Miracle-dz/UniFAR-FTUs huggingface dataset:
PII: S1010-7940(00)00383-3

Objective: To assess risk factors for hospital death and neurologic outcome after surgery on the proximal thoracic aorta using moderate hypothermic circulatory arrest and bilateral antegrade selective cerebral perfusion. Methods: From October 1995 through June 1999, 163 patients with a mean age of 63 ^ 11 years underwent surgery using bilateral antegrade selective cerebral perfusion. Degenerative aneurysms (55%) and acute type A dissection (28%) were the predominant indications for operation. Forty-six (28%) operations were considered as emergency procedure. Twenty-four (15%) procedures were reoperations. Results: Mean ASCP time was 48 ^ 20 min. Hospital mortality was 8.6% (n  14; 70% con®dence limit (CL): 6.4±10.8%). Univariate risk factors for hospital mortality were acute type A dissection (P  0:003), central neurologic damage ,24 h before the operation (P  0:000), preoperative hemodynamic instability (P  0:034), and rethoracotomy for any cause (P  0:036). Logistic regression analysis identi®ed central neurologic damage ,24 h (P  0:006, odds ratio 14) as an independent risk factor. Temporary neurologic damage occurred in 3.8% (n  6; 70% CL: 2.3±5.3%) of patients. Logistic regression analysis indicated preoperative hemodynamic instability (P  0:003, odds ratio 13) as an independent risk factor. Perioperative permanent central neurologic damage was reported in another 3.8% (n  6; 70% CL: 2.3±5.3%) patients. Acute type A dissection (P  0:018, odds ratio 8) and the non-use of a midline sternotomy (P  0:049, odds ratio 8) were retained as independent risk factors. Conclusion: Hospital mortality and perioperative neurologic complications are not signi®cantly in ̄uenced by the duration of antegrade selective cerebral perfusion. Overall complication rate is low. q 2000 Elsevier Science B.V. All rights reserved.
AgBr / (Sr 0.6 Bi 0.305 ) 2 Bi 2 O 7 Heterostructured Composites: Fabrication, Characterization, and Signiﬁcantly Enhanced Photocatalytic Activity

: The pyrochlore-type (Sr 0.6 Bi 0.305 ) 2 Bi 2 O 7 (SBO) containing Bi 3 + and Bi 5 + mixed valent states was ﬁrst investigated as a photocatalyst in our very recent work. To further improve the photocatalytic performance, AgBr / SBO heterostructured composites were synthesized by using a deposition-precipitation method. The characterization of phase structure, morphology, microstructure, elemental composition, and optical properties of the obtained products were performed using X-ray di ﬀ ractometer (XRD), ﬁeld emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM)TEM, X-ray photoelectron spectroscopy (XPS), UV-visible di ﬀ use reﬂectance spectroscopy (UV-vis DRS). The photocatalytic activity of samples was evaluated by degrading methylene blue under visible light illumination. AgBr / SBO composites possess high stability and signiﬁcantly enhanced photocatalytic performance. The improvement of photocatalytic activity is due to the enhanced light absorption and the separation of photoinduced electrons and holes on the interface of AgBr / SBO heterostructured composites.
The Perspectives in Gait Recognition

In this paper we provide a detailed information on classical and recent research results in gait recognition. We provide classiﬁcation of leading concepts, representations, experiments and available datasets. The most promising algorithms are provided with more details and in the end we provide some predictions on future research. Paper contains also summary on methods used in a variety of papers on gait recognition published after 2002.
De Novo Draft Genome Assembly Using Fuzzy K-mers

-Although second generation sequencing technology can be used to rapidly sequence an entire genome, assembly algorithms require a high level of coverage to produce a complete genomic sequence. We describe a fuzzy k -mer approach that is capable of rapidly ordering and orientating low coverage sequence reads with a high level of accuracy. Using this approach, a draft genome of Mycoplasma genitalium , sampled at varying low levels of coverage, was accurately anchored against the genome of Mycoplasma pneumoniae . The anchored reads were assembled into scaffolds with a vastly increased N50 length and an error rate of <1.5%.
Comparasion of 1DoF IMC and 2DoF IMC Method to Control Shell Heavy Oil Fractionator(SHOF) Model

