Inverse Projection Representation and Category Contribution Rate for Robust Tumor Recognition

Sparse representation based classification (SRC) methods have achieved remarkable results. SRC, however, still suffer from requiring enough training samples, insufficient use of test samples and instability of representation. In this paper, a stable inverse projection representation based classification (IPRC) is presented to tackle these problems by effectively using test samples. An IPR is firstly proposed and its feasibility and stability are analyzed. A classification criterion named category contribution rate is constructed to match the IPR and complete classification. Moreover, a statistical measure is introduced to quantify the stability of representation-based classification methods. Based on the IPRC technique, a robust tumor recognition framework is presented by interpreting microarray gene expression data, where a two-stage hybrid gene selection method is introduced to select informative genes. Finally, the functional analysis of candidate's pathogenicity-related genes is given. Extensive experiments on six public tumor microarray gene expression datasets demonstrate the proposed technique is competitive with state-of-the-art methods.Comment: 14 pages, 19 figures, 10 table

Thiamine Deficiency Causes Long-Lasting Neurobehavioral Deficits in Mice

Thiamine deficiency (TD) has detrimental effects on brain health and neurobehavioral development, and it is associated with many aging-related neurological disorders. To facilitate TD-related neuropsychological studies, we generated a TD mouse model by feeding a thiamine-deficient diet for 30 days, followed by re-feeding the control diet for either one week or 16 weeks as recovery treatment. We then performed neurobehavioral tests in these two cohorts: cohort of one week post TD treatment (1 wk-PTDT) and 16 weeks post TD treatment (16 wks-PTDT). The TD mice showed no significant difference from control in any tests in the 1 wk-PTDT cohort at the age of 13–14 weeks. The tests for the 16 wks-PTDT cohort at the age of 28–29 weeks, however, demonstrated anxiety and reduced locomotion in TD animals in open field and elevated plus maze. In comparison, rotor rod and water maze revealed no differences between TD and control mice. The current findings of the differential effects of the same TD treatment on locomotion and anxiety at different ages may reflect the progressive and moderate change of TD-induced neurobehavioral effects. The study suggests that, even though the immediate neurobehavioral impact of TD is modest or negligible at a young age, the impact could develop and become severe during the aging process

Uncertainty Intervals for Prediction Errors in Time Series Forecasting

Inference for prediction errors is critical in time series forecasting pipelines. However, providing statistically meaningful uncertainty intervals for prediction errors remains relatively under-explored. Practitioners often resort to forward cross-validation (FCV) for obtaining point estimators and constructing confidence intervals based on the Central Limit Theorem (CLT). The naive version assumes independence, a condition that is usually invalid due to time correlation. These approaches lack statistical interpretations and theoretical justifications even under stationarity. This paper systematically investigates uncertainty intervals for prediction errors in time series forecasting. We first distinguish two key inferential targets: the stochastic test error over near future data points, and the expected test error as the expectation of the former. The stochastic test error is often more relevant in applications needing to quantify uncertainty over individual time series instances. To construct prediction intervals for the stochastic test error, we propose the quantile-based forward cross-validation (QFCV) method. Under an ergodicity assumption, QFCV intervals have asymptotically valid coverage and are shorter than marginal empirical quantiles. In addition, we also illustrate why naive CLT-based FCV intervals fail to provide valid uncertainty intervals, even with certain corrections. For non-stationary time series, we further provide rolling intervals by combining QFCV with adaptive conformal prediction to give time-average coverage guarantees. Overall, we advocate the use of QFCV procedures and demonstrate their coverage and efficiency through simulations and real data examples.Comment: 35 pages, 17 figure

Fenton Reagent Oxidation and Decolorizing Reaction Kinetics of Reactive Red SBE

AbstractFenton reagent was employed to treat and decolorize the wastewater of Reactive Red SBE by on-line spectrophotometry. The effects of initial FeSO4 concentration, initial H2O2 concentration, pH, reactive red SBE and temperature on the decoloration of reactive red SBE were investigated. The results show that Fenton oxidize process follows pseudo first order kinetics in the first stage and reaction activation energy is 2.608 kJ/mol. The decolorizing reaction rate constants (k) increase with the rise of FeSO4 concentration, H2O2 concentration, temperature, but decrease with the rise of reactive red SBE, and the optimum pH is 3. Initial FeSO4 concentration and initial H2O2 concentration against k are linear correlation

2,4-Dibromo-6-[(hydroxyimino)methyl]phenol

In the title compound, C7H5Br4NO2, intra­molecular O—H⋯N hydrogen bonds are observed. In the crystal structure, inter­molecular O—H⋯O hydrogen bonds link the mol­ecules into dimers

Analysis of the scalar doubly heavy tetraquark states with QCD sum rules

In this article, we perform a systematic study of the mass spectrum of the scalar doubly charmed and doubly bottom tetraquark states using the QCD sum rules.Comment: 17 pages, 24 figures, add more discussion

China collection 2.1: Aerosol Optical Depth dataset for mainland China at 1km resolution

A wide range of data products have been published since the operation of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on NASA's TERRA and AQUA satellites. Based on DarkTarget and DeepBlue method, NASA has published Aerosol Optical Depth (AOD) products Collection 6.0 with spatial resolution of 3km. Although validated globally, regional and systematic errors are still found in the MODIS-retrieved AOD products. This is especially remarkable for bright heterogeneous land surface, such as mainland China. In order to solve the aerosol retrieval problem over heterogeneous bright land surface, the Synergetic Retrieval of Aerosol Properties algorithm (SRAP) has been developed based on the synergetic use of the MODIS data of TERRA and AQUA satellites. Using the SRAP algorithm, we produced AOD dataset-China Collection 2.1 at 1km spatial resolution, dated from August 2002 to 2012. We compared the China Collection 2.1 AOD datasets for 2010 with AERONET data. From those 2460 collocations, representing mutually cloud-free conditions, we find that 62% of China Collection 2.1 AOD values comparing with AERONET-observed values within an expected error envelop of 20% and 55% within an expected error envelop of 15%. Compared with MODIS Level 2 aerosol products, China Collection 2.1 AOD datasets have a more complete coverage with fewer data gaps over the study region

Mesencephalic Astrocyte-Derived Neurotrophic Factor (MANF) Regulates Neurite Outgrowth through the Activation of Akt/mTOR and Erk/mTOR Signaling Pathways

Neurite outgrowth is essential for brain development and the recovery of brain injury and neurodegenerative diseases. In this study, we examined the role of the neurotrophic factor MANF in regulating neurite outgrowth. We generated MANF knockout (KO) neuro2a (N2a) cell lines using clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 and demonstrated that MANF KO N2a cells failed to grow neurites in response to RA stimulation. Using MANF siRNA, this finding was confirmed in human SH-SY5Y neuronal cell line. Nevertheless, MANF overexpression by adenovirus transduction or addition of MANF into culture media facilitated the growth of longer neurites in RA-treated N2a cells. MANF deficiency resulted in inhibition of Akt, Erk, mTOR, and P70S6, and impaired protein synthesis. MANF overexpression on the other hand facilitated the growth of longer neurites by activating Akt, Erk, mTOR, and P70S6. Pharmacological blockade of Akt, Erk or mTOR eliminated the promoting effect of MANF on neurite outgrowth. These findings suggest that MANF positively regulated neurite outgrowth by activating Akt/mTOR and Erk/mTOR signaling pathways