1212.6971v1 fatcat:m7bnk6amrze6zcbi6u5agsnpqi

Linear Verrucous Epidermal Nevus

Arpit Gupta, Ruchi Rai
2019 Indian Pediatrics  
include surgical excision, laser, cryotherapy and topical/ intralesional glucocorticoids, with varying success rates and a high risk of recurrence.ARPIT GUPTA AND RUCHI RAI*Department of Neonatology-MRH  ... 
pmid:31729336 fatcat:tniyja4yqrc5xljmkzuzi3yelu

Optimizing human factors in dentistry

Arpit Gupta, AnilV Ankola, Mamata Hebbal
2013 Dental Research Journal  
Occupational health hazards among dental professionals are on a continuous rise and they have a significant negative overall impact on daily life. This review is intended to provide the information regarding risk factors and to highlight the prevention strategies for optimizing human factors in dentistry. Risk factors among dentists are multifactorial, which can be categorized into biomechanical and psychosocial. To achieve a realistic target of safety and health at work, prevention is clearly
more » ... he best approach; therefore, musculoskeletal disorders can be reduced through proper positioning of dental worker and patient, regular rest breaks, general good health, using ergonomic equipment, and exercises designed to counteract the particular risk factors for the dental occupation. However, substantial evidences are still required to elucidate the potential risk factors and to formulate effective prevention programs.
doi:10.4103/1735-3327.113362 pmid:23946745 pmcid:PMC3731969 fatcat:4jz3tti25za67fyjcuturoe7um

Sonata: Query-Driven Network Telemetry [article]

Arpit Gupta, Rob Harrison, Ankita Pawar, Rüdiger Birkner, Marco Canini, Nick Feamster, Jennifer Rexford, Walter Willinger
2017 arXiv   pre-print
More recently, Gupta et al.  ... 
arXiv:1705.01049v1 fatcat:o3rzfjtho5gyjiec5mu2usay2i

Inequality in India Declined during COVID

Arpit Gupta, Anup Malani, Bartosz Woda
2021 Social Science Research Network  
., 2021; Gupta et al., 2021; Malani et al., 2020) . A common inference is that this shock was likely therefore also regressive.  ... 
doi:10.2139/ssrn.3990161 fatcat:hxgnf5qle5hxfbcx5t4qwujeoe

Cross-Lingual Approaches to Reference Resolution in Dialogue Systems [article]

Amr Sharaf, Arpit Gupta, Hancheng Ge, Chetan Naik, Lambert Mathias
2018 arXiv   pre-print
In the slot-filling paradigm, where a user can refer back to slots in the context during the conversation, the goal of the contextual understanding system is to resolve the referring expressions to the appropriate slots in the context. In this paper, we build on the context carryover system Naik2018ContextualSC, which provides a scalable multi-domain framework for resolving references. However, scaling this approach across languages is not a trivial task, due to the large demand on acquisition
more » ... f annotated data in the target language. Our main focus is on cross-lingual methods for reference resolution as a way to alleviate the need for annotated data in the target language. In the cross-lingual setup, we assume there is access to annotated resources as well as a well trained model in the source language and little to no annotated data in the target language. In this paper, we explore three different approaches for cross-lingual transfer — delexicalization as data augmentation, multilingual embeddings and machine translation. We compare these approaches both on a low resource setting as well as a large resource setting. Our experiments show that multilingual embeddings and delexicalization via data augmentation have a significant impact in the low resource setting, but the gains diminish as the amount of available data in the target language increases. Furthermore, when combined with machine translation we can get performance very close to actual live data in the target language, with only 25% of the data projected into the target language.
arXiv:1811.11161v1 fatcat:fxt6dfdtojef7imk25nj7imcoq

DynamiQ: Planning for Dynamics in Network Streaming Analytics Systems [article]

Rohan Bhatia, Arpit Gupta, Rob Harrison, Daniel Lokshtanov, Walter Willinger
2021 arXiv   pre-print
The emergence of programmable data-plane targets has motivated a new hybrid design for network streaming analytics systems that combine these targets' fast packet processing speeds with the rich compute resources available at modern stream processors. However, these systems require careful query planning; that is, specifying the minute details of executing a given set of queries in a way that makes the best use of the limited resources and programmability offered by data-plane targets. We use
more » ... ch an existing system, Sonata, and real-world packet traces to understand how executing a fixed query workload is affected by the unknown dynamics of the traffic that defines the target's input workload. We observe that static query planning, as employed by Sonata, cannot handle even small changes in the input workload, wasting data-plane resources to the point where query execution is confined mainly to userspace. This paper presents the design and implementation of DynamiQ, a new network streaming analytics platform that employs dynamic query planning to deal with the dynamics of real-world input workloads. Specifically, we develop a suite of practical algorithms for (i) computing effective initial query plans (to start query execution) and (ii) enabling efficient updating of portions of such an initial query plan at runtime (to adapt to changes in the input workload). Using real-world packet traces as input workload, we show that compared to Sonata, DynamiQ reduces the stream processor's workload by two orders of magnitude.
arXiv:2106.05420v1 fatcat:x3ehfpw3erev3n4yfjfbaee6qu