— Shell Heavy Oil Fractionator (SHOF) is a distillation column type used to separate crude oil into desired products based on the boiling point difference of each product. The design of control on SHOF has several constraints, it is caused by non-linearity of the process, mulrivariable interactions, long dead time, and disturbances. It needs the control method that make the system response track the set point and eliminate the disturbances. This research is designed comparasion of 1 DoF IMC and 2 DoF IMC method to controlling SHOF with 3x3 MIMO decentralized in the form of First Order Plus Dead Time (FOPDT). Filter parameter tuning on this controller using Rivera filter parameter tuning method. Interaction between subsystems is reduced by applying the Relative Gain Array method and decoupling. The designed controllers were simulated in the MATLAB/SIMULINK environment. From the simulation results it was proven that the 2 DoF IMC showed the better performance compared to 1 DoF IMC with IAE respectively value of 44,4454 at , 19,2279 at , and 0,1483 at on set point tracking test respectively, and IAE value 93,9574 at , 40,0455 at , and 0,0099at on disturbance rejection test.
NEUROPROTECTIVE EFFECTS OF d-δ-TOCOTRIENOL RICH FRACTION ON CRUSHED SCIATIC NERVE IN DIABETIC RATS

Background: Peripheral neuropathy in diabetes is believed to be due to the reduced blood flow, altered antioxidant defense mechanism and glycemic status. Aims: Since vitamin E is an antioxidant and its potent neuroprotective form is tocotrienols, the current study was designed to explore the neuroprotective effects of d-δ-tocotrienol rich fraction (d-δ - TRF) on sciatic nerve regeneration not only in healthy but also in diabetic rats. Methods and Material: Diabetes was induced through single subcutaneous injection of alloxan (100 mg/kg). Twenty four albino rats included in the study were divided into four groups; healthy control, diabetic control, healthy treated and diabetic treated. Treated groups were administered d-δ - TRF orally and daily at the dose of 200 mg/kg for three weeks. Right sciatic nerve was approached through mid-thigh skin incision and was crushed with Kocher‟s forceps. Functional, histopathological, histomorphological and biochemical parameters were analyzed on 3 rd week. Statistical analysis: One way „ANOVA‟ followed by Tukeys test and Student t test were used for statistical significance. Results: It was noticed that d-δ - TRF significantly improves the antioxidant level, glycemic status and revascularization. It also accelerates regeneration and remyelination of nerve and reorganization of extracellular matrix in both healthy and diabetic rats. Conclusions: It is concluded that the d-δ - TRF is a strong antioxidant and antidiabetic dietary supplement in the management of crushed nerve injury in diabetics.
ASSOCIATION OF Fc (cid:1) RECEPTOR IIa (CD32) POLYMORPHISM WITH SEVERE MALARIA IN WEST AFRICA

Malaria continues to claim the lives of more children worldwide than any other infectious disease, and improved understanding of disease immunology is a priority for the development of new therapeutic and vaccination strategies. Fc (cid:1) RIIa (CD32) contains a polymorphic variant (H/R131) that has been associated with variability in susceptibility to both bacterial diseases and Plasmodium falciparum parasitemia. We investigated the role of this polymorphism in West Africans with mild and severe malarial disease. The HH131 genotype was significantly associated with susceptibility to severe malaria ( P (cid:1) 0.03, odds ratio (cid:1) 1.40, 95% confidence interval (cid:1) 1.02−1.91). In contrast to studies of parasitemia, the presence of the R131 allele, rather than the RR131 genotype, appeared to be the important factor in protection from disease. This is the first evidence for an association between CD32 polymorphism and severe malaria and provides an example of balancing selective pressures from different infectious diseases operating at the same genetic locus.
H INSECTICIDAL EFFICACY OF Azadirachta indica , NUCLEOPOLYHEDROVIRUS AND CHLORANTRANILIPROLE SINGLY OR COMBINED AGAINST FIELD POPULATIONS OF Helicoverpa armigera HÜBNER (LEPIDOPTERA: NOCTUIDAE)

