Miracle-dz/UniFAR-FTUs huggingface dataset:
CannyFS: Opportunistically Maximizing I/O Throughput Exploiting the Transactional Nature of Batch-Mode Data Processing

We introduce a user mode file system, CannyFS, that hides latency by assuming all I/O operations will succeed. The user mode process will in turn report errors, allowing proper cleanup and a repeated attempt to take place. We demonstrate benefits for the model tasks of extracting archives and removing directory trees in a real-life HPC environment, giving typical reductions in time use of over 80%. This approach can be considered a view of HPC jobs and their I/O activity as transactions. In general, file systems lack clearly defined transaction semantics. Over time, the competing trends to add cache and maintain data integrity have resulted in different practical tradeoffs. High-performance computing is a special case where overall throughput demands are high. Latency can also be high, with non-local storage. In addition, a theoretically possible I/O error (like permission denied, loss of connection, exceeding disk quota) will frequently warrant the resubmission of a full job or task, rather than traditional error reporting or handling. Therefore, opportunistically treating each I/O operation as successful, and part of a larger transaction, can speed up some applications that do not leverage asynchronous I/O.
Analytical Methods in Untargeted Metabolomics: State of the Art in 2015

Metabolomics comprises the methods and techniques that are used to measure the small molecule composition of biofluids and tissues, and is actually one of the most rapidly evolving research fields. The determination of the metabolomic profile – the metabolome – has multiple applications in many biological sciences, including the developing of new diagnostic tools in medicine. Recent technological advances in nuclear magnetic resonance and mass spectrometry are significantly improving our capacity to obtain more data from each biological sample. Consequently, there is a need for fast and accurate statistical and bioinformatic tools that can deal with the complexity and volume of the data generated in metabolomic studies. In this review, we provide an update of the most commonly used analytical methods in metabolomics, starting from raw data processing and ending with pathway analysis and biomarker identification. Finally, the integration of metabolomic profiles with molecular data from other high-throughput biotechnologies is also reviewed.
Low Temperature Adaptation Is Not the Opposite Process of High Temperature Adaptation in Terms of Changes in Amino Acid Composition

Previous studies focused on psychrophilic adaptation generally have demonstrated that multiple mechanisms work together to increase protein flexibility and activity, as well as to decrease the thermostability of proteins. However, the relationship between high and low temperature adaptations remains unclear. To investigate this issue, we collected the available predicted whole proteome sequences of species with different optimal growth temperatures, and analyzed amino acid variations and substitutional asymmetry in pairs of homologous proteins from related species. We found that changes in amino acid composition associated with low temperature adaptation did not exhibit a coherent opposite trend when compared with changes in amino acid composition associated with high temperature adaptation. This result indicates that during their evolutionary histories the proteome-scale evolutionary patterns associated with prokaryotes exposed to low temperature environments were distinct from the proteome-scale evolutionary patterns associated with prokaryotes exposed to high temperature environments in terms of changes in amino acid composition of the proteins.
Effects of Type 2 Diabetes on 12-Year Cognitive Change

OBJECTIVE To examine the effects of baseline and incident diabetes on change in cognitive function over 12 years. RESEARCH DESIGN AND METHODS A sample of 1,290 individuals aged ≥40 years at baseline, participating in the Maastricht Aging Study, were cognitively tested at baseline, after 6 years, and after 12 years. Of these, 68 participants had type 2 diabetes at baseline, and 54 and 57 had incident diabetes at the 6- and 12-year follow-up, respectively. Changes in performance on tests of information-processing speed, executive function, and verbal memory from baseline to 6- and 12-year follow-up were compared between groups using linear mixed models. Effects of diabetes on cognitive decline were adjusted for demographic variables, history of smoking, alcohol intake, and comorbid conditions, including hypertension, cardiovascular disease, BMI, and depression. RESULTS Participants with baseline diabetes showed larger decline in information-processing speed (estimate −7.64; P < 0.01), executive function (21.82; P < 0.01), and delayed word recall (−1.35; P < 0.05) over the 12-year follow-up compared with control subjects. No significant difference in decline was observed for immediate word recall. Compared with control subjects, participants with incident diabetes showed subtle early decline in information-processing speed only. Interestingly, they did not show larger decline in any other cognitive domain. CONCLUSIONS Individuals with baseline type 2 diabetes show accelerated cognitive decline, particularly in information-processing speed and executive function, compared with individuals without diabetes. In incident diabetes, decline in speed becomes detectable first, and cognitive decline seems to increase with increasing exposure time.
Grammaticalization and the Life-Cycles of Constructions

