Miracle-dz/UniFAR-FTUs huggingface dataset:
A nearly linear time algorithm for the half integral parity disjoint paths packing problem

We consider the following problem, which is called the half integral parity disjoint paths packing problem. Input: A graph G, k pair of vertices (s1, t1), (s2, t2), . ,(sk, tk) in G (which are sometimes called terminals), and a parity li for each i with 1 ≤ i ≤ k, where li = 0 or 1. Output: Paths P1, . , Pk in G such that Pi joins si and ti for i = 1, 2, . , k and parity of length of the path Pi is li, i.e, if li = 0, then length of Pi is even, and if li = 1, then length of Pi is odd for i = 1, 2, . , k. In addition, each vertex is on at most two of these paths. We present an O(mα(m, n) log n) algorithm for fixed k, where n, m are the number of vertices and the number of edges, respectively, and the function α(m, n) is the inverse of the Ackermann function (see by Tarjan [43]). This is the first polynomial time algorithm for this problem, and generalizes polynomial time algorithms by Kleinberg [23] and Kawarabayashi and Reed [20], respectively, for the half integral disjoint paths packing problem, i.e., without the parity requirement. As with the Robertson-Seymour algorithm to solve the k disjoint paths problem, in each iteration, we would like to either use a huge clique minor as a "crossbar", or exploit the structure of graphs in which we cannot find such a minor. Here, however, we must maintain the parity of the paths and can only use an "odd clique minor". We must also describe the structure of those graphs in which we cannot find such a minor and discuss how to exploit it. We also have algorithms running in O(m(1 + e)) time for any e > 0 for this problem, if k is up to o(log log log n) for general graphs, up to o(log log n) for planar graphs, and up to o(log log n/g) for graphs on the surface, where g is Euler genus. Furthermore, if k is fixed, then we have linear time algorithms for the planar case and for the bounded genus case.
Cardiac Dysfunction in a Porcine Model of Pediatric Malnutrition

Background Half a million children die annually of severe acute malnutrition and cardiac dysfunction may contribute to the mortality. However, cardiac function remains poorly examined in cases of severe acute malnutrition. Objective To determine malnutrition-induced echocardiographic disturbances and longitudinal changes in plasma pro-atrial natriuretic peptide and cardiac troponin-T in a pediatric porcine model. Methods and Results Five-week old piglets (Duroc-x-Danish Landrace-x-Yorkshire) were fed a nutritionally inadequate maize-flour diet to induce malnutrition (MAIZE, n = 12) or a reference diet (AGE-REF, n = 12) for 7 weeks. Outcomes were compared to a weight-matched reference group (WEIGHT-REF, n = 8). Pro-atrial natriuretic peptide and cardiac troponin-T were measured weekly. Plasma pro-atrial natriuretic peptide decreased in both MAIZE and AGE-REF during the first 3 weeks but increased markedly in MAIZE relative to AGE-REF during week 5–7 (p≤0.001). There was overall no difference in plasma cardiac troponin-T between groups. However, further analysis revealed that release of cardiac troponin-T in plasma was more frequent in AGE-REF compared with MAIZE (OR: 4.8; 95%CI: 1.2–19.7; p = 0.03). However, when release occurred, cardiac troponin-T concentration was 6.9-fold higher (95%CI: 3.0–15.9; p<0.001) in MAIZE compared to AGE-REF. At week 7, the mean body weight in MAIZE was lower than AGE-REF (8.3 vs 32.4 kg, p<0.001), whereas heart-weight relative to body-weight was similar across the three groups. The myocardial performance index was 86% higher in MAIZE vs AGE-REF (p<0.001) and 27% higher in MAIZE vs WEIGHT-REF (p = 0.025). Conclusions Malnutrition associates with cardiac dysfunction in a pediatric porcine model by increased myocardial performance index and pro-atrial natriuretic peptide and it associates with cardiac injury by elevated cardiac troponin-T. Clinical studies are needed to see if the same applies for children suffering from malnutrition.
Computational analysis of the Bidirectional Activation-based Learning in autoencoder task

