Predictive Model Degrees of Freedom in Linear Regression

Overparametrized interpolating models have drawn increasing attention from machine learning. Some recent studies suggest that regularized interpolating models can generalize well. This phenomenon seemingly contradicts the conventional wisdom that interpolation tends to overfit the data and performs poorly on test data. Further, it appears to defy the bias-variance trade-off. As one of the shortcomings of the existing theory, the classical notion of model degrees of freedom fails to explain the intrinsic difference among the interpolating models since it focuses on estimation of in-sample prediction error. This motivates an alternative measure of model complexity which can differentiate those interpolating models and take different test points into account. In particular, we propose a measure with a proper adjustment based on the squared covariance between the predictions and observations. Our analysis with least squares method reveals some interesting properties of the measure, which can reconcile the "double descent" phenomenon with the classical theory. This opens doors to an extended definition of model degrees of freedom in modern predictive settings.Comment: 47 pages, 18 figure

A Graph-Theoretic Approach to Brain Networks Associated with Swallowing

The functional connectivity between brain regions during swallowing is still not well understood. Understanding these complex interactions is of a great interest from scientific and clinical perspectives. In this study, we utilize functional magnetic resonance imaging (fMRI) to investigate brain functional networks during voluntary saliva swallowing in twenty two adult healthy subjects (all females, 23.1 ± 1.52 years of age). To construct these functional connections, we compute mean partial correlation matrices over ninety brain regions for each participant. Two regions are considered functionally connected if they showed statistically significant correlations. These correlation matrices are then analyzed using graph-theoretical approaches. In particular, we consider several network measures for the whole brain and swallowing-related brain regions. The results have shown that significant pairwise functional connections are mostly either local and intra-hemispheric or symmetrically inter-hemispheric. Furthermore, we have shown that the human brain functional network had robust small-world properties, which support efficient parallel information transfer at a relatively low cost. Swallowing related brain regions also had higher values for some of the network measures in comparison when these measures were calculated for the whole brain. Our results have demonstrated the basic network properties of the human brain compatible with previous functional network studies, but also showed unique connections in some regions during swallowing. This leads us to believe that graph-theoretical approaches are a valid tool for the analysis of the swallowing functional connectivity

Single-Unit Leadless EEG Sensor

Non-convulsive seizure (NCS) and non-convulsive status epilepticus (NCSE) are severe neurological disorders within intensive care units (ICUs) and emergency departments (EDs). Traditionally, physiological monitoring in ICUs and EDs focuses on cardiopulmonary variables, including blood pressure and heart rate. The neurological conditions, on the other hand, are often assessed by bedside observations from physicians. Without proper monitoring tools, the NCS and NCSE that lack observable clinical manifestations are easily overlooked or misdiagnosed. The problem can be amplified among patients with impaired consciousness who cannot respond to environmental stimuli. The delayed detection and treatment lead to substantial morbidity, mortality, and healthcare costs. Currently, electroencephalography (EEG) is the most effective diagnostic tool for NCS and NCSE in ICUs and EDs. Meanwhile, less than two percent of the critically ill patients in ICUs and EDs are undergoing EEG. The under-adoption or decreased utilization of EEG originates from challenges to accommodate EEG into established practice protocols. Therefore, the timely acquisition of EEG has been one of the paramount needs in today’s emergency care. This dissertation presents a novel EEG sensor that is leadless, self-contained, and the size of a U.S. Penny. The sensor enables rapid EEG setup and efficient EEG acquisition. The dissertation first investigated into a novel EEG electrode-structure enclosing four unique arc-shaped electrodes. We demonstrated the feasibility of such electrode configuration by experimental investigations on both a physical model and a healthy human subject. The dissertation then presented Monte Carlo simulations to predict the statistical performance of the single-unit sensor on the whole brain. A forward computation algorithm was implemented to compute the scalp potential in response to dipolar sources within an analytically modeled brain. The data-informed findings indicated that the whole-brain quantitative performance of this electrode configuration is comparable to the cup electrode currently used as the gold standard. The results are presented in a multi-variant probability density function. Taken a step further, a deterministic solution to such probability model was derived. These results provide insights into the workings of the single-unit sensor. Furthermore, a single-unit sensor prototype was constructed with a specially designed electronic system. The performance of the prototype was validated through experiments on a healthy human subject. Lastly, the efficacy of the prototype is demonstrated indirectly using pre-recorded EEG data from epilepsy patients. It has been observed that seizure signal can be detected via a neighboring bipolar recording configuration, which closely simulates the case of single-unit sensors for the detection of NCS and NCSE. The results of series of investigations conclude the feasibility and single-unit sensors in detecting epileptic EEG signals