Grammaticalization is commonly seen as "a process which turns lexemes into grammatical formatives and makes grammatical formatives still more grammatical". In this paper, it is argued that grammaticalization has to be treated in the wider perspective of the life cycles of grammatical constructions. The notion of an "inflationary process" is invoked in order to explain what goes on in grammaticalization. It is argued that the degree of independence of an element of a linguistic expression reflects its informational value and that one of the main components of grammaticalization is rhetorical devaluation, by which a construction comes to be used with a lower informational impact. 1. Grammaticalization as an integrated part of the study of the life cycles of constructions After having undergone a period of what Christian Lehmann (1982) has aptly called “amnesia”, the study of grammaticalization has recently witnessed an upsurge of interest among linguists. Although it was extensively studied as a phenomenon already in the 19 th century (most often under the heading of “agglutination theory”), grammaticalization as a term is usually ascribed to Meillet (1912), whose definition is often quoted in the PRGLILFDWLRQ JLYHQ E\ . XU\áRZLF] ZKHUH LW LV VDLG WR EH 3D SURFHVV ZKLFK WXUQV lexemes into grammatical formatives and makes grammatical formatives still more grammatical”. This approach focuses on the fate of individual items such as words and morphemes. In this paper, I shall by contrast try to take a wider view, in which grammaticalization in the traditional sense is seen as an integrated part of the study of the life cycles of grammatical constructions or patterns. More specifically: what is
Pattern Change of Inhibitory Drug Craving Control in Brain: A Study of Effective Connectivity

Background: The inhibitory behavioral control of brain in treated drug abusers encountering drug cues, as well as the constructing regions of its network, has been widely studied previously. The causal relation of relevant brain regions has also been noticed in the literature, but the time/task condition variability of this causal network has not been studied yet.Method: Thirteen drug abusers successfully treated with Methadone maintenance therapy, were scanned during a drug cue fMRI task. Two regions of interest (VMPFC and amygdala) were chosen based on the literature. Using Dynamic Causal Modelling (DCM), an effective connectivity network was estimated between these two brain regions and a craving-inducing input. Later, implementing a sliding window method on the extracted time-series, five further DCM networks were estimated to evaluate the time variability of the DCM network.Results: The result of ordinary DCM showed that there were reciprocal connections between regions, and the craving input only affects the amygdala region. Sliding window showed that the input link strength changes during the task. This change was an exponential growth which moved from near zero to a positive value.Discussion: The pattern of our DCM network demonstrated that the craving input passes from bottom brain regions to the top, and therefore, it indirectly affects top regions. However, the causal relations of this network varies during the task, and the craving link strength also grows exponentially. Our findings are in agreement with the hypothesis of craving inducement during stimulation, and therefore it may be considered as a proxy craving measurement.
The Study of OFDM ICI Cancellation Schemes in 2.4 GHz Frequency Band Using Software Defined Radio

