Miracle-dz/UniFAR-FTUs huggingface dataset:
Empirical Analysis of the Presence of Power Elite in Media

Politicians, politically connected business persons, bureaucrats, celebrities, and highly placed government officials (collectively termed as the power elite in sociology literature) can influence national and regional policy for personal and organizational benefit, which may not always be in the best interests of the people. Media is a crucial tool to shape public opinion, and is used heavily by the power elite to bring legitimacy to their policy decisions. In this paper, we empirically analyze the coverage given to the power elite in mainstream media on Demonetization, a significant, recent policy event in India. We compare the extent of coverage given to the elite and non-elite, the policy slant expressed by them, and differences in coverage between seven of the largest news media organizations in India. We find that among the power elite, powerful politicians and political parties are given the maximum coverage in the media, with conspicuous negligence in coverage given to expert opinions. Sentiment analysis clearly reveals that opposing political factions express opposing views towards the policy, and there is variation across different news sources as well. We are applying our methods on other contentious policy events to be able to do a more systematic analysis of how media can aid the power elite to shape public opinion by giving them disproportionately large coverage and visibility.
Prevalence and Molecular and Antimicrobial Characteristics of Cronobacter spp. Isolated From Raw Vegetables in China

Cronobacter spp. is a foodborne pathogen that causes life-threatening and invasive diseases, such as necrotizing enterocolitis, meningitis, and sepsis. In this study, we aimed to investigate the prevalence, molecular characteristics and antimicrobial resistance of Cronobacter spp. in raw vegetables marketed in China. Based on dietary habits in China, 403 raw vegetables that could be eaten without additional cooking were collected. Of the 403 samples tested, 122 (30.27%) were positive for Cronobacter spp. , and the contamination levels exceeded 110 most probable number (MPN)/g for 16.39% (20/122) of the samples. Coriander samples had the highest contamination rate of 52.81%, and the MPN values of 19.15% of positive coriander samples exceeded 100 MPN/g. Eleven serotypes were identified among 171 isolates, with Cronobacter sakazakii serogroup O1 (41 isolates) being the dominant serotype. Molecular characterization indicated that there was quite high genetic diversity in Cronobacter spp. , and multilocus sequence typing analyses yielded 106 sequence types (STs), 55 of which were newly identified. Notably, the most prevalent ST (eight isolates) was C. malonaticus ST60, which appeared in a recent clinical infectious disease study in China. Five C. sakazakii ST4, seven C. malonaticus ST7, and three C. sakazakii ST8 confirmed as pathogenic STs in other countries were also detected in this study. Furthermore, all isolates were susceptible to amikacin, amoxicillin-clavulanic, cefepime, ciprofloxacin, and imipenem, but some isolates exhibited a high ratio of resistance to cephalothin (59.65%). In this study, the high contamination rate and the detection of pathogenic and new STs in raw vegetables indicated potential hazards to customers. To the best of our knowledge, this is the first report to provide valuable information on the contamination status of Cronobacter spp. in vegetables that can be eaten raw in China.
Time‐dynamic profiling with application to hospital readmission among patients on dialysis

Standard profiling analysis aims to evaluate medical providers, such as hospitals, nursing homes, or dialysis facilities, with respect to a patient outcome. The outcome, for instance, may be mortality, medical complications, or 30‐day (unplanned) hospital readmission. Profiling analysis involves regression modeling of a patient outcome, adjusting for patient health status at baseline, and comparing each provider's outcome rate (e.g., 30‐day readmission rate) to a normative standard (e.g., national “average”). Profiling methods exist mostly for non time‐varying patient outcomes. However, for patients on dialysis, a unique population which requires continuous medical care, methodologies to monitor patient outcomes continuously over time are particularly relevant. Thus, we introduce a novel time‐dynamic profiling (TDP) approach to assess the time‐varying 30‐day readmission rate. TDP is used to estimate, for the first time, the risk‐standardized time‐dynamic 30‐day hospital readmission rate, throughout the time period that patients are on dialysis. We develop the framework for TDP by introducing the standardized dynamic readmission ratio as a function of time and a multilevel varying coefficient model with facility‐specific time‐varying effects. We propose estimation and inference procedures tailored to the problem of TDP and to overcome the challenge of high‐dimensional parameters when examining thousands of dialysis facilities.
Vascular Malformation of the Face: a Rare Case with Follow-up of 18 Years

