Miracle-dz/UniFAR-FTUs huggingface dataset:
In situ hybridization analysis of myelin gene transcripts in developing mouse spinal cord

We analyzed the location and abundance of transcripts for the 4 CNS myelin protein genes, myelin basic protein (MBP), proteolipid protein (PLP), myelin-associated glycoprotein (MAG), and 2′,3′-cyclic nucleotide phosphohydrolase (CNP), in the mouse cervical spinal cord from the time of rapid myelination until adulthood (8–45 d). In the white matter, maximal levels of transcripts were found for each of the myelin genes at the peak of myelination (8 d). Total MBP and PLP mRNAs stayed high until 20 d and showed a minor decrease thereafter. In contrast, MAG and the MBP exon 2 containing transcripts (coding for the 21.5 and 17 kDa MBP isoforms) decreased sharply between 8 and 20 d, suggesting that high levels of these transcripts are needed primarily during the initiation of myelination. CNP transcripts were less abundant, maintained high expression until 20 d, and then decreased sharply. PLP, MAG, and CNP transcripts were clustered in the oligodendrocyte cell body, while MBP mRNAs were scattered throughout the cell body and processes. In contrast to the white matter, all these myelin specific transcripts in the gray matter showed a marked increase from 8 to 20 d, as did the number of oligodendrocytes identified by CNP immunostaining. MAG transcripts were found in white matter and in satellite and other oligodendrocytes of the gray matter but not in neurons identified by their expression of neurofilament transcripts. The results of our quantitative in situ hybridization study are in good agreement with those of previous molecular studies and provide new information on the cellular and topographic distribution of myelin- specific mRNAs during myelination.
Parallel feature generation based on maximizing normalized acoustic likelihood

Combining information from parallel feature streams generally improves speech recognition accuracy. While many studies have attempted to determine the stage of the recognition system that provides best combination performance and the specific nature of how features are combined, relatively little attention has been paid to the design or selection of parallel feature sets when used in combination. In this paper we propose a new parallel feature generation algorithm based on the criterion of maximizing the normalized acoustic likelihood of the features after they are combined, which is closely related to the recognition accuracy obtained using the combination of these features. We use a gradient ascent procedure to manipulate the values of a set of transformation matrices through which individual features are passed before they are combined in a fashion that maximizes the normalized acoustic likelihood term after the features are combined. The function that combine the parallel features together is an intrinsic part of the optimization process. The use of the optimal linear transformation provides a relative decrease of 12.7 percent Word Error Rate on the DARPA Resource Management task.
A Meta-Heuristic Regression-Based Feature Selection for Predictive Analytics

A high-dimensional feature selection having a very large number of features with an optimal feature subset is an NP-complete problem. Because conventional optimization techniques are unable to tackle large-scale feature selection problems, meta-heuristic algorithms are widely used. In this paper, we propose a particle swarm optimization technique while utilizing regression techniques for feature selection. We then use the selected features to classify the data. Classification accuracy is used as a criterion to evaluate classifier performance, and classification is accomplished through the use of k-nearest neighbour (KNN) and Bayesian techniques. Various high dimensional data sets are used to evaluate the usefulness of the proposed approach. Results show that our approach gives better results when compared with other conventional feature selection algorithms.
A Survey on Intrusion Detection System using Machine Learning and Deep Learning

As we know internet of Things (IoT) is one of the fastest growing paradigm which is composed of Internet and different physical devices with different domains or the smart applications like home automation, business automation applications, health and environmental monitoring applications. The dependency on IOT devices is increasing day by day with our daily activities, which leads to most important challenge for security. Since having a better monitoring system for better security is a need. From more than two decades the concept or the frame work called IDS (Intrusion detection system) is playing important role for detecting the attacks in the network. Since the network attacks are not fixed in nature, a new type of attacks are happening on the network applications. There are many traditional IDS techniques are available but they are complex to apply. Since machine learning is one of the important area which is achieving good results in many applications. In this paper we study about the different machine learning techniques used till now and the methodology for the attack detection and the validation strategy. We will also discuss about the performance metrics.
Survival of Korean Adult Cancer Patients by Stage at Diagnosis, 2006-2010: National Cancer Registry Study