In Orthogonal Frequency Division Multiplexing (OFDM), frequency offset is a common problem that causes inter-carrier-interference (ICI) that degrades the quality of the transmitted signal. Many theoretical studies of the different ICI-cancellation schemes have been reported earlier by many authors. The need for experimental verification of the theoretically predicted results in 2.4 GHz frequency band is important. One of most widely used systems is Wi-Fi (IEE 802.11b) that makes use of this frequency band for short range wireless communication with throughput as high as 11 Mbps. In this work, several new ICI cancellation schemes have been tested in 2.4 GHz frequency using open source Software Defined Radio (SDR) namely GNU Radio. The GNU Radio system used in the experiment had two Universal Software Radio Peripheral (USRP N210) modules connected to a computer. Both the USRP units had one-daughterboard (XCVR2450) each for transmission and reception of radio signals. The input data to the USRP was prepared in compliance with IEEE-802.11b specification. The experimental results were compared with the theoretical results of the new Inter-Carrier Interference (ICI) cancellation schemes. The comparison of the results revealed that the new schemes are suitable for high performance transmission. The results of this paper open up new opportunities of using OFDM in heavily congested 2.4 GHz and 5 GHz bands (WiFi5: IEEE 802.a) for error free data transmission. The schemes also can be used in other frequencies where channels are heavily congested.
Particle Swarm Optimization Approach for Mitigation of Harmonics in Multilevel Inverters : A Review

Multilevel inverter technology has emerged recently as a very important alternative in the area of high-power mediumvoltage energy control. Using multilevel inverters application in fuel cell, solar cell & wind turbines is increasing now a day‘s rapidly. Therefore, Harmonic reduction techniques in multilevel inverters are considered very important task Over the past decades, depending upon the topologies and control strategies, numerous optimization techniques have been proposed for desired output waveform. This paper presents a review of optimization techniques used for multilevel inverters. The pros and cons of optimization techniques are discussed. The objective of these optimization techniques is to find out the optimum firing angles of multilevel inverters, which results in minimum harmonics.This paper presents a review application of PSO for harmonic reduction in multilevel inverters. As a preferred option for proposed work, reduction of total harmonic distortion with the aid of particle swarm optimization technique to multilevel inverters is suggested. Keywords— Harmonic suppression, Multilevel Inverter, PSO, Total Harmonic Distortion.
Improved centroid localization algorithm in WSNs

Wireless sensor networks (WSNs) are more and more widely used in many different scenarios. The localization information is an important criterion for the capability of WSNs. Centroid algorithm is a classical range-free localization algorithm. After receiving the anchor nodes, a node estimates its location using the centroid formula. But the set of the asymmetrical anchor nodes distributed around the unknown node may incur large error, and will jeopardize the localization precision. In order to solve the problem, we propose a Centroid algorithm with selective anchor node localization algorithm (SA-Centroid) for WSNs in this paper. The triangle centroid and polygon centroid were used and the method of selecting nearest anchor node was adopted. The experiment results illustrate that our algorithm is valid and effective.
Exploiting integrated GPUs for network packet processing workloads

Software-based network packet processing on standard high volume servers promises better flexibility, manageability and scalability, thus gaining tremendous momentum in recent years. Numerous research efforts have focused on boosting packet processing performance by offloading to discrete Graphics Processing Units (GPUs). While integrated GPUs, residing on the same die with the CPU, offer many advanced features such as on-chip interconnect CPU-GPU communication, and shared physical/virtual memory, their applicability for packet processing workloads has not been fully understood and exploited. In this paper, we conduct in-depth profiling and analysis to understand the integrated GPU's capabilities and performance potential for packet processing workloads. Based on that understanding, we introduce a GPU accelerated network packet processing framework that fully utilizes integrated GPU's massive parallel processing capability without the need for large numbers of packet batching, which might cause a significant processing delay. We implemented the proposed framework and evaluated the performance with several common, light-weight packet processing workloads on the Intel® Xeon® Processor E3-1200 v4 product family (codename Broadwell) with an integrated GT3e GPU. The results show that our GPU accelerated packet processing framework improved the throughput performance by 2-2.5x, compared to optimized packet processing on CPU only.
On modeling and control of a holonomic vectoring tricopter