Objective Vascular malformations are structural anomalies in the blood vessels. They are present at birth and persist throughout life. These malformations can be classified according to the type of vessel involved. A port-wine stain is a vascular malformation characterized by an increased number of ectatic vessels in the dermal vascular plexus, which can be found in any part of the body, including the head and neck region. Over time, most of these stains result in soft tissue hypertrophy and this growth can cause severe facial deformity. Materials and Methods This study describes a rare case of a giant proliferative vascular anomaly arising from a port-wine stain on the face. Results The report highlights the continuous and proliferative growth of the malformation observed after follow-up of 18 years, as well as the difficulty in establishing the diagnosis due to the complexity and dimension of the lesion and the conditions related to the patient’s low socioeconomic status. Conclusions We have described a rare and unusual case report of a giant proliferative vascular malformation arising from a Port-wine stain on the face.
Design of extended burst-mode asynchronous controllers using synchronous CAD tools

Synchronous Finite State Machines (SFSM) are widely used in the control unit design of complex digital systems. These systems are implemented in CMOS DSM (Deep-Sub-Micron) technology and can present serious problems related to the global clock. In this context, the asynchronous paradigm shows interesting features that fit as an alternative for the design, despite of the difficulties of the application of asynchronous logic. This paper proposes a new state assignment method for Asynchronous FSMs, which is described by the popular specification known as Extended Burst-Mode (XBM). The state assignment method uses the two-hot code to encode the XBM_AFSMs. Also, the paper proposes a “necessary and sufficient” condition for XBM_AFSMs encoded in two-hot to be synthesized with conventional tools, in the steps of logic minimization and technology mapping. Doing a comparison for a set of fifteen benchmarks with AFSMs of local clock that use the conventional logical minimization, the proposed method obtained an average reduction of products of 23% and literals of 51%.
Leveraging Web Data to Monitor Changes in Corporate-Government Interlocks in India

Corporate executives who are linked to politicians or administrative officials, or family members of public officials with links to corporate organizations, are known to build an interlocking social network that becomes a power structure of highly influential entities. Such power structures often lead to an inequitable distribution of resources and manipulation of policies. A deeper look at this power structure and the constituent interlocks can provide users with valuable insights on these influential connections, and eventually, on the shaping of socio-economic outcomes by the interlocked political economy. In this paper, we describe the design of a platform to empirically monitor the degree of corporate-government interlock in India over time, by making use of publicly available data on the web. We find that the interlock has strengthened over the last decade, and we report the kind of interconnections and structural changes that have happened during this time. We also describe the design of an application to present news articles about an event or topic alongside the interconnection network of entities referred to in the news articles, to help users get a quick view of the main actors involved in the event. We find that this news search application is able to highlight several interconnections between prominent entities in an event, which had not been reported in the media. Overall, we find it relevant to build a technology platform which can help researchers and journalists to monitor the extent of interlocks between powerful stakeholders in the corporate and government spheres.
Persistent reductions in the bioavailability of PCBs at a tidally inundated Phragmites australis marsh amended with activated carbon

