Miracle-dz/UniFAR-FTUs huggingface dataset:
Low Power Low Noise Neural Amplifier with Adjustable Gain

This work describes a 0.5 μm CMOS implementation of a Folded Cascode OTA designed for minimum Input Referred Noise for non-implantable EEG SoC arrays. It is also described a small area PID feedback network using a high resistive pMOS pseudo-resistor and small integration capacitances for programmable gain control throughout parasitic insensitive nMOS switches. Simulation results show that it achieves about 2.2 μVrms of input referred noise for 6 μA of total current at ±1.8 V supply voltage. The circuit provides a NEF of 4.55 within a 1.96 kHz bandwidth and midband gain of 40.22 dB.
Cascading model uncertainty from medium range weather forecasts (10 days) through a rainfall-runoff model to flood inundation predictions within the European Flood Forecasting System (EFFS)

Abstract. The political pressure on the scientific community to provide medium to long term flood forecasts has increased in the light of recent flooding events in Europe. Such demands can be met by a system consisting of three different model components (weather forecast, rainfall-runoff forecast and flood inundation forecast) which are all liable to considerable uncertainty in the input, output and model parameters. Thus, an understanding of cascaded uncertainties is a necessary requirement to provide robust predictions. In this paper, 10-day ahead rainfall forecasts, consisting of one deterministic, one control and 50 ensemble forecasts, are fed into a rainfall-runoff model (LisFlood) for which parameter uncertainty is represented by six different parameter sets identified through a Generalised Likelihood Uncertainty Estimation (GLUE) analysis and functional hydrograph classification. The runoff of these 52 * 6 realisations form the input to a flood inundation model (LisFlood-FP) which acknowledges uncertainty by utilising ten different sets of roughness coefficients identified using the same GLUE methodology. Likelihood measures for each parameter set computed on historical data are used to give uncertain predictions of flow hydrographs as well as spatial inundation extent. This analysis demonstrates that a full uncertainty analysis of such an integrated system is limited mainly by computer power as well as by how well the rainfall predictions represent potential future conditions. However, these restrictions may be overcome or lessened in the future and this paper establishes a computationally feasible methodological approach to the uncertainty cascade problem.
Multimodal Function Optimization Based on Improved ABC Algorithm

In order to improve the searching speed and the quality of global optimal solution, we propose an improved algorithm based on Artificial Bee Colony(ABC) algorithm, which can search the space by stochastic optimization and dynamic regulation (named SRABC). Firstly, the improved algorithm can update the next location of ABC algorithm, which can perfect the correlation for the bee colony. Secondly, we used the dynamic regulation to search for fitness function by restraining the direction, the approach can improve local search ability effectively. By testing 5 multimodal functions, the simulation results show that the SRABC algorithm has significant improvements in convergence rate and precision rate of global optimal solution.
Efficient transfer of base changes from a vector to the rice genome by homologous recombination: involvement of heteroduplex formation and mismatch correction

Gene targeting refers to the alteration of a specific DNA sequence in an endogenous gene at its original locus in the genome by homologous recombination. Through a gene-targeting procedure with positive–negative selection, we previously reported the generation of fertile transgenic rice plants with a positive marker inserted into the Adh2 gene by using an Agrobacterium-mediated transformation vector containing the positive marker flanked by two 6-kb homologous segments for recombination. We describe here that base changes within the homologous segments in the vector could be efficiently transferred into the corresponding genomic sequences of rice recombinants. Interestingly, a few sequences from the host genome were flanked by the changed sequences derived from the vector in most of the recombinants. Because a single-stranded T-DNA molecule in Agrobacterium-mediated transformation is imported into the plant nucleus and becomes double-stranded, both single-stranded and double-stranded T-DNA intermediates can serve in gene-targeting processes. Several alternative models, including the occurrence of the mismatch correction of heteroduplex molecules formed between the genomic DNA and either a single-stranded or double-stranded T-DNA intermediate, are compared to explain the observation, and implications for the modification of endogenous genes for functional genomic analysis by gene targeting are discussed.
3D Path Planning Based on Elevation Model and Ant Colony Algorithm

A new 3D path planning algorithm of unmanned ground vehicle is proposed. First of all, an approach for the complex 3D unstructured scene of outdoor unmanned ground vehicle is structured by Elevation model which has traits of robustness and high-efficiency. Secondly, the Ant colony algorithm to search the best path is employed. Combined with the process costing and group intelligence of Ant colony algorithm, the model is built in 3D Elevation scene, from which an ends-meeting, obstacle-avoiding and minimal cost best path is given. Simulation statistics show the validity of the proposed which Based on Elevation model and Ant colony algorithm at complex 3D unstructured scene of outdoor unmanned ground vehicle.
Behavior-Based Malware Detection on Mobile Phone