The development of resistance in cosmopolitan insect Helicoverpa armigera Hübner (Lepidoptera: Noctuidae) forced the researchers for alternative control measures. In the present study, insecticidal efficacy of formulations of Azadirachta indica , a Nucleopolyhedrovirus (NPV), and new anthranilic diamide insecticide (chlorantraniliprole) formulations was determined against 2 nd , through 5 th larval instars of H. armigera collected from diverse geographical locations in the Punjab province, Pakistan. Azadirachta indica was applied at 5 µL L -1 ; NPV at 2.1 × 10 5 polyhedral occlusion bodies (POB) mL -1 and chlorantraniliprole at 0.01 µL L -1 , either alone or in combinations with each other. The bioassays were conducted at 27 ± 1 °C and 65 ± 5% relative humidity. The mortality varied greatly among treatments, larval instars, and locations. The combinations of NPV with A. indica and chlorantraniliprole caused higher mortality, pupation and produced an additive effect compared to their application singly in all the tested populations. The population from Rawalpindi was always susceptible while the Gujranwala was the resistant. The results herein suggest that the effectiveness of NPV and A. indica can be improved by the presence of chlorantraniliprole against the larvae of H. armigera .
University of Birmingham Super-luminous supernovae from PESSTO

We present optical spectra and light curves for three hydrogen-poor super-luminous supernovae followed by the Public ESO Spectroscopic Survey of Transient Objects (PESSTO). Time series spectroscopy from a few days after maximum light to 100 days later shows them to be fairly typical of this class, with spectra dominated by Ca II, Mg II, Fe II and Si II, which evolve slowly over most of the post-peak photospheric phase. We determine bolometric light curves and apply simple ﬁtting tools, based on the diﬀusion of energy input by magnetar spin-down, 56 Ni decay, and collision of the ejecta with an opaque circumstellar shell. We investigate how the heterogeneous light curves of our sample (combined with others from the literature) can help to con-strain the possible mechanisms behind these events. We have followed these events to beyond 100-200 days after peak, to disentangle host galaxy light from fading supernova ﬂux and to diﬀerentiate between the models, which predict diverse behaviour at this phase. Models powered by radioactivity require unrealistic parameters to reproduce the observed light curves, as found by previous studies. Both magnetar heating and circumstellar interaction still appear to be viable candidates. A large diversity is emerging in observed tail-phase luminosities, with magnetar models failing in some cases to predict the rapid drop in ﬂux. This would suggest either that magnetars are not responsible, or that the X-ray ﬂux from the magnetar wind is not fully trapped. The light curve of one object shows a distinct re-brightening at around 100d after maximum light. We argue that this could result either from multiple shells of circumstellar material, or from a magnetar ionisation front breaking out of the ejecta.
Phase transition of Two-timescale Two-temperature Spin-lattice Gas Model

We study phase transition of a nonequilibrium statistical-mechanical model, in which two degrees of freedom with different time scales separated from each other touch to their own heat bath. A general condition for finding anomalous negative latent heat recently discovered is derived a from thermodynamic argument. As a specific example, phase diagram of a spin-lattice gas model is studied based on a mean-field analysis with replica method. While configurational variables are spin and particle in this model, it is found that the negative latent heat appears in a parameter region of the model, irrespective of the order of their time scale. Qualitative differences in the phase diagram are also discussed.
Astragalus Polysaccharides Alleviate Type 2 Diabetic Rats by Reversing the Expressions of Sweet Taste Receptors and Genes Related to Glycolipid Metabolism in Liver

