On Expressivity and Trainability of Quadratic Networks

Inspired by the diversity of biological neurons, quadratic artificial neurons can play an important role in deep learning models. The type of quadratic neurons of our interest replaces the inner-product operation in the conventional neuron with a quadratic function. Despite promising results so far achieved by networks of quadratic neurons, there are important issues not well addressed. Theoretically, the superior expressivity of a quadratic network over either a conventional network or a conventional network via quadratic activation is not fully elucidated, which makes the use of quadratic networks not well grounded. Practically, although a quadratic network can be trained via generic backpropagation, it can be subject to a higher risk of collapse than the conventional counterpart. To address these issues, we first apply the spline theory and a measure from algebraic geometry to give two theorems that demonstrate better model expressivity of a quadratic network than the conventional counterpart with or without quadratic activation. Then, we propose an effective and efficient training strategy referred to as ReLinear to stabilize the training process of a quadratic network, thereby unleashing the full potential in its associated machine learning tasks. Comprehensive experiments on popular datasets are performed to support our findings and evaluate the performance of quadratic deep learning

Density alteration in non-physiological cells

In the present study an important phenomenon of cells was discovered: the change of intracellular density in cell's response to drug and environmental factors. For convenience, this phenomenon is named as "density alteration in non-physiological cells" ( DANCE). DANCE was determined by discontinuous sucrose gradient centrifugation (DSGC), in which cells were separated into several bands. The number and position of the bands in DSGC varied with the change of cell culture conditions, drugs, and physical process, indicating that cell's response to these factors was associated with alteration of intracellular density. Our results showed that the bands of cells were molecularly different from each other, such as the expression of some mRNAs. For most cells tested, intracellular density usually decreased when the cells were in bad conditions, in presence of drugs, or undergoing pathological changes. However, unlike other tissue cells, brain cells showed increased intracellular density in 24 hrs after the animal death. In addition, DANCE was found to be related to drug resistance, with higher drug-resistance in cells of lower intracellular density. Further study found that DANCE also occurred in microorganisms including bacteria and fungus, suggesting that DANCE might be a sensitive and general response of cells to drugs and environmental change. The mechanisms for DANCE are not clear. Based on our study the following causes were hypothesized: change of metabolism mode, change of cell membrane function, and pathological change. DANCE could be important in medical and biological sciences. Study of DANCE might be helpful to the understanding of drug resistance, development of new drugs, separation of new subtypes from a cell population, forensic analysis, and importantly, discovery of new physiological or pathological properties of cells

3,4-Dihy­droxy­phenethyl acetate

In the title compound, C10H12O4, the dihedral angle between the acetate group and the aromatic ring is 20.47 (10)°. In the crystal, mol­ecules are linked by O—H⋯O hydrogen bonds, forming [001] chains. Weak C—H⋯O inter­actions consolidate the packing

Effects of acute ammonia exposure and post-exposure recovery on nonspecific immunity in Clam Cyclina sinensis

This study aimed to assess the toxicity of ammonia on clam Cyclina sinensis and the post-exposure recovery. With increased exposure to TAN, the alkaline phosphatase (AKP) activities after exposure showed a trend of growing initially and subsequently decreasing, whereas the AKP activities after post-exposure recovery showed an increasing trend. The AKP activities after post-exposure recovery were significantly higher than those in control. The acid phosphatase (ACP) activities in T1 and T2 after post-exposure recovery were higher than those in the control, whereas the ACP activities in T3, T4, and T5 after post-exposure recovery were significantly higher than those in the control. The lysozyme (LZM) activities in T1 and T2 after exposure were significantly higher than those in control, whereas the LZM activities in T3, T4, and T5 after exposure were significantly lower than those in the control. Overall, ACP and LZM in the clams exposed to a low level of TAN (≤ 40 mg/L) can recover to the normal levels completely. However, a 48h recovery period scarcely seems adequate to compensate for AKP, ACP, and LZM activities in the clams exposed to a high level of TAN (> 40 mg/L)

Identifying the physical origin of gamma-ray bursts with supervised machine learning

The empirical classification of gamma-ray bursts (GRBs) into long and short GRBs based on their durations is already firmly established. This empirical classification is generally linked to the physical classification of GRBs originating from compact binary mergers and GRBs originating from massive star collapses, or Type I and II GRBs, with the majority of short GRBs belonging to Type I and the majority of long GRBs belonging to Type II. However, there is a significant overlap in the duration distributions of long and short GRBs. Furthermore, some intermingled GRBs, i.e., short-duration Type II and long-duration Type I GRBs, have been reported. A multi-parameter classification scheme of GRBs is evidently needed. In this paper, we seek to build such a classification scheme with supervised machine learning methods, chiefly XGBoost. We utilize the GRB Big Table and Greiner's GRB catalog and divide the input features into three subgroups: prompt emission, afterglow, and host galaxy. We find that the prompt emission subgroup performs the best in distinguishing between Type I and II GRBs. We also find the most important distinguishing feature in prompt emission to be T_{90}, hardness ratio, and fluence. After building the machine learning model, we apply it to the currently unclassified GRBs to predict their probabilities of being either GRB class, and we assign the most probable class of each GRB to be its possible physical class.Comment: 23 pages, 8 tables, 11 figures, accepted for publication by ApJ. Full version of Table 5 is available as ancillary materia

1-{(1Z)-1-[6-(4-Chloro­phen­oxy)hex­y­l­oxy]-1-(2,4-difluoro­phen­yl)prop-1-en-2-yl}-1H-1,2,4-triazol-4-ium nitrate

In the title compound, C23H25ClF2N3O2 +·NO3 −, the triazole ring makes dihedral angles of 60.9 (4) and 25.0 (3)° with the 6-chloro­phenyl and 2,4-difluoro­phenyl rings, respectively. The mol­ecule adopts a Z configuration about the C=C double bond. In the crystal, the cations and anions are linked by N—H⋯O hydrogen bonds and weak C—H⋯O inter­actions

Effects of methylphenidate on attentional set-shifting in a genetic model of attention-deficit/hyperactivity disorder

Abstract Background Although deficits of attentional set-shifting have been reported in individuals with attention deficit/hyperactivity disorder (ADHD), it is rarely examined in animal models. Methods This study compared spontaneously hypertensive rats (SHRs; a genetic animal model of ADHD) and Wistar-Kyoto (WKY) and Sprague-Dawley (SD) rats (normoactive control strains), on attentional set-shifting task (ASST) performance. Furthermore, the dose-effects of methylphenidate (MPH) on attentional set-shifting of SHR were investigated. In experiment 1, ASST procedures were conducted in SHR, WKY and SD rats of 8 each at the age of 5 weeks. Mean latencies at the initial phase, error types and numbers, and trials to criteria at each stage were recorded. In experiment 2, 24 SHR rats were randomly assigned to 3 groups of 8 each-- MPH-L (lower dose), MPH-H (higher dose), and SHR-vehicle groups. From 3 weeks, they were administered 2.5 mg/kg or 5 mg/kg MPH or saline respectively for 14 consecutive days. All rats were tested in the ASST at the age of 5 weeks. Results The SHRs generally exhibited poorer performance on ASST than the control WKY and SD rats. Significant strain effects on mean latency [F (2, 21) = 639.636, p p p p p Conclusions The SHR may be impaired in discrimination learning, reversal learning and attentional set-shifting. Our study provides evidence that MPH may improve the SHR's performance on attentional set-shifting and lower dose is more effective than higher dose.</p