We use computational simulations to analyse the behavior of the recently proposed Bidirectional Activation-based Learning algorithm (BAL) which was inspired by the Generalized Recirculation algorithm (GeneRec). Both algorithms avoid biologically implausible backpropagation of the error signal, and instead use propagation of neuron activations, which drive the weight updates, using only local variables. We take a closer look at the 4-2-4 autoencoder task for which, despite the task simplicity, reliable convergence could not be achieved by either of the two models. We propose the learning mode with two, significantly different, learning rates (BAL2) that leads to considerably more successful task learning. We also analyze various factors, related to hidden activations, that contribute to further increase of the learning success. In addition, we test BAL2 also on the large scale database of handwritten digits, in which it yields relatively good performance.
Integrating Bioinformatics and Computational Biology: Perspectives and Possibilities for In Silico Network Reconstruction in Molecular Systems Biology

There is a flood of molecular data about many aspects of cellular functioning. This data ranges from sequence and structural data to gene and protein regulation data, including time dependent changes in the concentration. Integration of the different datasets through computational methods is required to extract biological information that is relevant from a systems biology perspective. In this paper we discuss how different computational tools and methods can be made to work together integrating differ- ent types of data, mining these data for biological information, and assisting in pathway reconstruction and biological hy- potheses generation. We review the recent body of literature where such integrative approaches are used and discuss automation of data integration and model building to generate testable biological hypotheses. We analyze issues regarding the design of such automated tools and discuss what limitations and pitfalls can be foreseen for the automation and what solutions can computer science and biologists provide to overcome them.
Airport security human factors: From the weakest to the strongest link in airport security screening.

Airport security screening is a challenging task. In fact, according to several experts, the human operator is often the weakest link of the security system. In this article, the results of human factor studies conducted over the last five years involving several international airports in four European countries are summarized. It is shown how human operators can in fact become the strongest link if they are selected and trained effectively. Recent developments and results of scientific studies in the following areas are briefly presented and discussed: Pre-employment assessment and selection tests, adaptive computerbased training, 3rd generation threat image projection, certification and competency assessment of x-ray
Ruminate : A Scalable Architecture for Deep Network Analysis

Traditionally, Network Intrusion Detection Systems (NIDS) inspect packet header and payload data for malicious content. While each system is different, most NIDS perform limited analysis on network streams and network protocols. Unfortunately, current NIDS are typically susceptible to evasion through network protocol encoding, such as base64 encoding of SMTP/MIME or gzip compression of HTTP. In addition, malicious desktop application payloads (e.g., PDF documents, Flash multimedia files) are beyond the inspection capabilities of popular NIDS. To address these limitations, we introduce Ruminate, a scalable object-centric traffic inspection and analysis architecture. Ruminate provides a distributed platform for deep analysis of network payload content. This includes full decoding of network protocols and recursive extraction of client application objects transferred over the network. While traditional NIDS utilize static packet load balancing to provide scalability, Ruminate employs dynamic load distribution of reassembled network streams and embedded objects, outsourcing the heavy processing to other processors or connected hosts. Therefore, high latency or computationally expensive analysis can be performed on commodity servers. Furthermore, our approach empowers system administrators to provision resources and preferentially treat traffic not only depending on the packet header but also on the data objects it carries. To achieve this, each object inspection algorithm is implemented as a separate component or service offered through a highly scalable producer-consumer architecture. We demonstrate using real-world traffic that our load balancing is far superior to existing techniques. This is because its granularity depends on the reconstructed objects rather than packet or simple stream analysis. Unlike existing systems, Ruminate can prevent NIDS evasion that leverages encoding or compression of malicious objects in network protocols, desktop application file formats, or encapsulation within other objects.
Reducing Cytoplasmic Polyamine Oxidase Activity in Arabidopsis Increases Salt and Drought Tolerance by Reducing Reactive Oxygen Species Production and Increasing Defense Gene Expression

