Miracle-dz/UniFAR-FTUs huggingface dataset:
A neuron-MOS neural network using self-learning-compatible synapse circuits

A circuit technology for self-learning neural network hardware has been developed using a high-functionality device called Neuron MOS Transistor (/spl upsi/MOS) as a key circuit element. A /spl upsi/MOS can perform weighted summation of multiple input signals and thresholding all at a single transistor level based on the charge sharing among multiple capacitors. An electronic synapse cell has been constructed with six transistors by merging a floating-gate EEPROM memory cell into a new-concept /spl upsi/MOS differential-source-follower circuitry. The synapse can represent both positive (excitatory) and negative (inhibitory) weights under single V/sub DD/ power supply and is free from standby power dissipation. An excellent linearity in the weight updating characteristics of the synapse memory has been also established by employing a simple self-feedback regime in each cell circuitry, thus making it fully compatible to the on-chip self-learning architecture of /spl upsi/MOS neural networks. The basic operation of the synapse cell and a /spl upsi/MOS neural network using the synapse has been experimentally verified using test circuits fabricated by a double-polysilicon CMOS process. >
Clinical significance of claudin-1 in gastric cancer : a meta-analysis

Current results have indicated an inconsistent association between claudin-1 expression and the gastric cancer (GC) classification type. The present meta-analysis was conducted to obtain credible conclusions about this relationship. A comprehensive electronic and manual search was performed for records published before December 2017 using the Cochrane Library, Embase, PubMed, and Chinese National Knowledge Infrastructure (CNKI). Conference abstracts were also manually screened. An odds ratio (OR) was presented with 95% confidence interval (CI) for all results. There were nine studies with 920 GC patients included. Claudin-1 expression was significantly associated with the well-to-moderate-differentiated GC cohort (OR: 0.27, 95% CI: 0.17-0.41, P < 0.001). However, no significant differences were detected in terms of gender, TNM staging, lymphoid node metastasis, or vascular invasion. According to subgroup analysis, expression of claudin-1 occurred more frequently in the intestinal type of GC in Western areas (OR: 0.32, 95% CI: 0.19-0.55, P < 0.001) and in Asia (OR: 0.50, 95% CI: 0.28-0.91, P=0.024). In conclusion, this meta-analysis expatiated that claudin-1 is a novel biomarker for differentiation of GC.
Treatment of intertrochanteric femur fractures in the elderly via bipolar hip arthroplasty or proximal femoral nail

Objective: There is a debate about the treatment of intertrochanteric femur fractures in the geriatric population. A proximal femoral nail (PFN), a sliding hip screw, and bipolar hip arthroplasty (BHA) are the most commonly used treatment modalities. The aim of this study was to compare the blood transfusion rate, duration of surgery, and clinical scores of elderly patients treated with cementless BHA and a PFN.
Woman BrownPerson BluePerson Boy Counterfactual Phrase Grounding : woman in brown Result N / A

Computer Vision applications often require a textual grounding module with precision, interpretability, and resilience to counterfactual inputs/queries. To achieve high grounding precision, current textual grounding methods heavily rely on large-scale training data with manual annotations at the pixel level. Such annotations are expensive to obtain and thus severely narrow the model’s scope of real-world applications. Moreover, most of these methods sacrifice interpretability, generalizability, and they neglect the importance of being resilient to counterfactual inputs. To address these issues, we propose a visual grounding system which is 1) end-to-end trainable in a weakly supervised fashion with only image-level annotations, and 2) counterfactually resilient owing to the modular design. Specifically, we decompose textual descriptions into three levels: entity, semantic attribute, color information, and perform compositional grounding progressively. We validate our model through a series of experiments and demonstrate its improvement over the state-of-the-art methods. In particular, our model’s performance not only surpasses other weakly/un-supervised methods and even approaches the strongly supervised ones, but also is interpretable for decision making and performs much better in face of counterfactual classes than all the others.
Replacement of soybean meal by kased-kok meal ( Neptunia javanica Miq . ) in the diet on gas production and ruminal degradability by using in vitro gas technique