The modeling and control of a vectoring tricopter UAV are developed in this article. The UAV is actuated by three thrust motors, each guided by suitable actuators, thus forming a platform able to independently track any desired attitude and trajectory. The derivation of the equations of motion is followed by the development of a vectoring controller that is supplemented by an allocation strategy. Both are based on geometric feedback linearization techniques, resulting in a singularity-free control law, taking into account the inertia effects of the main body, of the motors, and of the vectoring dynamics (actuators). A stability proof is developed validating the effectiveness of the control strategy under bounded disturbances. Simulations showcase the developed controller and tricopter performance.
A partition-based Summary-Graph-Driven Method for Efficient RDF Query Processing

RDF query optimization is a challenging problem. Although considerable factors and their impacts on query efficiency have been investigated, this problem still needs further investigation. We identify that decomposing query into a series of light-weight operations is also effective in boosting query processing. Considering the linked nature of RDF data, the correlations among operations should be carefully handled. In this paper, we present SGDQ, a novel framework that features a partition-based Summary Graph Driven Query for efficient query processing. Basically, SGDQ partitions data and models partitions as a summary graph. A query is decomposed into subqueries that can be answered without inter-partition processing. The final results are derived by perform summary graph matching and join the results generated by all matched subqueries. In essence, SGDQ combines the merits of graph match processing and relational join-based query implementation. It intentionally avoids maintain huge intermediate results by organizing sub-query processing in a summary graph driven fashion. Our extensive evaluations show that SGDQ is an effective framework for efficient RDF query processing. Its query performance consistently outperforms the representative state-of-the-art systems.
Facial Expression Recognition Based on MILBoost

In this paper, We use Adaboost to create MILBoost and propose a new MILBoost approach to automatically recognize the facial expression from video sequences by constructing the MILBoost methods. At first, we determine facial velocity information using optical flow technique, which is used to charaterize facial expression. Then visual words based on facial velocity is used to represent facial expression using Bag of Words. Final MILBoost model is used for facial expression recognition, in order to improve the recognition accuracy, the class label information was used for the learning of the MILBoost model. Experiments were performed on a facial expression dataset built by ourselves and evaluated the proposed method, the experiment results show that the average recognition accuracy is over 89.2%, which validates its effectiveness. Index Terms—Facial expression recognition; Motion feature; Bag of Words; MILBoost
Tumor necrosis factor alpha induces adhesion molecule expression on human fetal astrocytes

Leukocyte adhesion molecules on endothelial cells of the blood-brain barrier may participate in the entry of leukocytes into the central nervous system. Because astrocytes are also a component of the blood- brain barrier and have been associated with inflammation, we studied the ability of astrocytes to express leukocyte adhesion molecules using Northern blot and immunocytochemical techniques. Astrocytes treated with the proinflammatory cytokine tumor necrosis factor alpha (TNF) expressed messenger RNA for the adhesion molecules E-selectin, vascular cell adhesion molecule 1, and intercellular adhesion molecule 1, as well as their corresponding proteins. In addition, TNF-treated astrocytes expressed a monocyte adhesion protein identified by our laboratory, recognized by the monoclonal antibody IG9. These results indicate that under inflammatory conditions in the central nervous system, such as multiple sclerosis and acquired immune deficiency syndrome, astrocyte expression of adhesion molecules may facilitate the migration of leukocytes and contribute to the disease process.
Protocol Anomaly Detection for Network-based Intrusion Detection

A taxonomy was developed by Axelsson to define the space of intrusion detection technology and classify IDSs. The taxonomy categorizes IDSs by their detection principle and their operational aspects. The two main categories of detection principles are signature detection and anomaly detection. The remainder of this paper will compare the two categories of detection principles and describe a new type of anomaly detection based on protocol standards. While the taxonomy applies to both host-based and network-based IDSs, t.
Summary of Research Papers

