Miracle-dz/UniFAR-FTUs huggingface dataset:
Na(+)-dependent Cl-HCO3 exchange in the squid axon. Dependence on extracellular pH

Intracellular pH (pHi) in squid giant axons recovers from acid loads by means of a Na(+)-dependent Cl-HCO3 exchanger, the actual mechanism of which might be exchange of: (i) external Na+ and HCO3- for internal Cl- and H+, (ii) Na+ plus two HCO3- for Cl-, (iii) Na+ and CO3= for Cl-, or (iv) the NaCO3- ion pair for Cl-. Here we examine sensitivity of transport to changes of extracellular pH (pHo) in the range 7.1-8.6. We altered pHo in four ways, using: (i) classical "metabolic" disturbances in which we varied [HCO3-]o, [NaCO3-]o, and [CO3=]o at a fixed [CO2]o; (ii) classical "respiratory" disturbances in which we varied [CO2]o, [NaCO3-]o, and [CO3=]o at a fixed [HCO3-]o; (iii) novel mixed-type acid- base disturbances in which we varied [HCO3-]o and [CO2]o at a fixed [CO3=]o and [NaCO3-]o; and (iv) a second series of novel mixed-type disturbances in which we varied [CO2]o, [CO3=]o, and [Na+]o at a fixed [HCO3-]o and [NaCO3-]o. Axons (initial pHi approximately 7.4) were internally dialyzed with a pH 6.5 solution containing 400 mM Cl- but no Na+. After pHi, measured with a glass microelectrode, had fallen to approximately 6.6, dialysis was halted. The equivalent acid extrusion rate (JH) was computed from the rate of pHi recovery (i.e., increase) in the presence of Na+ and HCO3-. When pHo was varied by method (i), which produced the greatest range of [CO3=]o and [NaCO3-]o values, JH increased with pHo in a sigmoidal fashion; the relation was fitted by a pH titration curve with a pK of approximately 7.7 and a Hill coefficient of approximately 3.0. With method (ii), which produced smaller changes in [CO3=]o and [NaCO3-]o, JH also increased with pHo, though less steeply. With method (iii), which involved changes in neither [CO3=]o nor [NaCO3-]o, JH was insensitive to pHo changes. Finally, with method (iv), which involved changes in neither [HCO3-] nor [NaCO3-]o, but reciprocal changes in [CO3=]o and [Na+]o, JH also was insensitive to pHo changes. We found that decreasing pHo from 8.6 to 7.1 caused the apparent Km for external HCO3- ([Na+]o = 425 mM) to increase from 1.0 to 26.7 mM, whereas Jmax was relatively stable. Decreasing pHo from 8.6 to 7.4 caused the apparent Km values for external Na+ ([HCO3-]o = 48 mM) to increase from 8.6 to 81 mM, whereas Jmax was relatively stable. (ABSTRACT TRUNCATED AT 400 WORDS)
A Cryptographic Provenance Verification Approach For Host-Based Malware Detection

We present a malware detection approach by focusing on the characteristic behaviors of human users. We explore the human-malware differences and utilize them to aid the detection of infected hosts. There are two main research challenges in this study: one is how to select characteristic behavior features, and the other is how to prevent malware forgeries. We address both questions in this paper. A cryptographic provenance verification technique is described. Its two applications are demonstrated in keystrokebased bot identification and rootkit traffic detection. Specifically, we first present our design and implementation of a remote authentication framework called TUBA for monitoring a user’s typing patterns and verifying their integrity. We evaluate the robustness of TUBA through comprehensive experimental evaluation including two series of simulated bots. We then demonstrate our provenance verification approach by realizing a lightweight framework for blocking outbound rootkit-based malware traffic.
3D Stochastic Geometry Model for Large-Scale Molecular Communication Systems