The link between polyamine oxidases (PAOs), which function in polyamine catabolism, and stress responses remains elusive. Here, we address this issue using Arabidopsis pao mutants in which the expression of the five PAO genes is knocked-out or knocked-down. As the five single pao mutants and wild type (WT) showed similar response to salt stress, we tried to generate the mutants that have either the cytoplasmic PAO pathway (pao1 pao5) or the peroxisomal PAO pathway (pao2 pao3 pao4) silenced. However, the latter triple mutant was not obtained. Thus, in this study, we used two double mutants, pao1 pao5 and pao2 pao4. Of interest, pao1 pao5 mutant was NaCl- and drought-tolerant, whereas pao2 pao4 showed similar sensitivity to those stresses as WT. To reveal the underlying mechanism of salt tolerance, further analyses were performed. Na uptake of the mutant (pao1 pao5) decreased to 75% of WT. PAO activity of the mutant was reduced to 62% of WT. The content of reactive oxygen species (ROS) such as hydrogen peroxide, a reaction product of PAO action, and superoxide anion in the mutant became 81 and 72% of the levels in WT upon salt treatment. The mutant contained 2.8-fold higher thermospermine compared to WT. Moreover, the mutant induced the genes of salt overly sensitive-, abscisic acid (ABA)-dependent- and ABA-independent- pathways more strongly than WT upon salt treatment. The results suggest that the Arabidopsis plant silencing cytoplasmic PAOs shows salinity tolerance by reducing ROS production and strongly inducing subsets of stress-responsive genes under stress conditions.
Emergency Access to Protected Health Records

Digital Rights Management (DRM) schemes are receiving increased attention in the healthcare domain for the protection of sensitive health records as they offer security against insider attacks and advance protection features such as usage control. However, to be accepted by health care providers, a DRM solution has to fulfill specific healthcare requirements including emergency access. In this paper, we propose such DRM solution that can be deployed in highly distributed environments of electronic or personal health record infrastructures.
Incidental diagnosis of unilateral renal and adnexal agenesis in a 46-year-old multiparous woman

Patient: Female, 46 Final Diagnosis: Unilateral adneksial and renal agenesis Symptoms: Menometrorrhagia Medication: — Clinical Procedure: Total abdominal hysterectomy and unilateral salphingoopherectomy Specialty: Obstetrics and gynecology Objective: Rare disease Background: Unilateral renal and adnexal agenesis is quite rare. Absence of any uterine abnormality accompanying current urogenital abnormalities is even rarer. Case Report: We report on the case of a 46-year-old multiparous woman, incidentally diagnosed to have unilateral renal, ovarian, and tubal agenesis just before hysterectomy due to menometrorrhagia and myoma uteri. Conclusions: Any diagnosis of a urogenital abnormality necessitates investigation of comorbid renal or genital abnormalities.
Comparison of Optical Quality and Intraocular Scattering after Posterior Chamber Phakic Intraocular Lens with and without a Central Hole (Hole ICL and Conventional ICL) Implantation Using the Double-Pass Instrument

Purpose To objectively compare the optical quality and the intraocular scattering after implantation of the posterior chamber phakic implantable collamer lens (Visian ICL™, STAAR Surgical) with and without a central artificial hole for moderate to high ametropia. Methods This retrospective study comprised 28 eyes of 28 consecutive patients undergoing Hole ICL implantation (mean age ± standard deviation, 30.3±5.8 years), and 24 age-matched eyes of 24 patients undergoing conventional ICL implantation (age, 30.4±6.1 years). We quantitatively assessed the postoperative values of MTF cutoff frequency, Strehl ratio, objective scattering index (OSI), and OQAS values (OVs), using an Optical Quality Analysis System™. We compared these postoperative variables between the two groups. Results The mean MTF cutoff frequency, Strehl ratio, OSI, OV100%, OV 20%, and OV9%, were 26.21±8.32 cycles/degree, 0.16±0.04, 1.16±0.57, 0.87±0.28, 0.80±0.35, and 0.80±0.33, respectively, 3 months after Hole ICL implantation. We found no significant differences in the MTF cutoff frequency (Mann Whitney U test, p = 0.59), the Strehl ratio (p = 0.82), the OSI (p = 0.63), or the OVs at contrasts of 100% (p = 0.58), 20% (p = 0.40), and 9% (p = 0.87), between the two groups. Conclusions Both Hole ICL and conventional ICL implantation provides an excellent optical performance including intraocular scattering. Newly developed Hole ICL implantation appears to be essentially equivalent in the optical quality variables to conventional ICL implantation, suggesting that the presence of the central artificial hole does not significantly affect the optical quality and the intraocular scattering after surgery.
Distinguishing Paradigmatic Semantic Relations : Human Ratings and Distributional Similarity