Characterizing Performance Inequity Across U.S. Ookla Speedtest Users [article]

Udit Paul, Jiamo Liu, Vivek Adarsh, Mengyang Gu, Arpit Gupta, Elizabeth Belding
2021 arXiv   pre-print
The Internet has become indispensable to daily activities, such as work, education and health care. Many of these activities require Internet access data rates that support real-time video conferencing. However, digital inequality persists across the United States, not only in who has access but in the quality of that access. Speedtest by Ookla allows users to run network diagnostic tests to better understand the current performance of their network. In this work, we leverage an Internet
more » ... ance dataset from Ookla, together with an ESRI demographic dataset, to conduct a comprehensive analysis that characterizes performance differences between Speedtest users across the U.S. Our analysis shows that median download speeds for Speedtest users can differ by over 150Mbps between states. Further, there are important distinctions between user categories. For instance, all but one state showed statistically significant differences in performance between Speedtest users in urban and rural areas. The difference also exists in urban areas between high and low income users in 27 states. Our analysis reveals that states that demonstrate this disparity in Speedtest results are geographically bigger, more populous and have a wider dispersion of median household income. We conclude by highlighting several challenges to the complex problem space of digital inequality characterization and provide recommendations for furthering research on this topic.
arXiv:2110.12038v1 fatcat:qokzayivizbopi7mvn3r57cdym

Learning to Navigate Autonomously in Outdoor Environments : MAVNet [article]

Saumya Kumaar, Arpit Sangotra, Sudakshin Kumar, Mayank Gupta, Navaneethkrishnan B, S N Omkar
2018 arXiv   pre-print
In the modern era of automation and robotics, autonomous vehicles are currently the focus of academic and industrial research. With the ever increasing number of unmanned aerial vehicles getting involved in activities in the civilian and commercial domain, there is an increased need for autonomy in these systems too. Due to guidelines set by the governments regarding the operation ceiling of civil drones, road-tracking based navigation is garnering interest . In an attempt to achieve the above
more » ... entioned tasks, we propose an imitation learning based, data-driven solution to UAV autonomy for navigating through city streets by learning to fly by imitating an expert pilot. Derived from the classic image classification algorithms, our classifier has been constructed in the form of a fast 39-layered Inception model, that evaluates the presence of roads using the tomographic reconstructions of the input frames. Based on the Inception-v3 architecture, our system performs better in terms of processing complexity and accuracy than many existing models for imitation learning. The data used for training the system has been captured from the drone, by flying it in and around urban and semi-urban streets, by experts having at least 6-8 years of flying experience. Permissions were taken from required authorities who made sure that minimal risk (to pedestrians) is involved in the data collection process. With the extensive amount of drone data that we collected, we have been able to navigate successfully through roads without crashing or overshooting, with an accuracy of 98.44%. The computational efficiency of MAVNet enables the drone to fly at high speeds of upto 6m/sec. We present the same results in this research and compare them with other state-of-the-art methods of vision and learning based navigation.
arXiv:1809.00396v1 fatcat:ldnh4rtutjdqpij467oiew2g5e

Skin or Skim? Inside Investment and Hedge Fund Performance

Arpit Gupta
2017 Social Science Research Network  
Business and Columbia University. We thank Billy Xu for excellent research assistance. See https://www.skinorskim.org for Form ADV data used in this paper. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research. NBER working papers are circulated for discussion and comment purposes. They have not been peer-reviewed or been subject to the review by the NBER Board of Directors that accompanies official NBER publications.
doi:10.2139/ssrn.2982889 fatcat:zwx3baktm5dsnj3xtxqey7i5ma

Cancer Diagnoses and Household Debt Overhang

Arpit Gupta, Edward R. Morrison, Catherine Fedorenko, Scott D Ramsey
2015 Social Science Research Network  
This paper explores the role of capital structure in determining how households respond to unanticipated shocks. We draw on a novel dataset linking individual cancer records to high-quality administrative data on personal mortgages, bankruptcies, foreclosures, and credit reports. We find that cancer diagnoses induce a substantial increase in various measures of financial stress regardless of whether the patient carries health insurance. Foreclosure rates, for example, increase 65 percent during
more » ... the five years following diagnosis. The effect, however, is concentrated among patients with low levels of housing equity. Highly leveraged households default, undergo foreclosure, or file for bankruptcy; less-levered households cope with health shocks by drawing on home equity and other sources of liquidity. These results point to the critical role of capital structure in determining how households respond to severe shocks. They also suggest that household leverage may merit as much policy attention as health insurance.
doi:10.2139/ssrn.2583975 fatcat:eor7pljuxvhive23f2o3a2uboq