In situ amendment of sediments with highly sorbent materials like activated carbon (AC) is an increasingly viable strategy to reduce the bioavailability of persistent, sediment‐associated contaminants to benthic communities. Because in situ sediment remediation is an emerging strategy, much remains to be learned about the field conditions under which amendments can be effective, the resilience of amendment materials toward extreme weather conditions, and the optimal design of engineered applications. We report the results of a multiyear, pilot‐scale field investigation designed to measure the persistence and efficacy of AC amendments to reduce the bioavailability of polychlorinated biphenyls (PCBs) in an intertidal Phragmites marsh. The amendments tested were granular AC (GAC), GAC with a layer of sand, and a pelletized fine AC. Key metrics presented include vertically resolved black carbon concentrations in sediment and PCB concentrations in sediment, porewater, and several invertebrate species. The results demonstrate that all 3 amendments withstood Hurricane Sandy and remained in place for the duration of the study, successfully reducing porewater PCB concentrations by 34 to 97%. Reductions in invertebrate bioaccumulation were observed in all amendment scenarios, with pelletized fine AC producing the most pronounced effect. The present findings support the use of engineered AC amendments in intertidal marshes and can be used to inform amendment design, delivery, and monitoring at other contaminated sediment sites. Environ Toxicol Chem 2018;37:2496–2505. © 2018 SETAC
API Blindspots: Why Experienced Developers Write Vulnerable Code

Despite the best efforts of the security community, security vulnerabilities in software are still prevalent, with new vulnerabilities reported daily and older ones stubbornly repeating themselves. One potential source of these vulnerabilities is shortcomings in the used language and library APIs. Developers tend to trust APIs, but can misunderstand or misuse them, introducing vulnerabilities. We call the causes of such misuse blindspots. In this paper, we study API blindspots from the developers’ perspective to: (1) determine the extent to which developers can detect API blindspots in code and (2) examine the extent to which developer characteristics (i.e., perception of code correctness, familiarity with code, conﬁdence, professional experience, cognitive function, and personality) affect this capability. We conducted a study with 109 developers from four countries solving programming puzzles that involve Java APIs known to contain blindspots. We ﬁnd that (1) The presence of blindspots correlated negatively with the developers’ accuracy in answering implicit security questions and the developers’ ability to identify potential security concerns in the code. This effect was more pronounced for I/O-related APIs and for puzzles with higher cyclomatic complexity. (2) Higher cognitive functioning and more programming experience did not predict better ability to detect API blindspots. (3) Developers exhibiting greater openness as a personality trait were more likely to detect API blindspots. This study has the potential to advance API security in (1) design, implementation, and testing of new APIs; (2) addressing blindspots in legacy APIs; (3) development of novel methods for developer recruitment and training based on cognitive and personality assessments; and (4) improvement of software development processes (e.g., establishment of security and functionality teams).
Carrier Level-Shifted Based Control Method for the PWM 3L-T-Type qZS Inverter With Capacitor Imbalance Compensation

This paper presents a modified carrier level-shifted based control method for a pulsewidth modulation controlled three-phase three-level T-type quasi-impedance-source inverter. The benefits of the proposed strategy are a uniform distribution of shoot-through states of constant width throughout the fundamental period and the mitigation of the inner capacitors’ voltages imbalance. The latter is achieved by means of a proportional-integral controller, which adjusts the relative time application of redundant states. The improved performance is demonstrated in terms of reliability, as the capacitors do not suffer from neutral-point imbalance. The control method can also be implemented in a different multilevel inverter configuration with an impedance-source network. A comprehensive simulation study and several experiments were performed in order to validate the adopted method in situations of imbalanced capacitor voltages.
Autoencoders Learn Generative Linear Models

We provide a series of results for unsupervised learning with autoencoders. Specifically, we study shallow two-layer autoencoder architectures with shared weights. We focus on three generative models for data that are common in statistical machine learning: (i) the mixture-of-gaussians model, (ii) the sparse coding model, and (iii) the sparsity model with non-negative coefficients. For each of these models, we prove that under suitable choices of hyperparameters, architectures, and initialization, autoencoders learned by gradient descent can successfully recover the parameters of the corresponding model. To our knowledge, this is the first result that rigorously studies the dynamics of gradient descent for weight-sharing autoencoders. Our analysis can be viewed as theoretical evidence that shallow autoencoder modules indeed can be used as feature learning mechanisms for a variety of data models, and may shed insight on how to train larger stacked architectures with autoencoders as basic building blocks.
Elevated lactate level predicts intensive care unit admissions, endoscopies and transfusions in patients with acute gastrointestinal bleeding