Paradigmatic semantic relations such as synonymy, antonymy, hypernymy and (co-)hyponymy are central to the organisation of the mental lexicon (Miller & Fellbaum, 1991; Murphy, 2003; among others), by providing a structure for the lexical concepts that words express. The relational structure differs across word classes: According to Miller & Fellbaum (1991), “no single set of semantic relations [. ] is adequate for the entire lexicon: nouns, adjectives, and verbs each have their own semantic relations and their own organisation determined by the role they must play in the construction of linguistic messages. ” For example, while hypernymy is a natural relation for organising the noun lexicon, it is of minor importance for verbs, and unnatural for adjectives. In contrast, antonymy is considered the central relation for organising the adjective lexicon, and antonymy also plays a role in the mental lexicon for verbs, next to hypernymy, synonymy and entailment.
Normal and Compound Poisson Approximations for Pattern Occurrences in NGS Reads

Next generation sequencing (NGS) technologies are now widely used in many biological studies. In NGS, sequence reads are randomly sampled from the genome sequence of interest. Most computational approaches for NGS data first map the reads to the genome and then analyze the data based on the mapped reads. Since many organisms have unknown genome sequences and many reads cannot be uniquely mapped to the genomes even if the genome sequences are known, alternative analytical methods are needed for the study of NGS data. Here we suggest using word patterns to analyze NGS data. Word pattern counting (the study of the probabilistic distribution of the number of occurrences of word patterns in one or multiple long sequences) has played an important role in molecular sequence analysis. However, no studies are available on the distribution of the number of occurrences of word patterns in NGS reads. In this article, we build probabilistic models for the background sequence and the sampling process of the sequence reads from the genome. Based on the models, we provide normal and compound Poisson approximations for the number of occurrences of word patterns from the sequence reads, with bounds on the approximation error. The main challenge is to consider the randomness in generating the long background sequence, as well as in the sampling of the reads using NGS. We show the accuracy of these approximations under a variety of conditions for different patterns with various characteristics. Under realistic assumptions, the compound Poisson approximation seems to outperform the normal approximation in most situations. These approximate distributions can be used to evaluate the statistical significance of the occurrence of patterns from NGS data. The theory and the computational algorithm for calculating the approximate distributions are then used to analyze ChIP-Seq data using transcription factor GABP. Software is available online (www-rcf.usc.edu/∼fsun/Programs/NGS_motif_power/NGS_motif_power.html). In addition, Supplementary Material can be found online (www.liebertonline.com/cmb).
Complete camera calibration using spheres : A dual-space approach

Camera calibration is a fundamental problem in computer vision and photogrammetry. We present a new algorithm to calibrate cameras using spheres. In general, an occluding contour of a sphere projects to an ellipse in the image. Our algorithm uses the projection of the occluding contours of three spheres and solves for the intrinsic parameters and the locations of the spheres. The problem is formulated in the dual space and the parameters are solved for optimally and efficiently using semi-definite programming. The technique is flexible, accurate and easy to use. In addition, it can be used to simultaneously calibrate multiple cameras with a common field of view. Experimental results from computer simulated data and real world data, both for a single camera and multiple cameras, are presented.
A prospective study of CSF markers in 250 patients with possible Creutzfeldt–Jakob disease