Sweet taste receptors (STRs) play an important role in glucose metabolism, and type 2 diabetic rats have abnormal expressions of STRs in multiple tissues. Astragalus polysaccharides (APS) has shown a significant therapeutic effect on type 2 diabetes mellitus (T2DM), but its mechanism needs to be further clarified. T2DM rat model was induced by intraperitoneal streptozotocin injection and treated with APS for 8 weeks. Daily indicators of experimental rats were observed, and expression levels of STRs and genes related to glycolipid metabolism were determined by real-time quantitative PCR and western blot. The present study revealed that APS alleviated the symptoms of T2DM rats, improved HOMA-IR and promoted insulin secretion. Gene expression analysis found that APS significantly increased the expressions of signaling molecules in STRs pathways, including taste receptor family 1 member 2 (T1R2), α-gustducin (Gα) and transient receptor potential cation channel subfamily member 5 (TRPM5), and reversed the expressions of genes related to glucolipid metabolism, including glucose transporters 2 and 4 (GLUT2 and GLUT4), pyruvate carboxylase (PC), fatty acid synthase (FAS) and acetyl-CoA carboxylase (ACC) in the liver of T2DM rats. However, APS had no influences on the expressions of genes, including glycogen synthase kinase-3 beta (GSK-3β), pyruvate kinase (PK) and phosphoenolpyruvate carboxykinase (PEPCK) in the liver of T2DM rats. These results suggested that the physiological roles of STRs in the liver were involved with glucose transport and metabolism. APS alleviated T2DM rats by activating the STRs pathway, and promoted glucose transport and lipogenesis.
Lysine acetylation of Escherichia coli lactate dehydrogenase regulates enzyme activity and lactate synthesis

As an evolutionarily conserved posttranslational modification, protein lysine acetylation plays important roles in many physiological and metabolic processes. However, there are few reports about the applications of lysine acetylation in metabolic regulations. Lactate is a main byproduct in microbial fermentation, and itself also an important bulk chemical with considerable commercial values in many fields. Lactate dehydrogenase (LdhA) is the key enzyme catalyzing lactate synthesis from pyruvate. Here, we reported that Escherichia coli LdhA can be acetylated and the acetylated lysine sites were identified by mass spectrometry. The effects and regulatory mechanisms of acetylated sites on LdhA activity were characterized. Finally, lysine acetylation was successfully used to regulate the lactate synthesis. LdhA (K9R) mutant overexpressed strain improved the lactate titer and glucose conversion efficiency by 1.74 folds than that of wild-type LdhA overexpressed strain. LdhA (K154Q-K248Q) mutant can inhibit lactate accumulation and improve 3HP production. Our study established a paradigm for lysine acetylation in lactate synthesis regulation and suggested that lysine acetylation may be a promising strategy to improve the target production and conversion efficiency in microbial synthesis. The application of lysine acetylation in regulating lactate synthesis also provides a reference for the treatment of lactate-related diseases.
Real-Time Target Detection Method Based on Lightweight Convolutional Neural Network

The continuous development of deep learning improves target detection technology day by day. The current research focuses on improving the accuracy of target detection technology, resulting in the target detection model being too large. The number of parameters and detection speed of the target detection model are very important for the practical application of target detection technology in embedded systems. This article proposed a real-time target detection method based on a lightweight convolutional neural network to reduce the number of model parameters and improve the detection speed. In this article, the depthwise separable residual module is constructed by combining depthwise separable convolution and non–bottleneck-free residual module, and the depthwise separable residual module and depthwise separable convolution structure are used to replace the VGG backbone network in the SSD network for feature extraction of the target detection model to reduce parameter quantity and improve detection speed. At the same time, the convolution kernels of 1 × 3 and 3 × 1 are used to replace the standard convolution of 3 × 3 by adding the convolution kernels of 1 × 3 and 3 × 1, respectively, to obtain multiple detection feature graphs corresponding to SSD, and the real-time target detection model based on a lightweight convolutional neural network is established by integrating the information of multiple detection feature graphs. This article used the self-built target detection dataset in complex scenes for comparative experiments; the experimental results verify the effectiveness and superiority of the proposed method. The model is tested on video to verify the real-time performance of the model, and the model is deployed on the Android platform to verify the scalability of the model.
Characterization of Nasco grape pomace-loaded nutriosomes and their neuroprotective effects in the MPTP mouse model of Parkinson’s disease