Purpose Although the cancer stage at diagnosis is the most important prognostic factor for patients' survival, there are few population-based estimates of stage-specific survival outcome, especially in Asian countries. Our study aims to estimate stage-specific survival for Korean patients. Materials and Methods We analyzed the Korea National Cancer Incidence Database data on 626,506 adult patients aged ≥ 20 years, who were diagnosed between 2006 and 2010 with stomach, colorectal, liver, lung, breast, cervix, prostate, and thyroid cancers. Patients were followed up to December 2011, and the 5-year relative survival rates (RSRs) were calculated for gender and age group by Surveillance, Epidemiology, and End Results (SEER) stage at diagnosis. Results The 5-year RSRs for all localized-stage cancers, except for lung and liver, exceeded 90% with that for thyroid cancer being the highest at 100.4%. These values for distant stage liver, lung, and stomach cancers were very dismal at 2.5%, 4.8%, and 5.5%, respectively, while it was 69.1% for thyroid cancer, and was in the range of 18.3-36.4% for colorectal, cervix, breast and prostate cancers. Overall, the 5-year RSRs for all cancer types decreased with aging across all the disease stages with exception of prostate cancer, which suggests biologic difference in these cancer types in a young age group. When compared with US SEER data, Korean patients had better stage-specific survival rates for stomach, colorectal, liver, and cervical cancers. Conclusion Korean cancer patients showed relatively favorable stage distribution and 5-year RSRs, which suggests potential contribution of the national cancer screening program.
Education and occupational social class: which is the more important indicator of mortality risk?

STUDY OBJECTIVES: In the UK, studies of socioeconomic differentials in mortality have generally relied upon occupational social class as the index of socioeconomic position, while in the US, measures based upon education have been widely used. These two measures have different characteristics; for example, social class can change throughout adult life, while education is unlikely to alter after early adulthood. Therefore different interpretations can be given to the mortality differentials that are seen. The objective of this analysis is to demonstrate the profile of mortality differentials, and the factors underlying these differentials, which are associated with the two socioeconomic measures. DESIGN: Prospective observational study. SETTING: 27 work places in the west of Scotland. PARTICIPANTS: 5749 men aged 35-64 who completed questionnaires and were examined between 1970 and 1973. FINDINGS: At baseline, similar gradients between socioeconomic position and blood pressure, height, lung function, and smoking behaviour were seen, regardless of whether the education or social class measure was used. Manual social class and early termination of full time education were associated with higher blood pressure, shorter height, poorer lung function, and a higher prevalence of smoking. Within education strata, the graded association between smoking and social class remains strong, whereas within social class groups the relation between education and smoking is attenuated. Over 21 years of follow up, 1639 of the men died. Mortality from all causes and from three broad cause of death groups (cardiovascular disease, malignant disease, and other causes) showed similar associations with social class and education. For all cause of death groups, men in manual social classes and men who terminated full time education at an early age had higher death rates. Cardiovascular disease was the cause of death group most strongly associated with education, while the non-cardiovascular non-cancer category was the cause of death group most strongly associated with adulthood social class. The graded association between social class and all cause mortality remains strong and significant within education strata, whereas within social class strata the relation between education and mortality is less clear. CONCLUSIONS: As a single indicator of socioeconomic position occupational social class in adulthood is a better discriminator of socioeconomic differentials in mortality and smoking behaviour than is education. This argues against interpretations that see cultural--rather than material--resources as being the key determinants of socioeconomic differentials in health. The stronger association of education with death from cardiovascular causes than with other causes of death may reflect the function of education as an index of socioeconomic circumstances in early life, which appear to have a particular influence on the risk of cardiovascular disease.
IMPORTANCE RESAMPLING FOR BOOTSTRAP CONFIDENCE REGIONS