1-(3-Pyrid­yl)pyrrolidine-2,5-dione

In the title mol­ecule, C9H8N2O2, the dihedral angle between the pyridine and the pyrrolidine rings is 64.58 (12)°. In the crystal structure, weak C—H⋯π-electron ring inter­actions stabilize the packing

Multi-timescale Event Detection in Nonintrusive Load Monitoring based on MDL Principle

Load event detection is the fundamental step for the event-based non-intrusive load monitoring (NILM). However, existing event detection methods with fixed parameters may fail in coping with the inherent multi-timescale characteristics of events and their event detection accuracy is easily affected by the load fluctuation. In this regard, this paper extends our previously designed two-stage event detection framework, and proposes a novel multi-timescale event detection method based on the principle of minimum description length (MDL). Following the completion of step-like event detection in the first stage, a long-transient event detection scheme with variable-length sliding window is designed for the second stage, which is intended to provide the observation and characterization of the same event at different time scales. In that, the context information in the aggregated load data is mined by motif discovery, and then based on the MDL principle, the proper observation scales are selected for different events and the corresponding detection results are determined. In the post-processing step, a load fluctuation location method based on voice activity detection (VAD) is proposed to identify and remove the unreasonable events caused by fluctuations. Based on newly proposed evaluation metrics, the comparison tests on public and private datasets demonstrate that our method achieves higher detection accuracy and integrity for events of various appliances across different scenarios.Comment: 11 pages,16 figure

State-Relevant Maxwell's Equation from Kaluza-Klein Theory

We study a five-dimensional perfect fluid coupled with Kaluza-Klein (KK) gravity. By dimensional reduction, a modified form of Maxwell's equation is obtained, which is relevant to the equation of state of the source. Since the relativistic magnetohydrodynamics (MHD) and the 3-dimensional formulation are widely used to study space matter, we derive the modified Maxwell's equations and relativistic MHD in 3+1 form. We then take an ideal Fermi gas as an example to study the modified effect, which can be visible under high density or high energy condition, while the traditional Maxwell's equation can be regarded as a result in the low density and low temperature limit. We also indicate the possibility to test the state-relevant effect of KK theory in a telluric laboratory.Comment: 11 pages, 3 figures; version published in PR

Effects of L-carnitine against oxidative stress in human hepatocytes: involvement of peroxisome proliferator-activated receptor alpha

<p>Abstract</p> <p>Background</p> <p>Excessive oxidative stress and lipid peroxidation have been demonstrated to play important roles in the production of liver damage. L-carnitine is a natural substance and acts as a carrier for fatty acids across the inner mitochondrial membrane for subsequent beta-oxidation. It is also an antioxidant that reduces metabolic stress in the cells. Recent years L-carnitine has been proposed for treatment of various kinds of disease, including liver injury. This study was conducted to evaluate the protective effect of L-carnitine against hydrogen peroxide (H₂O₂)-induced cytotoxicity in a normal human hepatocyte cell line, HL7702.</p> <p>Methods</p> <p>We analyzed cytotoxicity using MTT assay and lactate dehydrogenase (LDH) release. Antioxidant activity and lipid peroxidation were estimated by reactive oxygen species (ROS) levels, activities and protein expressions of superoxide dismutase (SOD) and catalase (CAT), and malondialdehyde (MDA) formation. Expressions of peroxisome proliferator-activated receptor (PPAR)-alpha and its target genes were evaluated by RT-PCR or western blotting. The role of PPAR-alpha in L-carnitine-enhanced expression of SOD and CAT was also explored. Statistical analysis was performed by a one-way analysis of variance, and its significance was assessed by Dennett's post-hoc test.</p> <p>Results</p> <p>The results showed that L-carnitine protected HL7702 cells against cytotoxity induced by H₂O₂. This protection was related to the scavenging of ROS, the promotion of SOD and CAT activity and expression, and the prevention of lipid peroxidation in cultured HL7702 cells. The decreased expressions of PPAR-alpha, carnitine palmitoyl transferase 1 (CPT1) and acyl-CoA oxidase (ACOX) induced by H₂O₂can be attenuated by L-carnitine. Besides, we also found that the promotion of SOD and CAT protein expression induced by L-carnitine was blocked by PPAR-alpha inhibitor MK886.</p> <p>Conclusions</p> <p>Taken together, our findings suggest that L-carnitine could protect HL7702 cells against oxidative stress through the antioxidative effect and the regulation of PPAR-alpha also play an important part in the protective effect.</p