Information delivery using chemical molecules is an integral part of biology at multiple distance scales and has attracted recent interest in bioengineering and communication. The collective signal strength at the receiver (i.e., the expected number of observed molecules inside the receiver), resulting from a large number of transmitters at random distances (e.g., due to mobility), can have a major impact on the reliability and efficiency of the molecular communication system. Modeling the collective signal from multiple diffusion sources can be computationally and analytically challenging. In this paper, we present the first tractable analytical model for the collective signal strength due to randomly-placed transmitters, whose positions are modelled as a homogeneous Poisson point process in three-dimensional (3D) space. By applying stochastic geometry, we derive analytical expressions for the expected number of observed molecules at a fully absorbing receiver and a passive receiver. Our results reveal that the collective signal strength at both types of receivers increases proportionally with increasing transmitter density. The proposed framework dramatically simplifies the analysis of large-scale molecular systems in both communication and biological applications.
Transcriptomic Analysis Provides Insights into Grafting Union Development in Pecan (Carya illinoinensis)

Pecan (Carya illinoinensis), as a popular nut tree, has been widely planted in China in recent years. Grafting is an important technique for its cultivation. For a successful grafting, graft union development generally involves the formation of callus and vascular bundles at the graft union. To explore the molecular mechanism of graft union development, we applied high throughput RNA sequencing to investigate the transcriptomic profiles of graft union at four timepoints (0 days, 8 days, 15 days, and 30 days) during the pecan grafting process. After de novo assembly, 83,693 unigenes were obtained, and 40,069 of them were annotated. A total of 12,180 differentially expressed genes were identified between by grafting. Genes involved in hormone signaling, cell proliferation, xylem differentiation, cell elongation, secondary cell wall deposition, programmed cell death, and reactive oxygen species (ROS) scavenging showed significant differential expression during the graft union developmental process. In addition, we found that the content of auxin, cytokinin, and gibberellin were accumulated at the graft unions during the grafting process. These results will aid in our understanding of successful grafting in the future.
Highly pathogenic H5N1 influenza virus can enter the central nervous system and induce neuroinflammation and neurodegeneration

One of the greatest influenza pandemic threats at this time is posed by the highly pathogenic H5N1 avian influenza viruses. To date, 61% of the 433 known human cases of H5N1 infection have proved fatal. Animals infected by H5N1 viruses have demonstrated acute neurological signs ranging from mild encephalitis to motor disturbances to coma. However, no studies have examined the longer-term neurologic consequences of H5N1 infection among surviving hosts. Using the C57BL/6J mouse, a mouse strain that can be infected by the A/Vietnam/1203/04 H5N1 virus without adaptation, we show that this virus travels from the peripheral nervous system into the CNS to higher levels of the neuroaxis. In regions infected by H5N1 virus, we observe activation of microglia and alpha-synuclein phosphorylation and aggregation that persists long after resolution of the infection. We also observe a significant loss of dopaminergic neurons in the substantia nigra pars compacta 60 days after infection. Our results suggest that a pandemic H5N1 pathogen, or other neurotropic influenza virus, could initiate CNS disorders of protein aggregation including Parkinson's and Alzheimer's diseases.
Fast Heuristic Algorithm for Multi-scale Hierarchical Community Detection

Complex networks constitute the backbones of many complex systems such as social networks. Detecting the community structure in a complex network is both a challenging and a computationally expensive task. In this paper, we present the HAMUHI-CODE, a novel fast heuristic algorithm for multiscale hierarchical community detection inspired on an agglomerative hierarchical clustering technique. We define a new structural similarity of vertices based on the classical cosine similarity by removing some vertices in order to increase the probability of identifying inter-cluster edges. Then we use the proposed structural similarity in a new agglomerative hierarchical algorithm that does not merge only clusters with maximal similarity as in the classical approach, but merges any cluster that does not meet a parameterized community definition with its most similar adjacent cluster. The algorithm computes all the similar clusters at the same time is checking if each cluster meets the parameterized community definition. It is done in linear time complexity in terms of the number of cluster in the iteration. Since a complex network is a sparse graph, our approach HAMUHI-CODE has a super-linear time complexity with respect to the size of the input in the worst-case scenario (if the clusters merge in pairs), making it suitable to be applied on large-scale complex networks. To test the properties and the efficiency of our algorithm we have conducted extensive experiments on real world and synthetic benchmark networks by comparing it to several baseline state-of-the-art algorithms.
A comparison of the use of virtual versus physical snapshots for supporting update-intensive workloads