The aim of this study was to investigate the effect of replacement of soybean meal (SBB) by kased-kok (Neptunia javanica Miq.) meal, (KSKM) in the diet on gas production and ruminal degradability by using in vitro gas technique. The experimental design was a completely randomized design (CRD) and the dietary treatments were replacement of SBM by KSKM at 30, 60 and 100%, respectively with 0.5 g of roughage and concentrate ratio at 40:60.The gas production was recorded at 0, 1, 2, 4, 6, 8, 12, 18, 24, 48 and 72 h of incubation and was used for calculation of gas kinetics. The results revealed that gas kinetics and cumulative gas production were not significantly different among treatments (P>0.05). The in vitro degradability of DM, OM and true digestibility in treatment that replacement SBM with KSKM at 30 and 60% were not different with SMB group. However, increased level of replacement to 100%, the in vitro degradability and true digestibility were reduced. Microbial biomass was highest with KSKM replacement at 30% (19.6 mg). Moreover, NH3-N concentrations were quadratically increased when increasing levels of KSKM in the diet and were highest with KSKM replacement at 30% (25.6 mg/ dL). Based on this study, it could be concluded that replacement of SBM by KSKM at 30% in the diets could improve in vitro gas production,gas kinetics, ruminal degradability, microbial mass and NH3-N concentration.
Practical Bayesian Neural Networks via Adaptive Subgradient Optimization Methods

We introduce a novel framework for the estimation of the posterior distribution over the weights of a neural network, based on a new probabilistic interpretation of adaptive subgradient algorithms such as A DA G RAD and A DAM . We demonstrate the effectiveness of our Bayesian A DAM method, B ADAM , by experimentally showing that the learnt uncertainties correctly relate to the weights’ predictive capabilities by weight pruning. We also demonstrate the quality of the derived uncertainty measures by comparing the performance of B ADAM to standard methods in a Thompson sampling setting for multi-armed bandits, where good uncertainty measures are required for an agent to balance exploration and exploitation
Application of the Data Distribution Service for Implementing OSA-CBM Standard

As unmanned systems become standard equipment, the ability to monitor and manage system health is not just an enabling technology, but is required in order to meet platform availability and supportability goals. Its unique requirements can affect the selection of hardware, the strategy for collecting and processing data, and the integration of healthrelated information with other subsystems. The Open System Architecture for Condition Based Maintenance (OSA-CBM) is a standard aimed to reduce the development and integration cost of Integrated Vehicle Health Management (IVHM) systems and to achieve a higher level of performance that includes totally integrated diagnostics and prognostic capabilities. However, despite the well-known advantages of the approach, there have been a few implementation examples of the standard. In this paper, we discuss the applicability of the data centric publish/subscribe model for the design and development of OSA-CBM systems. Computational power and bandwidth are always the key constraints in IVHM application deployments. The publish/subscribe software model is used to form a fundamental structure of the OSA-CBM software, both module’s internal components and inter-module (middleware) communications. The primary benefit of publish/subscribe interaction style is that it abstracts the message transport from the software components or modules and allows them to be uncoupled. The module can add/change/remove internal components from the internal publish/subscribe data domain, called blackboard, and subscribe to local add/change/remove notification. Module blackboards are to assure scalability and reconfigurable. The resulting OSA-CBM design provides software enabling capability to distribute/reconfigure IVHM data processing algorithms across the hardware platforms to meet the required computation and bandwidth constraints. Moreover, another system potential would be a rapid deployment capability, which a generic OSA-CBM module can be programmed via a process description script change. This frees developers to concentrate on the domain-specific issues of their application. Finally, an example application is presented based on a Machine Fault Simulator Gearbox to illustrate the described aspects.
Number : WUCSE-2004-14 2004-03-31 High Performance Packet Classification