Comprehension of indirect requests is influenced by their degree of imposition

In everyday conversation, much communication is achieved using indirect language. This is particularly true when we utter requests. The decision to use indirect language is influenced by a number of factors including deniability, politeness, and the degree of imposition on the receiver of a request. In this paper we report the results of an eye-tracking experiment examining the influence on reading of the degree of imposition of a request. We manipulate whether context describes a situation in which the level of imposition on the receiver of the request is high (which thus motivates the use of indirect language) with one in which the level of imposition is low (and thus does not motivate the use of indirect language). We compare the comprehension of statements that are phrased indirectly with the comprehension of statements that are phrased more directly. We find that statements phrased indirectly are read more quickly in contexts where the level of imposition on the receiver is high versus when the level of imposition is low. In contrast, we find the processing of statements phrased directly does not vary as a function of level of imposition. This indicates that readers use pragmatic knowledge to guide interpretation of indirect requests. Our data provide an insight into the interface between pragmatic and semantic processing

De novo characterization of a whitefly transcriptome and analysis of its gene expression during development

<p>Abstract</p> <p>Background</p> <p>Whitefly (<it>Bemisia tabaci</it>) causes extensive crop damage throughout the world by feeding directly on plants and by vectoring hundreds of species of begomoviruses. Yet little is understood about its genes involved in development, insecticide resistance, host range plasticity and virus transmission.</p> <p>Results</p> <p>To facilitate research on whitefly, we present a method for <it>de novo </it>assembly of whitefly transcriptome using short read sequencing technology (Illumina). In a single run, we produced more than 43 million sequencing reads. These reads were assembled into 168,900 unique sequences (mean size = 266 bp) which represent more than 10-fold of all the whitefly sequences deposited in the GenBank (as of March 2010). Based on similarity search with known proteins, these analyses identified 27,290 sequences with a cut-off E-value above 10^-5. Assembled sequences were annotated with gene descriptions, gene ontology and clusters of orthologous group terms. In addition, we investigated the transcriptome changes during whitefly development using a tag-based digital gene expression (DGE) system. We obtained a sequencing depth of over 2.5 million tags per sample and identified a large number of genes associated with specific developmental stages and insecticide resistance.</p> <p>Conclusion</p> <p>Our data provides the most comprehensive sequence resource available for whitefly study and demonstrates that the Illumina sequencing allows <it>de novo </it>transcriptome assembly and gene expression analysis in a species lacking genome information. We anticipate that next generation sequencing technologies hold great potential for the study of the transcriptome in other non-model organisms.</p

The Application of Functional Grease in the Army Diet

The comprehensive construction of modern logistics is a major strategic task of military logistics in the new century and a major guarantee to promote the modernization of national defense and military construction.Focusing on the problem of oil intake in the current military dietary structure, this paper take the Soldier special provision nutritional oil（SSPNO）canteens as the research target to explore the properties of various functional grease and the feasibility of applying them to army diets, so as to provide ideas for the design and development of such products, and also provide guarantees for further strengthening the physical quality and combat effectiveness of soldiers