Deployments of networked sensors fuel online applications that feed on real-time sensor data. This scenario calls for techniques that support the management of workloads that contain queries as well as very frequent updates. This paper compares two well-chosen approaches to exploiting the parallelism offered by modern processors for supporting such workloads. A general approach to avoiding contention among parallel hardware threads and thus exploiting the parallelism available in processors is to maintain two copies, or snapshots, of the data: one for the relatively long-duration queries and one for the frequent and very localized updates. The snapshot that receives the updates is frequently made available to queries, so that queries see up-to-date data. The snapshots may be physical or virtual. Physical snapshots are created using the C library memcpy function. Virtual snapshots are created by the fork system function that creates a new process that initially has the same data snapshot as the process it was forked from. When the new process carries out updates, this triggers the actual memory copying in a copy-on-write manner at memory page granularity. This paper characterizes the circumstances under which each technique is preferable. The use of physical snapshots is surprisingly efficient.
Extracting micro-structural gabor features for face recognition

Robustness and discriminability are two key issues in face recognition. In this paper, we propose a new algorithm which extracts micro-structural Gabor feature to achieve good robustness and discriminability simultaneously. We first design a family of directional block partitions to compute the block-level directional projections of the classical Gabor feature. Then we use two statistical kernels, i.e, the mean kernel and the variance kernel, to extract the micro-structural statistics. Analysis of both robustness and discriminability is conducted to show that the new feature is not only more robust to misalignment, but also more discriminative than the classical down-sampling Gabor feature, which is further demonstrated by three groups of experiments on the BANCA dataset.
The Case for RackOut: Scalable Data Serving Using Rack-Scale Systems

To provide low latency and high throughput guarantees, most large key-value stores keep the data in the memory of many servers. Despite the natural parallelism across lookups, the load imbalance, introduced by heavy skew in the popularity distribution of keys, limits performance. To avoid violating tail latency service-level objectives, systems tend to keep server utilization low and organize the data in micro-shards, which provides units of migration and replication for the purpose of load balancing. These techniques reduce the skew, but incur additional monitoring, data replication and consistency maintenance overheads. In this work, we introduce RackOut, a memory pooling technique that leverages the one-sided remote read primitive of emerging rack-scale systems to mitigate load imbalance while respecting service-level objectives. In RackOut, the data is aggregated at rack-scale granularity, with all of the participating servers in the rack jointly servicing all of the rack's micro-shards. We develop a queuing model to evaluate the impact of RackOut at the datacenter scale. In addition, we implement a RackOut proof-of-concept key-value store, evaluate it on two experimental platforms based on RDMA and Scale-Out NUMA, and use these results to validate the model. Our results show that RackOut can increase throughput up to 6x for RDMA and 8.6x for Scale-Out NUMA compared to a scale-out deployment, while respecting tight tail latency service-level objectives.
Implementation of single precision floating point multiplier using Karatsuba algorithm

This paper presents an efficient floating point multiplier using Karatsuba algorithm. Digital signal processing algorithms and media applications use a large number of multiplications, which is both time and power consuming. We have used IEEE 754 format for binary representation of the floating point numbers. Verilog HDL is used to implement Karatsuba multiplication algorithm which is technology independent pipelined design. This multiplier implements the significant multiplication along with sign bit and exponent computations. Three stage pipelining is being used in the design with the latency of 8 clock cycles. In this design, the mantissa bits are divided into three parts of particular bit width in such a way so that the multiplication can be done using the standard multipliers available in FPGA cyclone II device family and synthesized using Altera-Quartus II.
Neural Mechanisms for the Robust Representation of Junctions