In this article, we obtain an importance resampling formula to reduce the amount of resampling necessary for the construction of bootstrap con dence regions. In the one-dimensional case, the formula reduces to that of Jones (1988) and Do & Hall (1991). However, the methods employed by previous authors are not tamed for direct generalization to multi-dimensional parameters. Therefore no formula is available for bootstrap con dence regions in the literature. Our method, which is closely related to the large deviation tilting, allows a relatively easy treatment of the multi-dimensional case. The method also reveals a phenomenon that happens only in the multi-dimensional case. That is, the optimally tilted distribution is a mixture of exponentially tilted distributions, and the mixture components depend on the shape of the con dence region. We also provide a general account of the importance resampling in relation to the large deviation tilting. E ciency properties of the simulation scheme using the proposed formula is established together with numerical evidence. Some key words: Bootstrap; Con dence region; Importance resampling; Large deviation; Uniform resampling Research partially supported by the National Science Council of ROC. Visiting National Taiwan University and Academia Sinica, research partially supported by Hong Kong Research Grant Council.
A CAM-based Information Detection Hardware System for fast exact pattern matching

A CAM-based Information Detection Hardware System for fast exact pattern matching is implemented on a hardware system with FPGA and ASIC. The system has a simple structure, does not employ any Central Processor Unit (CPU) as well as complicated algorithms. We take advantage of Content Addressable Memory (CAM) which has an ability of parallel multi-match mode for designing the system. The system is applied to fast pattern matching with various required search patterns without using any search principles. In this paper, the authors present the system for exact pattern matching on 2-D data.
Bacterial cellulose: Application as drug delivery system

Bacterial cellulose (BC) is a very interesting biopolymers to biomedical application, including drug delivery system, due to unique characteristics as such as high degree purity and of porosity, relative high permeability to liquid and gases, high holding water capacity, tensile strength and randomly oriented three-dimensional fiber network. Several authors described the use of BC membranes or copolymers to use as drug delivery system. The aim of the present mini-review was to show the wide and vantages application of the BC and its copolymers for use as controlled drug delivery system.
Coding Ants: Using Ant Colony Optimization to Accelerate CT Reconstruction

–There is no one size fits all solution when it comes to CT reconstruction. Many different CT reconstruction algorithms and implementations have been devised in an attempt to solve the problem of producing an image under a specific set of constraints. One optimal CT reconstruction implementation can look very different from another optimal implementation; depending on the data, quality, and time constraints. In this paper, we present a framework that is able to dynamically create and compile new implementations that optimize the multiple objectives contained in CT reconstruction. We then show the results of this framework when applied to a GPU accelerated version of the FDK back-projection algorithm.
The effect of fumonisins producing Fusarium verticillioides on the microbiota in pig caecum

Fumonisin-producing fungal species,Fusarium verticillioides, culture was mixed in the diets of 6 piglets for 9 days (Fumonisin B1[FB1] intake of 17 mg/kg) to investigate whether there is any potential alteration in the caecal bacterial communities between the experimental (withF. verticillioides) and control groups (withoutF. verticillioides). Plate count agar culturing technique was applied to measure the amount of aerobic and anaerobic bacteria,Escherichia coli, coliforms,Lactobacillusspp. andClostridium perfringens. A significant difference was observed between the control and experimental group only in the case of aerobic bacteria on Day 4, 8.60 ± 0.22 compared to 8.06 ± 0.20 (P< 0.05), respectively. Quantitative polymerase chain reaction (qPCR) was performed to estimate the DNA copy number of total bacteria,BacteroidesandPrevotellaspp. ,Clostridiumspp. ,E. coli,Enterobacteriales,FirmicutesandLactobacillusspp. Significant differences were observed between the control and experimental group regarding total bacteria on Day 2 and Day 6,Firmicuteson Day 2 andE. coliandEnterobacterialeson Day 4. Regarding the entire feeding time, no significant difference between the two groups was found in all species of investigated bacteria by the culturing technique and qPCR after an 8-day exposure. The present research contributes to the understanding of how microbiota responds to the FB1load.
What We Have Learned 1.1 It Actually Works Discussion 3