Background and aims Initial clinical management decision in patients with acute gastrointestinal bleeding (GIB) is often based on identifying high- and low-risk patients. Little is known about the role of lactate measurement in the triage of patients with acute GIB. We intended to assess if lactate on presentation is predictive of need for intervention in patients with acute GIB. Patients and methods We performed a single-center, retrospective, cross-sectional study including patients ≥18 years old presenting to emergency with acute GIB between January 2014 and December 2014. Intensive care unit (ICU) admission, inpatient endoscopy (upper endoscopy and/or colonoscopy), and packed red blood cell (PRBC) transfusion were assessed as outcomes. Analyses included univariate and multivariate logistic regression analyses. Results Of 1,237 patients with acute GIB, 468 (37.8%) had venous lactate on presentation. Of these patients, 165 (35.2%) had an elevated lactate level (>2.0 mmol/L). Patients with an elevated lactate level were more likely to be admitted to ICU than patients with a normal lactate level (adjusted odds ratio [AOR] 2.96, 95% confidence interval [CI] 1.74–5.01; p<0.001). Patients with an elevated lactate level were more likely to receive PRBC transfusion (AOR 3.65, 95% CI 1.76–7.55; p<0.001) and endoscopy (AOR 1.64, 95% CI 1.02–2.65; p=0.04) than patients with a normal lactate level. Conclusion Elevated lactate level predicts the need for ICU admissions, transfusions, and endoscopies in patients with acute GIB. Lactate measurement may be a useful adjunctive test in the triage of patients with acute GIB.
Solving Systems of Quadratic Equations via Exponential-type Gradient Descent Algorithm

We consider the rank minimization problem from quadratic measurements, i.e., recovering a rank $r$ matrix $X \in \mathbb{R}^{n \times r}$ from $m$ scalar measurements $y_i=a_i^{\top} XX^{\top} a_i,\;a_i\in \mathbb{R}^n,\;i=1,\ldots,m$. Such problem arises in a variety of applications such as quadratic regression and quantum state tomography. We present a novel algorithm, which is termed exponential-type gradient descent algorithm, to minimize a non-convex objective function $f(U)=\frac{1}{4m}\sum_{i=1}^m(y_i-a_i^{\top} UU^{\top} a_i)^2$. This algorithm starts with a careful initialization, and then refines this initial guess by iteratively applying exponential-type gradient descent. Particularly, we can obtain a good initial guess of $X$ as long as the number of Gaussian random measurements is $O(nr)$, and our iteration algorithm can converge linearly to the true $X$ (up to an orthogonal matrix) with $m=O\left(nr\log (cr)\right)$ Gaussian random measurements.
Osmosis through a Semi-permeable Membrane: a Consistent Approach to Interactions

The movement of ionic solutions is an essential part of biology and technology. Fluidics, from nano- to micro- to microfluidics, is a burgeoning area of technology which is all about the movement of ionic solutions, on various scales. Many cells, tissues, and organs of animals and plants depend on osmosis, as the movement of fluids is called in biology. Indeed, the movement of fluids through channel proteins (that have a hole down their middle) is fluidics on an atomic scale. Ionic fluids are complex fluids, with energy stored in many ways. Ionic fluids flow driven by gradients of concentration, chemical and electrical potential, and hydrostatic pressure. Each flow is classically described by its own field theory, independent of the others, but of course, in reality every gradient drives every kind of flow to a varying extent. Combining field equations is tricky and so the theory of complex fluids derives the equations, rather than assumes their interactions. When field equations are derived, rather than assumed, their variables are consistent. That is to say all variables satisfy all equations under all conditions with one set of parameters. Here we treat a classical osmotic cell in this spirit, using a sharp interface method to derive boundary conditions consistent with all flows and fields. We allow volume to change with concentration, since changes of volume are a property of ionic solutions known to all who make them in the laboratory. We consider flexible and inflexible membranes. We show how to combine the energetics of the membrane with the energetics of the surrounding complex fluids. The results seem general but need application to specific situations of technological, biological and experimental importance before the consequences of consistency can be understood.
Increased Healthcare Utilization for Medical Comorbidities Prior to Surgery Improves Postoperative Outcomes.