In this proposal, we seek to develop methods for packet classification that can deliver high performance (e.g. wire speed processing at 10 Gb/s) while being reasonably cost-effective (e.g. memory-efficient and having low hardware complexity). In particular, we discuss a new approach involving extended TCAMs. This new approach eliminates the problems that preclude TCAMs from being considered viable solutions to the packet classification problem. High Performance Packet Classification Edward W. Spitznagel ews1@cse.wustl. edu Washington University St. Louis, MO 63130-4899
Detection of Splicing in Digital Images Based on Illuminant Features

Nowadays digital images are widely used in our day to day life. Image forgery is the process of manipulation of an image to hide some meaningful information of the image. Today digital image forgery become easy due to the availiability of powerful computers, advanced photo editing softwares so that even ordinary users have more access to the digital doctoring tools than even before. The driving forces for the detection of forgered images are the need of authenticity and to maintain the integrity of the image. In this paper an automatic machine learning method for detecting the forgery due to image composition or splicing is considered. Here GLCM features and edge based features are extracted from the illuminant map of an image and 'then provide to a machine learning approach for obtaining the result. Here we use kNN classifier for classifying the image as whether it is original or forgered.
Stock Market Anomalies across Various Stock Market Indices of Pakistan

This investigation implies the impacts of stock market anomalies on the various stock market indices. The two stock market anomalies that have been focused on include the Day of the Week effect, which has been tested on KMI 30, KSE 100, BR 30, KSE All Share and KSE 30 indices for one and a half year duration; whereas, the Month of the Year anomaly, which has been tested on KSE 100, KSE 30 and BR 30 indices for six-year duration, both phases ending at February 2013. The two anomalies of focus have been investigated to analyze the returns of stock indices through the use of dummy variables, OLS, Correlation and Descriptive Statistics. The daily findings reveal that there exists Friday effect for KMI 30 index; Tuesday, Wednesday and Friday effects for both KSE 100 and KSE All Share indices. Similarly, our monthly findings reveal that there exists January, March and April anomalies for the three sample indices but they do not apply to the complete monthly sample period. Keyword: Efficient Market Hypothesis, Stock Exchanges, “Day-of-the-Week” Effect, “Month of the Year” Effect, Dummy Variables and OLS
An Error Diffusion Method for Color Reproduction in Ink Jet Printing

This paper describes a method of color rendition ba on the extension of bilevel error diffusion technique fr one component per pixel (originally gray image), to arbitrary set of colors, with an arbitrary number of co components per pixel. For each color pixel in the original image, t method selects that color from the output set, that m mizes the error of color rendition in a local array arou the current investigated pixel. A decision function w introduced in order to investigate the error between original and the error diffusion represented picture, all color components. For each pixel, the error of color rendition resu as the sum over all pixel errors in the local arr weighted according to the geometrical distance to current investigated point. The paper describes also the influence of the sh and size of local array as well as the weight mask u to compute the color error. Different weight masks used for different color components of the pixel in or to reduce the moiré effect on the printed colors. T optimal local array parameters (size, shape and we mask) are derived experimentally and results are c pared in terms of color accuracy and computational formance. Additionally, few color spaces are investiga in order to find perceptually the better color distance error computation.
A Write-friendly Hashing Scheme for Non-volatile Memory Systems

Emerging non-volatile memory technologies (NVMs) have been considered as promising candidates for replacing DRAM and SRAM, due to their advantages of high density, high scalability, and requiring near-zero standby power, while suffering from the limited endurance and asymmetric properties of reads and writes. The significant changes of low-level memory devices cause nontrivial challenges to high-level in-memory and in-cache data structure design due to overlooking the NVM device properties. In this paper, we study an important and common data structure, hash table, which is ubiquitous and widely used to construct the index and lookup table in main memory and caches. Based on the observations that existing hashing schemes cause many extra writes to NVMs, we propose a cost-efficient write-friendly hashing scheme, called path hashing, which incurs no extra writes to NVMs while delivers high performance. The basic idea of path hashing is to leverage a novel hash-collision resolution method, i.e., position sharing, which meets the needs of insertion and deletion requests without extra writes to NVMs. By further exploiting double-path hashing and path shortening techniques, path hashing delivers high performance of hash tables in terms of space utilization and request latency. We have implemented path hashing and used a gem5 full system simulator with NVMain to evaluate its performance in the context of NVMs. Extensive experimental results demonstrate that path hashing incurs no extra writes to NVMs, and achieves up to 95% space utilization ratio as well as low request latency, compared with existing state-of-the-art hashing schemes.
A probabilistic fuzzy approach to modeling stock price behavior