During the 15 years since the Bank of Canada embarked on its current course, we have learned a great deal about how to conduct a policy of inflation targeting. For the most part, the experience has been a happy one and its lessons have been encouraging. Many of the papers presented at this conference rightly emphasize the progress we have made in our understanding of the economy and in our ability to control inflation. Yet it is certainly too early for any central bank to declare victory over inflation, or for any economist to claim that we now understand the mysteries of monetary dynamics. A number of critical issues for determining the longrun viability of inflation targeting remain unresolved and will probably require a lot of research—and possibly a certain amount of adverse experience—before we can claim to understand them. Accordingly, my remarks are intended to outline what I perceive as the most important lessons that we have learned about inflation targeting, as well as those that remain to be learned.
Head Position and Cerebral Blood Flow Velocity in Acute Ischemic Stroke: A Systematic Review and Meta-Analysis

Background: Patients with acute ischemic stroke (AIS) have impaired vasomotor reactivity, especially in the affected cerebral hemisphere, such that they may depend directly on systemic blood pressure to maintain perfusion to vulnerable ‘at risk' penumbral tissue. As the sitting up position may affect cerebral perfusion by decreasing cerebral blood flow (CBF) in salvageable tissue, positioning AIS patients with their head in a lying flat position could increase CBF through collateral circulation or gravitational force. We wished to quantify the effect of different head positions on mean flow velocity (MFV) by transcranial Doppler ultrasonography (TCD) in AIS patients to assess the potential for benefit (or harm) of head positioning in a clinical trial. Methods: We performed a systematic review and meta-analysis of observational studies with TCD to evaluate differences in cerebral MFV between the lying flat and sitting up head positions in AIS. For each study and each comparison, we obtained the mean value of changes in MFV and its variance. Results: A total of 303 studies were identified, but 298 were excluded for varying reasons; 4 papers met the inclusion criteria and 57 patients were included in the meta-analysis for calculation of the overall mean difference in MFV. We found a significant increase in MFV from a bed angle of 30 to 15° (4.6 cm/s, 95% confidence interval, CI, 2.9-6.2, p < 0.001) and from 30 to 0° (8.3 cm/s, 95% CI 5.3-11.3, p < 0.001) in the affected hemisphere but not on the normal side in AIS patients. Conclusions: In AIS patients, MFV increased significantly in the side affected by the stroke but not in the unaffected side when they were positioned in a lying flat head position at 0 or 15° compared to an upright head position at 30°. The clinical significance of these findings is now undergoing further randomized evaluation in the international multicenter Head Position in Acute Stroke Trial (HeadPoST).
Intracellular Localization and Functional Effects of P 21-Activated Kinase-1 ( Pak 1 ) in Cardiac Myocytes

We investigated intracellular localization and substrate specificity of P-activated kinase-1 (Pak1) in rat cardiac myocytes. Pak1 is a serine/threonine protein kinase that is activated by Rac1/Cdc42 and important in signaling of stress responses. Yet the localization and in vivo function of Pak1 in heart cells is poorly understood. Studies reported here indicate that Pak1 physically interacts with protein phosphatase 2a and localizes to the Z-disk, cell membrane, intercalated disc, and nuclear membrane of adult rat heart myocytes. We compared levels of phosphorylation of cardiac troponin I (cTnI) in control myocytes with phosphorylation of cTnI and myosin binding protein C (C-protein) in myocytes with increased Pak1 activity. The increase in activity was induced by infection of myocytes with a recombinant adenovirus (AdPak1) containing cDNA for a constitutively active Pak1. Control cells were infected with a virus (AdLacZ) containing LacZ. Basal levels of phosphorylation of cTnI and C-protein were relatively high in the myocytes infected with AdLacZ. However, phosphorylation of cTnI and C-protein in cells expressing constitutively active Pak1 was significantly reduced compared with those expressing LacZ. Measurement of Ca tension relations in single myocytes demonstrated that this reduction in phosphorylation of cTnI and C-protein was associated with the predicted increase in sensitivity to Ca . Our data provide evidence for a novel pathway of phosphatase regulation in cardiac myocytes. (Circ Res. 2004;94:194-200.)
Transparent Dual Memory Compression Architecture

