Privacy-Preserving Outsourcing of Large-Scale Nonlinear Programming to the Cloud

The increasing massive data generated by various sources has given birth to big data analytics. Solving large-scale nonlinear programming problems (NLPs) is one important big data analytics task that has applications in many domains such as transport and logistics. However, NLPs are usually too computationally expensive for resource-constrained users. Fortunately, cloud computing provides an alternative and economical service for resource-constrained users to outsource their computation tasks to the cloud. However, one major concern with outsourcing NLPs is the leakage of user's private information contained in NLP formulations and results. Although much work has been done on privacy-preserving outsourcing of computation tasks, little attention has been paid to NLPs. In this paper, we for the first time investigate secure outsourcing of general large-scale NLPs with nonlinear constraints. A secure and efficient transformation scheme at the user side is proposed to protect user's private information; at the cloud side, generalized reduced gradient method is applied to effectively solve the transformed large-scale NLPs. The proposed protocol is implemented on a cloud computing testbed. Experimental evaluations demonstrate that significant time can be saved for users and the proposed mechanism has the potential for practical use.Comment: Ang Li and Wei Du equally contributed to this work. This work was done when Wei Du was at the University of Arkansas. 2018 EAI International Conference on Security and Privacy in Communication Networks (SecureComm

Fostering the healthcare workforce during the COVID‐19 pandemic: Shared leadership, social capital, and contagion among health professionals

Health professionals managing patients with COVID-19 disease are at high risk of contagion. All medical personnel involved in caring for patients need coordination, knowledge and trust. Empirical work on human resources has tended to focus on the effects of human resource practices on performance, whereas leadership and social interactions have been overlooked. Based upon interviews with medical staff working in specialised medical units, this study uses the social capital theory to examine relationships among shared leadership, social capital, and contagion rates. First, shared leadership was found to positively affect COVID-19 contagion among health professionals. Second, by sharing information and a common language, and showing high levels of trust, namely social capital, medical units seem to reduce contagion rates of COVID-19. In other words, shared leadership plays a fundamental role in improving performance in healthcare by means of social capital

Chemical Hand Warmer Packet Ingestion: A Case of Elemental Iron Exposure.

For individuals who work outdoors in the winter or play winter sports, chemical hand warmers are becoming increasingly more commonplace because of their convenience and effectiveness. A 32-year-old woman with a history of chronic pain and bipolar disorder presented to the emergency department complaining of a warm sensation in her mouth and epigastrium after reportedly ingesting the partial contents of a chemical hand warmer packet containing between 5 and 8 g of elemental iron. She had been complaining of abdominal pain for approximately 1 month and was prescribed unknown antibiotics the previous day. The patient denied ingestion of any other product or medication other than what was prescribed. A serum iron level obtained approximately 6 hours after ingestion measured 235 micrograms/dL (reference range 40-180 micrograms/dL). As the patient demonstrated no new abdominal complaints and no evidence of systemic iron toxicity, she was discharged uneventfully after education. However, the potential for significant iron toxicity exists depending on the extent of exposure to this or similar products. Treatment for severe iron toxicity may include fluid resuscitation, whole bowel irrigation, and iron chelation therapy with deferoxamine. Physicians should become aware of the toxicity associated with ingestion of commercially available hand warmers. Consultation with a medical toxicologist is recommended

Signal Propagation in Feedforward Neuronal Networks with Unreliable Synapses

In this paper, we systematically investigate both the synfire propagation and firing rate propagation in feedforward neuronal network coupled in an all-to-all fashion. In contrast to most earlier work, where only reliable synaptic connections are considered, we mainly examine the effects of unreliable synapses on both types of neural activity propagation in this work. We first study networks composed of purely excitatory neurons. Our results show that both the successful transmission probability and excitatory synaptic strength largely influence the propagation of these two types of neural activities, and better tuning of these synaptic parameters makes the considered network support stable signal propagation. It is also found that noise has significant but different impacts on these two types of propagation. The additive Gaussian white noise has the tendency to reduce the precision of the synfire activity, whereas noise with appropriate intensity can enhance the performance of firing rate propagation. Further simulations indicate that the propagation dynamics of the considered neuronal network is not simply determined by the average amount of received neurotransmitter for each neuron in a time instant, but also largely influenced by the stochastic effect of neurotransmitter release. Second, we compare our results with those obtained in corresponding feedforward neuronal networks connected with reliable synapses but in a random coupling fashion. We confirm that some differences can be observed in these two different feedforward neuronal network models. Finally, we study the signal propagation in feedforward neuronal networks consisting of both excitatory and inhibitory neurons, and demonstrate that inhibition also plays an important role in signal propagation in the considered networks.Comment: 33pages, 16 figures; Journal of Computational Neuroscience (published