In this thesis, a probabilistic fuzzy model that produces a conditional probability for a stock return given a lagged return, is fitted on historical stock returns. The model consists of three rules: one for “low”, one for “medium”, and one for “high” lagged returns. For each fuzzy class of lagged returns, a conditional probability distribution is approximated using a mixture model. The three rules are interpolated using a fuzzy reasoning scheme, similar to that of TakagiSugeno fuzzy inference systems. Using the resulting model, potential stock price paths can be simulated. From these price paths we can deduce an option price that is valid for risk-neutral investors that are not able to benefit from arbitrage opportunities.
Error‐corrected output coding‐based class decomposition approach for remote sensing classification

This paper discusses the application of an error‐corrected output coding (ECOC)‐based class decomposition approach for land cover classification. Exhaustive and random techniques to generate error‐correcting output codes were used. A univariate decision tree and a backpropagation neural network were used as base classifiers. Results from the ECOC‐based class decomposition approach are compared with the multiclass classification approach. Results suggest that an ECOC‐based class decomposition approach performs well with both decision tree and neural network classifiers in comparison with a multiclass approach and results are significantly better. Results using an ECOC‐based class decomposition approach indicate a significant improvement in classification accuracy with noisy as well as small training data sets. A study with a random technique‐based class decomposition approach suggests that the size of codes used to decompose the multiclass problem affects the classification accuracy but no significant improvement is achieved beyond a code length of 21 using both classifiers, except increased computational cost. A boosting and ECOC‐based class decomposition approach perform equally well as a univariate decision tree as base classifier using a large training data set. Further, the performance of boosting degrades with increases in the amount of noise in the training data set in comparison with the ECOC‐based approach, as well as with smaller training data sets.
Interlibrary Loan Patron Satisfaction at the Wichita State University Libraries

Abstract In 2004, the Wichita State University (WSU) interlibrary loan services completed a study of currently available interlibrary loan software. Based upon the results of the study, the library chose the Inter-library Loan Internet Accessible database (ILLiad). After implementation, individual training was offered to patrons. In 2006, staff decided to survey patrons' satisfaction. The general purpose of the survey was to determine whether users had accepted the new system, to measure satisfaction with turnaround time, delivery method and the print quality and usefulness of the received material. This article contains a brief description of interlibrary loan operations at WSU, a review of interlibrary loan satisfaction literature and a discussion of the design, implementation, results and analysis of the survey.
Dynamic Regulation of miRNA Expression by Functionally Enhanced Placental Mesenchymal Stem Cells PromotesHepatic Regeneration in a Rat Model with Bile Duct Ligation