OBJECTIVE The purpose of this study was to evaluate the impact of optimization of preoperative comorbidities by nonsurgical clinicians on short-term postoperative outcomes. SUMMARY BACKGROUND DATA Preoperative comorbidities can have substantial effects on operative risk and outcomes. The modifiability of these comorbidity-associated surgical risks remains poorly understood. METHODS We identified patients with a major comorbidity (eg, diabetes, heart failure) undergoing an elective colectomy in a multipayer national administrative database (2010-2014). Patients were included if they could be matched to a preoperative surgical clinic visit within 90 days of an operative intervention by the same surgeon. The explanatory variable of interest ("preoperative optimization") was defined by whether the patient was seen by an appropriate nonsurgical clinician between surgical consultation and subsequent surgery. We assessed the impact of an optimization visit on postoperative complications with use of propensity score matching and multilevel, multivariable logistic regression. RESULTS We identified 4531 colectomy patients with a major potentially modifiable comorbidity (propensity weighted and matched effective sample size: 6037). After matching, the group without an optimization visit had a higher rate of complications (34.6% versus 29.7%, P = 0.001). An optimization visit conferred a 31% reduction in the odds of a complication (P < 0.001) in an adjusted analysis. Median preoperative costs increased by $684 (P < 0.001) in the optimized group, and a complication increased total costs of care by $14,724 (P < 0.001). CONCLUSIONS AND RELEVANCE We demonstrated an association between use of nonsurgical clinician visits by comorbid patients prior to surgery and a significantly lower rate of complications. These findings support the prospective study of preoperative optimization as a potential mechanism for improving postoperative outcomes.
Federated Learning with Non-IID Data

Federated learning enables resource-constrained edge compute devices, such as mobile phones and IoT devices, to learn a shared model for prediction, while keeping the training data local. This decentralized approach to train models provides privacy, security, regulatory and economic benefits. In this work, we focus on the statistical challenge of federated learning when local data is non-IID. We first show that the accuracy of federated learning reduces significantly, by up to 55% for neural networks trained for highly skewed non-IID data, where each client device trains only on a single class of data. We further show that this accuracy reduction can be explained by the weight divergence, which can be quantified by the earth mover's distance (EMD) between the distribution over classes on each device and the population distribution. As a solution, we propose a strategy to improve training on non-IID data by creating a small subset of data which is globally shared between all the edge devices. Experiments show that accuracy can be increased by 30% for the CIFAR-10 dataset with only 5% globally shared data.
Slfn2 Regulates Type I Interferon Responses by Modulating the NF-κB Pathway

Although members of the Slfn family have been implicated in the regulation of type I interferon (IFN) responses, the mechanisms by which they mediate their effects remain unknown. In the present study, we provide evidence that targeted disruption of the Slfn2 gene leads to increased transcription of IFN-stimulated genes (ISGs) and enhanced type I IFN-mediated antiviral responses. ABSTRACT Although members of the Slfn family have been implicated in the regulation of type I interferon (IFN) responses, the mechanisms by which they mediate their effects remain unknown. In the present study, we provide evidence that targeted disruption of the Slfn2 gene leads to increased transcription of IFN-stimulated genes (ISGs) and enhanced type I IFN-mediated antiviral responses. We demonstrate that Slfn2 interacts with protein phosphatase 6 regulatory subunit 1 (PPP6R1), leading to reduced type I IFN-induced activation of nuclear factor kappa B (NF-κB) signaling, resulting in reduced expression of ISGs. Altogether, these data suggest a novel mechanism by which Slfn2 controls ISG expression and provide evidence for a critical role for Slfn2 in the regulation of IFN-mediated biological responses.