Junctions provide important cues in various perceptual tasks, such as the determination of occlusion relationships for figure-ground separation, transparency perception, and object recognition, among others. In computer vision, junctions are used in a number of tasks, like point matching for image tracking or correspondence analysis. We propose a biologically motivated approach to junction representation in which junctions are implicitly characterized by high activity for multiple orientations within a cortical hypercolumn. A local measure of circular variance is suggested to extract junction points from this distributed representation. Initial orientation measurements are often fragmented and noisy. A coherent contour representation can be generated by a model of V1 utilizing mechanisms of collinear long-range integration and recurrent interaction. In the model, local oriented contrast estimates that are consistent within a more global context are enhanced while inconsistent activities are suppressed. In a series of computational experiments, we compare junction detection based on the new recurrent model with a feedforward model of complex cells. We show that localization accuracy and positive correctness in the detection of generic junction configurations such as L- and T-junctions is improved by the recurrent long-range interaction. Further, receiver operating characteristics analysis is used to evaluate the detection performance on both synthetic and camera images, showing the superior performance of the new approach. Overall, we propose that nonlocal interactions implemented by known mechanisms within V1 play an important role in detecting higher-order features such as corners and junctions.
Non-Pharmacological Interventions for Chronic Pain and Depression: any Possible Applications of Multisensory Feedback Approaches Based on Body Representation?

Chronic pain is often associated with sleep disruption, fatigue, cognitive deficits and mood alterations. In particular a bidirectional relationship exists between pain and mood disorders, for example chronic pain and depression. When these morbidities co-occur, the patient’s quality of life can significantly decrease. Different pharmacological solutions have been proposed to target both symptom atologies but misuse, addiction and side effects may limit their adoption. Non-pharmacological interventions like psychotherapy and physical activity have been shown to yield promising results in the management of both chronic pain and mood disorders. In the last twenty years multisensory feedback approaches based on body representation have also been shown to be a valid method to treat different forms of chronic pain. However, comorbid mood disorders have not been taken in consideration by this latter approach. The advances in the treatment of chronic pain with comorbid depression may benefit from future studies using multisensory feedback approaches based on body representation
Integral variable structure control of nonlinear system using a CMAC neural network learning approach

This work presents a novel integral variable structure control (IVSC) that combines a cerebellar model articulation controller (CMAC) neural network and a soft supervisor controller for use in designing single-input single-output (SISO) nonlinear system. Based on the Lyapunov theorem, the soft supervisor controller is designed to guarantee the global stability of the system. The CMAC neural network is used to perform the equivalent control on IVSC, using a real-time learning algorithm. The proposed IVSC control scheme alleviates the dependency on system parameters and eliminates the chattering of the control signal through an efficient learning scheme. The CMAC-based IVSC (CIVSC) scheme is proven to be globally stable inasmuch all signals involved are bounded and the tracking error converges to zero. A numerical simulation demonstrates the effectiveness and robustness of the proposed controller.
Kluyveromyces lactis gene KlBIM1 in high copy state suppresses heterologous protein secretion

The aim of this work was to investigate the genes that under over-expression in the yeast Kluyveromyces lactis decrease the yield of secretory proteins. The MD2/1-9 mutant strain with an enhanced ability to secrete different proteins was used. The genes suppressing the protein secretion process were detected by using the α -amylase gene. The gene KlBIM1 was found to suppress mutation of the MD2/1-9 mutant strain in yeast K. lactis. To test the influence of the chromosomal gene on protein secretion, the BIM1 gene was disrupted in both yeast K. lactis and S. cerevisae, and the influence of disruption on the protein secretion process was evaluated. The disruption of the gene KlBIM1 had no influence on the protein secretion process in K. lactis, however, disruption of the BIM1 gene in S. cerevisiae elevated protein secretion by approximately 24%. Our experiment has shown that K. lactis strain lacking the gene KlBIM1 is not suitable for elevated heterologous protein secretion. The K. lactis mutant strain MD2/1-9 was transformed by the S. cerevisiae gene BIM1 in order to evaluate the influence of this gene in a high-copy state to the α -amylase secretion process. The S. cerevisiae gene BIM1 in a high-copy-number state significantly decreased secretion of α -amylase in K. lactis MD2/1-9. This fact suggests that the homology between the gene KlBIM1 in K. lactis and BIM1 in S. cerevisiae is rather high and the biological function of those genes in both yeasts is quite similar.
Euclidean Shape and Motion from Multiple Perspective Views by Affine Iterations