Grape pomaces have recently received great attention for their richness in polyphenols, compounds known to exert anti-inflammatory and antioxidant effects. These pomaces, however, have low brain bioavailability when administered orally due to their extensive degradation in the gastrointestinal tract. To overcome this problem, Nasco pomace extract was incorporated into a novel nanovesicle system called nutriosomes, composed of phospholipids (S75) and water-soluble maltodextrin (Nutriose® FM06). Nutriosomes were small, homogeneously dispersed, had negative zeta potential, and were biocompatible with intestinal epithelial cells (Caco-2). Nasco pomace extract resulted rich in antioxidant polyphenols (gallic acid, catechin, epicatechin, procyanidin B2, and quercetin). To investigate the neuroprotective effect of Nasco pomace in the subacute 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) mouse model of Parkinson’s disease (PD), Nasco nutriosomes or Nasco suspension was administered intragastrically and their neuroprotective effects were evaluated. Degeneration of nigro-striatal dopaminergic neurons induced by subacute MPTP treatment, the pathological hallmark of PD, was assessed through immunohistochemical evaluation of tyrosine hydroxylase (TH) in the caudate-putamen (CPu) and substantia nigra pars compacta (SNc), and the dopamine transporter (DAT) in CPu. Immunohistochemical analysis revealed that Nasco nutriosomes significantly prevented the reduction in TH- and DAT-positive fibres in CPu, and the number of TH-positive cells in SNc following subacute MPTP treatment, while Nasco suspension counteracted MPTP toxicity exclusively in SNc. Overall, these results highlight the therapeutic effects of Nasco pomace extract when administered in a nutriosome formulation in the subacute MPTP mouse model of PD and validate the effectiveness of the nutriosome preparation over suspension as an innovative nano-drug delivery system for in vivo administration.
Predicting high-frequency nutrient dynamics in the Danube River with surrogate models using sensors and Random Forest

Nutrient dynamics play an essential role in aquatic ecosystems. Despite advances in sensor technology, nutrient concentrations are difficult and expensive to monitor in-situ and in real-time. Emerging data-driven methods may provide surrogate measures for nutrient concentrations. In this work, we use 4-years of water quality data with high-frequency (15-min) intervals acquired at 2 automatic stations in the German Danube River to train data-driven algorithms and build surrogate measures for nitrate (NO3--N), ammonium (NH4+-N), and orthophosphate (PO43--P). Pre-processing of the data included removing outliers and filling missing values by linear interpolation. Multiple Linear Regression (MLR) and Random Forest (RF) are trained, cross-validated, and tested using dissolved oxygen (DO), temperature (Temp), conductivity (EC), pH, discharge rate (Q), and chlorophyll-a (Chl-a) as input futures. Additionally, we used time-series data to develop cyclical features to test improvements in the underlying relationship between data. This work presents a thorough description of the modeling workflow, including intermediate steps for feature engineering, feature selection, and hyperparameter optimization. In total, 12 surrogate models (2 algorithms * 3 constituents * 2 stations) are compared with R2 and RMSE as error metrics. The results show that RF outperforms MLR when adding at least three predictors for all the surrogate models. The MLR models give R2-values for NO3--N 0.67 and 0.89, NH4+-N 0.39 and 0.40, PO43--P 0.34 and 0.54 of Pfelling station and Jochenstein station, respectively. RF models produce accurate predictions and low error performances for all the targets NO3--N (R2 = 0.99 and 0.99), NH4+-N (R2 = 0.98 and 0.99), PO43--P (R2 = 0.96 and 0.96). The percentage improvement of RMSE for RF compared to MLR in prediction nutrients ranges from 73 to 92%. This work demonstrates the usefulness of surrogate models using the RF algorithm when reproducing nutrient dynamics and serving as soft sensors for monitoring nutrient concentrations.