Mobile malware is rapidly developing, but current anti-virus products in mobile devices still use the signature-based solutions, which usually need a large database and cannot detect malware variants. In this paper, we proposed a behavior-based malware detection system for Windows Mobile platform called WMMD (Windows Mobile Malware Detection system). WMMD uses API interception techniques to dynamic analyze application's behavior and compare it with malicious behavior characteristics library using model checking. The experiment results show that WMMD can effectively detect the obfuscated or packed malware variants that cannot be detected by other main stream anti-virus products.
Outage performance of analog network coding in generalized two-way multi-hop networks

We investigate the performance of analog network coding (ANC) for multi-hop networks in this paper. With the amplify-and-forward (AF) protocol, relays broadcast the sum of two colliding signals to neighboring nodes, while the source node can subtract its own signal from the colliding signal to obtain the received information. We first give the transmission scheme expressions for the n-node m-frame two-way multi-hop network. For this scheme, we derive the end-to-end signal-to-noise ratio (SNR) expression. Without loss of generality, the closed-form expression of the outage probability for the generalized multi-hop network is evaluated. Numerical results demonstrate that the outage performance with ANC is better than the traditional scheme without ANC.
Mitigating Breakdown Voltage with Dual Channel Vertical Strained SiGe Impact Ionization MOSFET (VESIMOS)

The Single and Dual Strained SiGe layer for Vertical Strained Silicon Germanium (SiGe) Impact Ionization MOSFET (VESIMOS) have been successfully analyzed in this paper. It is found that drain current for single (SC) and dual channel (DC) VESIMOS were increased sharply initially due to the presence of Germanium. Germanium has high impact ionization rates to ensure that the transition from OFF state to ON state is abrupt. However, breakdown voltage of the SC device was decreased from BV=2.9V to 2.5V by increasing the composition of Ge from 10% to 30%. The same characteristics were found for DC VESIMOS where BV= 2V had decreased to 1.6V by varying the Ge composition. In short, the breakdown voltage which affected by the appearance of second SiGe channel and Ge composition was justified. Apart from that, with the presence of second SiGe channel, the switching speed and ION/IOFF of the device were improved. It was found that the sub-threshold slope of SC and DC VESIMOS were inversely proportional to the breakdown voltage. Hence, DC VESIMOS can be promoted as extraordinary candidate for low power nanoelectronics device.
FindingMiMo: tracing a missing mobile phone using daily observations

With the widespread use of smartphones, the loss of a device is critical, both in disrupting daily communications, and in losing valuable property. When a mobile device is missing, localization techniques may assist in finding the device. Current techniques, however, hardly provide a complete solution because of inaccurate position estimation, especially in indoor environments. In this paper, we describe a software architecture called FindingMiMo, which tracks and locates a missing mobile device in indoor environments. The system consists of a missing mobile which logs diverse environmental features on a daily basis, and a chaser which traces the trail of the device using the observation log. During daily operation, the mobile device does not perform location estimation; it only observes the ambient features such as radio signals to minimize its operation cost. Instead, the chaser determines where the missing device measured the observations. This research implemented the scheme on Android-based smartphones. Real experiments with carefully designed, missing-and-tracking scenarios show that the participants successfully approached their lost phones within four meters distance, on average.
Software Requirements Implementation and Management

Proper elicitation, analysis, and documentation of requirements at the beginning of a software development project are considered important preconditions for successful software development. Furthermore, successful development requires that the requirements be correctly implemented and managed throughout the rest of the development. This latter success criterion is discussed in this paper. The paper presents a taxonomy for requirements implementation and management (RIM) and provides insights into the current state of these practices in the software industry. Based on the taxonomy and the industrial observations, a model for RIM is elaborated. The model describes the essential elements needed for successful implementation and management of requirements. In addition, three critical elements of the model with which the practitioners are currently struggling are discussed. These elements were identified as (1) involvement of software developers in system level requirements allocation, (2) work product verification with reviews, and (3) requirements traceability.
A Random Group Mobility Model for Mobile Networks

In this paper, we investigate mobility model in mobile networking and propose a novel random group mobility model for mobile ad hoc networks. The presented model named Charge Vector Group Mobility Model regards mobile nodes as particles carrying different kinds of charges. Reference points are also defined carrying only one kind of charge and moving in simulation area with some general rules. Mobile nodes then move according to several rules and transit among three states. This random group mobility model can illustrate the mobilities in real life, including aggregating, disaggregating, group movement and individual movement and show both randomness and some orderliness.
Reelin supplementation recovers synaptic plasticity and cognitive deficits in a mouse model for Angelman syndrome