Cycle-centrality in complex networks

Networks are versatile representations of the interactions between entities in complex systems. Cycles on such networks represent feedback processes which play a central role in system dynamics. In this work, we introduce a measure of the importance of any individual cycle, as the fraction of the total information flow of the network passing through the cycle. This measure is computationally cheap, numerically well-conditioned, induces a centrality measure on arbitrary subgraphs and reduces to the eigenvector centrality on vertices. We demonstrate that this measure accurately reflects the impact of events on strategic ensembles of economic sectors, notably in the US economy. As a second example, we show that in the protein-interaction network of the plant Arabidopsis thaliana, a model based on cycle-centrality better accounts for pathogen activity than the state-of-art one. This translates into pathogen-targeted-proteins being concentrated in a small number of triads with high cycle-centrality. Algorithms for computing the centrality of cycles and subgraphs are available for download

The Efficacy and Safety Profile of Netarsudil 0.02% in Glaucoma Treatment: Real-World Outcomes

Introduction: More effective glaucoma medications are necessary as medication intolerance and non-adherence remain problematic. Netarsudil is a newly FDA-approved Rho kinase inhibitor. We hypothesize that netarsudil will safely reduce intraocular pressure (IOP) compared to baseline even while other glaucoma medications are used. Methods: This retrospective observational study was conducted on glaucoma patients seen at the Wills Eye Hospital Glaucoma Service who received netarsudil 0.02% between March and September of 2018. Intraocular pressure (IOP, via Goldmann applanation tonometry) and best corrected visual acuity (BCVA, via Snellen visual acuity charts) comparisons between baseline and 1- and 3-month follow-up visits were performed using Student’s t-tests. Results: This study included 172 eyes of 108 patients. Compared to baseline, a mean±SD decrease in IOP of 3.67±4.91 and 3.91±4.83 mmHg was noted at 1- and 3-month follow-up visits, respectively (both p\u3c0.001). No statistically significant difference in IOP change between patients on ≥3 and \u3c3 glaucoma medications at month 1 was observed (p=0.667). Conjunctival hyperemia was the most common side effect at months 1 and 3 (15.7% and 23.0% of patients, respectively). Blurred vision was reported at 1- and 3-month follow-up (5.8% and 8.0% of patients, respectively), but no significant difference in BCVA was observed (p= 0.723 and 0.611, respectively). Discussion: With a mild side effect profile, netarsudil yielded a significant IOP reduction in glaucoma patients, including significant reductions in patients on ≥3 medications. Given its efficacy and unique mechanism of action, earlier-line use of netarsudil may be considered

Radiative Electroweak Symmetry Breaking in a Little Higgs Model

We present a new Little Higgs model, motivated by the deconstruction of a five-dimensional gauge-Higgs model. The approximate global symmetry is $SO(5)_0\times SO(5)_1$, breaking to $SO(5)$, with a gauged subgroup of $[SU(2)_{0L}\times U(1)_{0R}]\times O(4)_1$, breaking to $SU(2)_L \times U(1)_Y$. Radiative corrections produce an additional small vacuum misalignment, breaking the electroweak symmetry down to $U(1)_{EM}$. Novel features of this model are: the only un-eaten pseudo-Goldstone boson in the effective theory is the Higgs boson; the model contains a custodial symmetry, which ensures that $\hat{T}=0$ at tree-level; and the potential for the Higgs boson is generated entirely through one-loop radiative corrections. A small negative mass-squared in the Higgs potential is obtained by a cancellation between the contribution of two heavy partners of the top quark, which is readily achieved over much of the parameter space. We can then obtain both a vacuum expectation value of $v=246$ GeV and a light Higgs boson mass, which is strongly correlated with the masses of the two heavy top quark partners. For a scale of the global symmetry breaking of $f=1$ TeV and using a single cutoff for the fermion loops, the Higgs boson mass satisfies 120 GeV $\lesssim M_H\lesssim150$ GeV over much of the range of parameter space. For $f$ raised to 10 TeV, these values increase by about 40 GeV. Effects at the ultraviolet cutoff scale may also raise the predicted values of the Higgs boson mass, but the model still favors $M_H\lesssim 200$ GeV.Comment: 32 pages, 10 figures, JHEP style. Version accepted for publication in JHEP. Includes additional discussion of sensitivity to UV effects and fine-tuning, revised Fig. 9, added appendix and additional references

When Anomaly Mediation is UV Sensitive

Despite its successes---such as solving the supersymmetric flavor problem---anomaly mediated supersymmetry breaking is untenable because of its prediction of tachyonic sleptons. An appealing solution to this problem was proposed by Pomarol and Rattazzi where a threshold controlled by a light field deflects the anomaly mediated supersymmetry breaking trajectory, thus evading tachyonic sleptons. In this paper we examine an alternate class of deflection models where the non-supersymmetric threshold is accompanied by a heavy, instead of light, singlet. The low energy form of this model is the so-called extended anomaly mediation proposed by Nelson and Weiner, but with potential for a much higher deflection threshold. The existence of this high deflection threshold implies that the space of anomaly mediated supersymmetry breaking deflecting models is larger than previously thought.Comment: 14 pages, 1 figure (version to appear in JHEP