Placenta-derived mesenchymal stem cells (PD-MSCs) were highlighted as therapeutic sources in several degenerative diseases. Recently, microRNAs (miRNAs)were found to mediate one of the therapeutic mechanisms of PD-MSCs in regenerative medicine. To enhance the therapeutic effects of PD-MSCs, we established functionally enhanced PD-MSCs with phosphatase of regenerating liver-1 overexpression (PRL-1(+)). However, the profile and functions of miRNAs induced by PRL-1(+) PD-MSCs in a rat model with hepatic failure prepared by bile duct ligation (BDL) remained unclear. Hence, the objectives of the present study were to analyze the expression of miRNAs and investigate their therapeutic mechanisms for hepatic regeneration via PRL-1(+) in a rat model with BDL. We selected candidate miRNAs based on microarray analysis. Under hypoxic conditions, compared with migrated naïve PD-MSCs, migrated PRL-1(+) PD-MSCs showed improved integrin-dependent migration abilitythrough Ras homolog (RHO) family-targeted miRNA expression (e.g., hsa-miR-30a-5p, 340-5p, and 146a-3p). Moreover, rno-miR-30a-5p and 340-5p regulated engraftment into injured rat liver by transplantedPRL-1(+) PD-MSCs through the integrin family. Additionally, an increase inplatelet-derived growth factor receptor A (PDGFRA) by suppressing rno-miR-27a-3p improved vascular structure in rat liver tissues after PRL-1(+) PD-MSC transplantation. Furthermore, decreased rno-miR-122-5p was significantly correlated with increased proliferation of hepatocytes in liver tissues by PRL-1(+) PD-MSCs byactivating the interleukin-6 (IL-6) signaling pathway through the repression of rno-miR-21-5p. Taken together, these findings improve the understandingof therapeutic mechanisms based on miRNA-mediated stem-cell therapy in liver diseases.
Linguistic Annotation

TEI-compliant documents are broken into 2 parts: 1. Header = information about the document I File description (<fileDesc>): bibliographic information I Encoding description (<encodingDesc>): relationship to the source I Text profile (<profileDesc>): non-bibliographic information (setting of the text, languages used, etc.) I Revision history (<revisionDesc>): changes made 2. Body = the original text itself
Trophic Lesions of the Lower Limbs As Exponents of Vascular Complications in Essential Thrombocythemia

Background. The etiology of lower limb ulcer formation is highly diversified. Venous and/or arterial insufficiency associated with essential thrombocythemia is one of the possible causes. The available literature offers scant data on the coexistence of essential thrombocythemia and necrotic lower limb lesions resulting from arterial and/or venous perfusion disturbances. Objectives. The aim of the study was to conduct a retrospective analysis of patients with idiopathic thrombocythemia treated for trophic lesions of the lower limbs at the Wrocław Medical University Angiology Department between 2002 and 2010. Material and Methods. Between 2002 and 2010 only 11 of the patients who were treated at the Wroclaw Medical University Angiology Department for trophic limbs lesions also had thrombocythemia. This group consisted of 6 women and 5 men aged 27–85 years. The case histories of these patients were submitted to retrospective analysis. Results. Trophic lesions coexisted with essential thrombocythemia in only 11 patients (aged 27–85) during this period. Critical ischemia of the toes with the presence of necrotic lesions was found in six study subjects, while ulcers located on the lateral side of the leg were observed in two patients. A futher three patients presented simultaneous foot and lateral calf ischemic lesions. Conclusions. Despite advances in vascular diagnostics, the pathomechanism of calf ulcers has proved difficult to explain. Although idiopathic thrombocythemia is not common cause of trophic lesions of the lower limbs, it should be considered in the differential diagnosis. At the same time, patients with idiopathic thrombocythemia should always be monitored for signs of disturbances in lower extremity perfusion and for coexisting risk factors for cardiovascular complications (Adv Clin Exp Med 2011, 20, 4, 455–460).
Impact of Functional Visceral and Somatic Pain/ Stress Syndromes on Cingulate Cortex

Chapter contents Goals and Rationale of This Chapter 500 Irritable Bowel Syndrome 501 Neuroanatomy of Functional Pain: Visceral Syndromes 502 Fibromyalgia 503 Neuroanatomy of Functional Pain: FM 503 Non-specifi c Low-Back Pain 503 Neuroanatomy of Functional Pain: NSLBP 504 Overlap of Functional Pain and Stress 505 Depression Infl uences Cingulate Pain Processing 506 Cingulate Inactivation during Depression 507 Animal Models and Links between Pain and Stress Syndromes 508 Cingulate Links to Visceral and Somatic Pain and Stress Syndromes 509 References 509