The Reelin signaling pathway is implicated in processes controlling synaptic plasticity and hippocampus‐dependent learning and memory. A single direct in vivo application of Reelin enhances long‐term potentiation, increases dendritic spine density and improves associative and spatial learning and memory. Angelman syndrome (AS) is a neurological disorder that presents with an overall defect in synaptic function, including decreased long‐term potentiation, reduced dendritic spine density, and deficits in learning and memory, making it an attractive model in which to examine the ability of Reelin to recover synaptic function and cognitive deficits. In this study, we investigated the effects of Reelin administration on synaptic plasticity and cognitive function in a mouse model of AS and demonstrated that bilateral, intraventricular injections of Reelin recover synaptic function and corresponding hippocampus‐dependent associative and spatial learning and memory. Additionally, we describe alteration of the Reelin profile in tissue from both the AS mouse and post‐mortem human brain.
Memory Management Support for Tiled Array Organization

A novel method is described which adds support for sub-array ordered (tiled) arrays to a conventional MMU. The resulting pages contain two dimensional tiles of data rather than one dimensional strips, making tiled virtual memory transparently available to general purpose application programs. The method is further extended to support sub-arrays with three or more dimensions. The image MMU of the Kodak Prophecy Color Publishing System is shown as a product implementation for color picture arrays.
The effects of scale differences on inferences in accounting research : coefficient estimates , tests of incremental association , and relative value relevance

Firms’ financial data vary considerably with the size of their operations. Such scale differences potentially confound several types of inferences, of which this paper analyzes three. This paper evaluates two potential solutions to these inference problems suggested by theory: (i) deflating the data by a proxy for scale; and (ii) including a scale proxy as an independent variable. First, simulations show that deflating the data more effectively mitigates coefficient bias than including that proxy as an independent variable. Reconciling this result with the opposing conclusion of Barth and Kallapur (1996, Contemporary Accounting Research) reveals that the prior results depend on assumptions that are economically and statistically unreasonable. Second, the deflation approach results in more accurate tests of incremental association in terms of mean squared error. Third, deflating by a scale proxy results in well-specified tests of relative association using Vuong’s (1989) Z-statistic for non-nested models whereas including the scale proxy as an independent variable results in overstated significance. Given the additional advantages of deflation with respect to heteroscedasticity and the coefficient of determination (R) demonstrated in prior studies, researchers should generally deflate their models when scale differences exist in the data. JEL Classification: C51, G10, G38, M41
A Comparative Analysis of Gene Expression Patterns and Cell Phenotypes between Cervical and Peripheral Blood Mononuclear Cells

Studies of the immunological environment in the female genital tract (FGT) are critical for the development of vaccines or microbicides to halt the spread of sexually transmitted infections. Challenges arise due to the difficulties of sampling from this site, and the majority of studies have been conducted utilising peripheral blood mononuclear cells. Identifying functional differences between immune cells of the FGT and peripheral blood would aid in our understanding of mucosal immunology. We compared the gene expression profile of mononuclear cells at these two sites. Messenger RNA expression analysis was performed using gene expression arrays on matched cervical mononuclear cells and peripheral blood mononuclear cells. Further cellular phenotyping was done by 10 colour flow cytometry. Of the 22,185 genes expressed by these samples, 5345 genes were significantly differentially expressed between the cell populations. Most differences can be explained by significantly lower levels of T and B cells and higher levels of macrophages and dendritic cells in the FGT compared with peripheral blood. Several immunologically relevant pathways such as apoptosis and innate immune signalling, and a variety of cytokines and cytokine receptors were differentially expressed. This study highlights the importance of the unique immunological environment of the FGT and identifies important differences between systemic and mucosal immune compartments.
A stochastic inventory routing problem for infectious medical waste collection

We consider the problem of designing a logistic system to organize adequate collection of infectious medical waste. Waste materials are produced by patients in self‐treatment, stored at pharmacies and picked up by local authorities for disposal. The problem is formulated as a collector‐managed inventory routing problem, encompassing stochastic aspects, which are common in such problems. Social objectives, specifically the satisfaction of pharmacists and local authorities, as well as the minimization of public health risks, are considered for the real‐world‐motivated inventory routing problem. To optimize the planning process for a predefined time horizon, we take advantage of radio frequency identification technology, which allows an improvement of the planning process for pharmacists as well as local authorities. We develop two solution approaches to optimize the determination of visit dates and corresponding vehicle routes. We design a sampling method and an approach based on an adaptive large neighborhood search algorithm to treat the stochastic problem. The suggested approaches are tested on real‐world data from the region of Provence‐Alpes‐Côte d'Azur, in France. To evaluate the performance of the proposed solution methods, the results for different waste collection scenarios are analyzed and compared. © 2013 Wiley Periodicals, Inc. NETWORKS, Vol. 63(1), 82–95 2014
MORPHEME BOUNDARY IDENTIFICATION USING LETTER SUCCESSOR VARIETY