We describe a method for solving the Euclidean reconstruction problem with a perspective camera model by incrementally performing Euclidean reconstruction with either a weak or a paraperspective camera model. With respect to other methods that compute shape and motion from a sequence of images with a calibrated camera, this method converges in a few iterations, is computationally efficient, and solves for the sign (reversal) ambiguity. We give a detailed account of the method, analyze its convergence, and test it with both synthetic and real data.
The silence of Good Samaritan kidney donation in Australia: a survey of hospital websites

It is common for living donor candidates to use the Internet as a tool to enhance their decision‐making process. Specifically, the websites of transplant hospitals can potentially be a vital source of information for those contemplating living donation. In an effort to explore the low incidence of Good Samaritan kidney donation (donations to strangers) in Australia, two raters conducted a nine‐attribute website content analysis for all hospitals which participate in these transplants (n = 15). Overall, the concept of living donation is relatively silent on Australian hospital websites. Only four hospitals mention their living donor program, and only one mentions their Good Samaritan program. No site linked directly to Australia's AKX Paired Kidney Exchange Program – the only program which facilitates pair and chain transplants in Australia. Further, information about deceased donation is nearly absent as well. An individual with the altruistic desire to donate will generally find scant or absent information about donation at the website of their local transplant hospital, although this information could easily be present as an educational tool which supports the consent process. Using a hospital website to educate the public about a clinical service should not be viewed as ethically problematic (solicitation), but rather an ethical essential.
HAMEX: heterogeneous architecture and memory exploration framework

The increasing amount of computation in heterogeneous architectures (including CPU and GPU cores) puts a big burden on memory subsystem. With the gap between compute units and the memory performance getting wider, designing a platform with a responsive memory system becomes more challenging. This issue is exacerbated when memory systems have to satisfy a high volume of traffic generated from heterogeneous compute units. Furthermore, as emerging memory technologies are being introduced to address these issues, a rapid and flexible mechanism is needed to evaluate these technologies in the context of heterogeneous architectures. This paper proposes HAMEX, a framework that enables early design space exploration of heterogeneous systems with a focus on resolving memory access bottlenecks. This framework first allows system designers to easily model heterogeneous architectures that can run both CPU and GPU workloads. Next, given a set of workloads partitioned on various compute units, traffic generated by these units are captured in order to explore different memory systems. We show the feasibility of design space exploration using HAMEX by simulating a contemporary commercial heterogeneous platform and explore the opportunities for power and performance improvements by adopting different memory technologies.
MMDV : M ultipath and M PR based AO DV routing protocol

The problem of routing in mobile ad hoc networks is considered as an important issue. In fact, these networks are characterized by multi hop wireless connectivity, node mobility, limited power and memory resources. In this paper we study several possible modifications of AODV[1] routing protocol based on selected features available in other routing protocols. Simulation results allowed us to select the two most relevant ones. MMDV is an amelioration of AODV protocol providing for multipath and MPR based flooding. This protocol consists of both proactive and reactive components. In a proactive phase, nodes compute their MPR lists and compute paths to their two hop neighbors. In a reactive phase, nodes compute two paths for each destination. Simulation results show that MMDV enhance the packet delivery performance and reduce the overhead.