In this article, the core results of the author’s papers are summarized. The author’s work has been carried out mainly on the finite field analogues of classical problems in harmonic analysis, geometric measure theory, and combinatorics. In particular, the author has investigated the boundedness of extension operators and the Erdős-Falconer type distance problems in the finite field setting. The author has also studied the connection between these two topics. 1. Recent developments in extension problems for finite fields Let V be a subset of R, d ≥ 2, and d a positive measure supported on V . Then, one may ask that for which values of p and r does the estimate ∥f̂d ∥Lr(Rd) ≤ Cp,r,d∥f∥Lp(V,d ) for all f ∈ L(V, d ) hold? This problem is known as the extension theorem which has not been completely solved in higher dimensions. Mockenhaupt and Tao ([8]) first addressed and studied the finite field analogue of the extension problem. Let us review what is the extension problem in the finite field setting. We denote by (Fq , dx) a d-dimensional vector space over the finite field Fq, where we endow the space with a normalized counting measure dx. On the other hand, (Fq , dm) denotes the dual space with a counting measure dm. Let (V, d ) be an algebraic variety in (Fq , dx), where we endow the variety V with a normalized surface measure d . Namely, we have the following formula d (x) = ∣Fq ∣ ∣V ∣ V (x), where ∣V ∣ denotes a cardinality of V ⊂ Fq and we identify the set V with the characteristic function V on V. For each 1 ≤ p, r ≤ ∞ we define R∗(p → r) to be the smallest constant such that the extension estimate ∥f̂d ∥Lr(Fdq ,dm) ≤ R ∗(p→ r)∥f∥Lp(V,d ) holds for all functions f on V. Notice that R∗(p → r) is always a finite number and it may depend on the underlying finite field Fq. The extension problem in finite fields is to determine possibly small exponents, 1 ≤ p, r ≤ ∞ such that R∗(p→ r) ≤ Cp,r,d <∞, where the main point is that the constant Cp,r,d is independent of the size of the underlying finite field Fq. In [8], Mockenhaupt and Tao developed useful tools to study the extension problem in finite fields for various algebraic varieties V , but their work was mostly restricted
Environmental Tolerance

A theory for the expression of a population's response to density-independent gradients of environmental factors is derived for the case of asexuality. It is shown that the environmental tolerance of a genotype is a function of at least four parameters: g$_1$ and V$_{E1}$, the environmental optimum and its developmental variance between individuals, and g$_2$ and V$_{E2}$, the expected genetic contribution to the breadth of adaptation and its developmental variance. The realized breadth of adaptation of a genotype (V$^{1/2}$) is a complex function of g$_2$, V$_{E1}$, and V$_{E2}$, but we argue that, with an appropriate scale transformation, the tolerance curve of a genotype is approximately normal, with mean g$_1$ and standard deviation V$^{1/2}$. It is shown that temporal heterogeneity in the environment selects for more-broadly-adapted genotypes but that the within-generation component (V$_{\phitw}$) plays a more prominent role than the between-generation component (V$_{\phitb}$). Spatial heterogeneity selects for higher V$^{1/2}$ only when it occurs in conjunction with temporal variance within generations and only if V$_{\phitb}$ is small relative to V$_{\phitw}$. We argue that since g$_2$ is expected to evolve subject to the constraint that V$^{1/2}$ is optimized, species exposed to conditions favoring identical V$^{1/2}$ may evolve different g$_2$ if pronounced interspecific differences exist for V$_{E1}$ and V$_{E2}$. A maximum-likelihood method is shown to be capable of generating accurate estimates of the genotypic parameters g$_1$, g$_2$, V$_{E1}$, and V$_{E2}$ with moderately large samples. We suggest how this procedure may be used to estimate analogous parameters for a population of mixed genotypes and to obtain estimates of the genetic variance for the environmental optimum and breadth of adaptation. The potential utility of this methodology for the analysis of data routinely generated in programs for environmental assessment and plant breeding is pointed out.