Computer systems with a level of understanding of human language are a requirement of the today’s needs. Researchers are very much interested in developing systems to improve the interaction between humans and computers. In order to achieve it, research is increasingly applied to automated processing of natural language data. This is useful for many applications such as information retrieval, text categorization, dictionary automation, text compression, data encryption, vowelization and spelling aids, automatic translation and computer aided instruction.
Teamwork construction in E-learning system: A systematic literature review

With the increasing diversity of learners, forming suitable learning groups, in collaborative learning, represents a complex and a time-consuming task. Several researchers focus on the theory of teamwork organizations, based on academic performances, learning styles, learning settings, gender, etc. Therefore, grouping learners based on their predicted academic performance level in each subject separately may be more effective in a collaborative learning environment, but it still a challenging subject. First of all, we present in this paper a systematic literature review (SLR) to identify the relevant studies that address the problem of predicting academic performance and to extract the used data mining methods such as Decision Tree, Naïve Bayes, Neural Network, Support Vector Machine, etc. At the beginning, a set of 658 papers were selected. After applying the different SLR's steps, this selection has been filtered to 12 papers using specific selection criteria and a careful analysis of each paper. Then, the selected studies were used to answer the defined research questions. Finally, synthesis data, current research gaps and recommendations for further work are discussed in this paper.
Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neurons

Cooperative competitive networks are believed to play a central role in cortical processing and have been shown to exhibit a wide set of useful computational properties. We propose a VLSI implementation of a spiking cooperative competitive network and show how it can perform context dependent computation both in the mean firing rate domain and in spike timing correlation space. In the mean rate case the network amplifies the activity of neurons belonging to the selected stimulus and suppresses the activity of neurons receiving weaker stimuli. In the event correlation case, the recurrent network amplifies with a higher gain the correlation between neurons which receive highly correlated inputs while leaving the mean firing rate unaltered. We describe the network architecture and present experimental data demonstrating its context dependent computation capabilities.
Long-term results after treatment of humeral neck fractures using modified Hackethal bundle nailing.

OBJECTIVE This study reports the long-term surgical outcomes of elderly patients who underwent surgery using the modified Hackethal bundle nailing method on the basis of an approximately 10-year follow-up study. METHODS We treated 34 patients (7 males, 27 females) with 2- and 3-fragment fractures of the proximal humeral neck. Their ages at the time of operation ranged from 65 to 75 years (mean age, 69.5 years). They were classified as Neer group I (G-I, 8.8%), III (G-III, 79.4%) or IV (G-IV 11.8%). The duration of follow-up in patients averaged 130.6 months (range: 125.0 - 156.0 months). Patients were graded according to the Constant-Murley (CM) scoring system. Pre-operative and postoperative X-rays were also assessed. RESULTS All the fractures united within 6- 9 weeks, with an average of 7.4 weeks. The mean overall Constant score was 80.0 points (G-I: 83.3; G-III: 80.5; G-IV 75.6). Among the 34 patients, 30 (88.2%) obtained excellent results and 4 (11.8%) obtained good results. Mal-union in the coronal plane was observed in two patients (6.28%) who had 160 degrees angulation in three part fracture. Mal-union of the greater tuberosity occurred in one patient (3.14%) leading to limitation of abduction to 90 degrees. There were no cases of avascular necrosis, neurovascular complications or deep infections. CONCLUSION This study suggests that the modified H-technique is simple, less invasive, and a reliable and effective procedure for elderly patients.
A Novel Turtle Shell Based Scheme for Data Hiding

Data hiding is a well-known technique which embeds the secret data into a digital media. Most of the existing schemes either have the low image quality, or provide the restricted embedding capacity. In this paper, a new data hiding scheme based on turtle shell is proposed to obtain better image quality and higher embedding capacity. In the proposed scheme, a secret digit is embedded into each cover pixel pair with the guidance of the turtle shell. Experimental results reveal that the proposed scheme ensures not only higher embedding capacity, but also obtains better visual quality compared with the existing schemes.