The increasing memory requirements of big data applications have been driving the precipitous growth of memory capacity in server systems. To maximize the efficiency of external memory, HW-based memory compression techniques have been proposed to increase effective memory capacity. Although such memory compression techniques can improve the memory efficiency significantly, a critical trade-off exists in the HW-based compression techniques. As the memory blocks need to be decompressed as quickly as possible to serve cache misses, latency-optimized techniques apply compression at the cacheline granularity, achieving the decompression latency of less than a few cycles. However, such latency-optimized techniques can lose the potential high compression ratios of capacity-optimized techniques, which compress larger memory blocks with longer latency algorithms.Considering the fundamental trade-off in the memory compression, this paper proposes a transparent dual memory compression (DMC) architecture, which selectively uses two compression algorithms with distinct latency and compression characteristics. Exploiting the locality of memory accesses, the proposed architecture compresses less frequently accessed blocks with a capacity-optimized compression algorithm, while keeping recently accessed blocks compressed with a latency-optimized one. Furthermore, instead of relying on the support from the virtual memory system to locate compressed memory blocks, the study advocates a HW-based translation between the uncompressed address space and compressed physical space. This OS-transparent approach eliminates conflicts between compression efficiency and large page support adopted to reduce TLB misses. The proposed compression architecture is applied to the Hybrid Memory Cube (HMC) with a logic layer under the stacked DRAMs. The experimental results show that the proposed compression architecture provides 54% higher compression ratio than the state-of-the-art latency-optimized technique, with no performance degradation over the baseline system without compression.
Exclusive breastfeeding and its effect on growth of Malawian infants: results from a cross-sectional study

Abstract Background: For the optimal nutrition of children under 2 years of age, it is considered important that they be exclusively breastfed for the first 6 months before being given complementary food. Aims and Objectives: A cross-sectional nutritional baseline survey was undertaken in 2011 in the Kasungu and Mzimba Districts of Malawi to assess the nutritional status of children under 2 years of age and its determinants in order to prepare a nutrition education intervention programme. The intention of this study was to assess the nutritional status of infants aged 0–<6 months with regard to food intake. Methods: Interviews were conducted on randomly selected families with children under 2 years; anthropometric measurements were obtained from mothers and their children. Only infants between 0 and <6 months were selected for analysis (n = 196). An ANCOVA test was performed on age of the infant with mothers’ height and weight as covariates. Results: Prevalence of stunting (infants’ length-for-age Z-score (LAZ) <−2SD) was 39%, wasting (WLZ <−2SD) 2%, and underweight (WAZ <−2SD) 13%. Of the infants under 6 months, 43% were exclusively breastfed. Predominant breastfeeding and mixed breastfeeding were less common (21% and 36%, respectively). The ANCOVA confirmed the association between exclusive breastfeeding and LAZ and WAZ: exclusively breastfed infants had a higher mean (SE) LAZ (−1·13, 0·12) and WAZ (−0·41, 0·13) than infants not being exclusively breastfed (−1·59, 0·11, and −0·97, 0·11, respectively). There was no overall significant association between breastfeeding practice and WLZ. Conclusion: Exclusive breastfeeding of infants under 6 months is associated with higher mean LAZ and WAZ. Promotion of exclusive breastfeeding in low-income countries is important in preventing growth retardation.