Gaugomaly mediation revisited

Arpit Gupta, David E. Kaplan, Tom Zorawski
2013 Journal of High Energy Physics  
Most generic models of hidden sector supersymmetry breaking do not feature singlets, and gauginos obtain masses from anomaly mediated supersymmetry breaking. If one desires a natural model, then the dominant contribution to scalar masses should be of the same order, i.e. also from AMSB. However, pure AMSB models suffer from the tachyonic slepton problem. Moreover, there is a large splitting between the gluino and the wino LSP masses resulting in tight exclusion limits from typical superpartner
more » ... earches. We introduce messenger fields into this framework to obtain a hybrid theory of gauge and anomaly mediation, solving both problems simultaneously. Specifically, we find any number of vector-like messenger fields (allowed by GUT unification) compress the predicted gaugino spectrum when their masses come from the Giudice-Masiero mechanism. This more compressed spectrum is less constrained by LHC searches and allows for lighter gluinos. In addition to the model, we present gaugino pole mass equations that differ from (and correct) the original literature.
doi:10.1007/jhep11(2013)149 fatcat:ub3ivzgszvcqta44q33jua4gum

Smart Highway Energy Generation

Arpit Gupta
2019 International Journal of Scientific Research in Science and Technology  
Energy generation has seen significant development in recent years. This investigation describes a new technique for generating energy from the waste kinetic energy of the vehicles speed & the practical side we have been able to produce and store electrical energy using the vehicle minimum speed also without any extra cost for the land.If our concept is implementation throughout India, it not only increases the power generation to more than a few gig watts of electricity but also has other
more » ... us fringe benefits including longer road life, employment generation, reduced CO2 emission in environment.
doi:10.32628/ijsrst196165 fatcat:i2mtlyxpvjhl3inj6fdpqo4b4m

CORAL: Contextual Response Retrievability Loss Function for Training Dialog Generation Models [article]

Bishal Santra, Ravi Ghadia, Arpit Dwivedi, Manish Gupta, Pawan Goyal
2022 arXiv   pre-print
Natural Language Generation (NLG) represents a large collection of tasks in the field of NLP. While many of these tasks have been tackled well by the cross-entropy (CE) loss, the task of dialog generation poses a few unique challenges for this loss function. First, CE loss assumes that for any given input, the only possible output is the one available as the ground truth in the training dataset. In general, this is not true for any task, as there can be multiple semantically equivalent
more » ... , each with a different surface form. This problem gets exaggerated further for the dialog generation task, as there can be multiple valid responses (for a given context) that not only have different surface forms but are also not semantically equivalent. Second, CE loss does not take the context into consideration while processing the response and, hence, it treats all ground truths with equal importance irrespective of the context. But, we may want our final agent to avoid certain classes of responses (e.g. bland, non-informative or biased responses) and give relatively higher weightage for more context-specific responses. To circumvent these shortcomings of the CE loss, in this paper, we propose a novel loss function, CORAL, that directly optimizes recently proposed estimates of human preference for generated responses. Using CORAL, we can train dialog generation models without assuming non-existence of response other than the ground-truth. Also, the CORAL loss is computed based on both the context and the response. Extensive comparisons on two benchmark datasets show that the proposed methods outperform strong state-of-the-art baseline models of different sizes.
arXiv:2205.10558v1 fatcat:mqvnior5kjghpomn2kdtf5uwoa

Prenatal Presentation of Medulloepithelioma: Case and Literature Review

Nidhi Arora, Chanchal Ahmed, Arpit Gupta, Nitin Ghonge, Anita Kaul
2019 Cureus  
Congenital brain tumors (CBTs) are extremely rare and account for only 0.5%-1.9% of all pediatric brain tumors. Medulloepithelioma is one of the rare tumors with an incidence of about 1% among all CBTs with a very dismal prognosis and typically diagnosed at the median age of 24 months. The objective is reporting medulloepithelioma presenting in the intrauterine period with very few prior cases being reported in the prenatal period, and to add to the limited existing literature on
more » ... oma. We present a rare case of medulloepithelioma referred to us in the antenatal period at 27 weeks and subsequently causing intrauterine fetal demise. Prenatal MRI of the fetal brain and postnatal histopathological findings on autopsy were suggestive of intracranial medulloepithelioma.
doi:10.7759/cureus.5018 pmid:31285981 pmcid:PMC6605960 fatcat:slyvcz7defhzzinzsinmlcvs2u
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