Objective: To investigate various cerebrospinal fluid (CSF) markers that could assist in the clinical diagnosis of Creutzfeldt–Jakob disease (CJD). Methods: CSF samples were analysed for the presence of 14-3-3 protein, microtubule associated protein tau, and β amyloid in 250 patients with possible CJD. Densitometric analysis was used to quantify the level of 14-3-3 in all patients. Results: Analysis of the clinical data showed that cerebellar signs or myoclonus combined with progressive dementia were the main features leading to a clinical suspicion of CJD. While 14-3-3 detection had a sensitivity of 100% and a specificity of 92%, tau determination using a threshold of 1300 pg/ml had a sensitivity of 87% and a specificity of 97%. If the protocol for the analysis of 14-3-3 was modified (using densitometric analysis) a higher specificity (97%) could be obtained, but with a lower sensitivity (96%). Maximum sensitivity, specificity, and positive predictive value were obtained with a combination of 14-3-3 and β amyloid determinations. The concentrations of 14-3-3 and tau in the CSF were reduced in CJD patients with a long duration of disease (more than one year; p < 0.05). The concentrations of 14-3-3 or tau were lowest at the onset or at the end stage of the disease, while the β amyloid concentration remained low throughout the course of the disease. Conclusions: Both 14-3-3 and tau protein are sensitive and specific biomarkers for CJD. The combination of 14-3-3 and β amyloid analysis resulted in the maximum sensitivity, specificity, and positive predictive value. When these biomarkers are used in the diagnosis of CJD, the phase of the disease in which the CSF sample was obtained should be taken into account. Disease duration, dependent on the PrP genotype, also has a significant influence on the level of 14-3-3 and tau in the CSF.
Non-even spread NSGA-II and its application to conflicting multi-objective compatible control

Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is a sound method to deal with the multi-objective optimization problem, and even spread Pareto front preserving strategy is one of its two key principles. However, especially for some dynamic problems, the most interested area is certain special area among the Pareto front. To meet this requirement, the non-even Pareto front spread preserving principle is proposed and is taken as the optimization tool for the multi-objective compatible control problem (MOCCP). To decrease the real-time computation load at every control step, based on the tight relation between the system states of the neighboring sampling instants, an iterative control algorithm is presented. The stability preference selection strategy in the algorithm tends to produce a stable controller in face of the Pareto front with the divergent or oscillating segment. To further decrease the computation time, adaptable population corresponding with the control process is adopted. Comparative simulation example illustrates the validity.
A 58 nW ECG ASIC With Motion-Tolerant Heartbeat Timing Extraction for Wearable Cardiovascular Monitoring

An ASIC for wearable cardiovascular monitoring is implemented using a topology that takes advantage of the electrocardiogram's (ECG) waveform to replace the traditional ECG instrumentation amplifier, ADC, and signal processor with a single chip solution. The ASIC can extract heartbeat timings in the presence of baseline drift, muscle artifact, and signal clipping. The circuit can operate with ECGs ranging from the chest location to remote locations where the ECG magnitude is as low as 30 μV. Besides heartbeat detection, a midpoint estimation method can accurately extract the ECG R-wave timing, enabling the calculations of heart rate variability. With 58 nW of power consumption at 0.8 V supply voltage and 0.76 mm 2 of active die area in standard 0.18 μm CMOS technology, the ECG ASIC is sufficiently low power and compact to be suitable for long term and wearable cardiovascular monitoring applications under stringent battery and size constraints.
A Unified Theory of Density Models and Auto-Encoders ∗

This report introduces an objective function for simultaneously optimising the density model and transition matrices of a Markov source. The chosen objective function seeks to minimise the average total number of bits that is required to encode the joint state of the Markov source. This may be applied to the problem of optimising the bottomup (recognition model) and top-down (generative model) connections in a multilayer neural network. This approach unifies many previous results on the optimisation of multilayer unsupervised neural networks.
Faceted Bug Report Search with Topic Model

During bug reporting, The same bugs could be repeatedly reported. As a result, extra time could be spent on bug triaging and fixing. In order to reduce redundant effort, it is important to provide bug reporters with the ability to search for previously reported bugs efficiently and accurately. The existing bug tracking systems are using relatively simple ranking functions, which often produce unsatisfactory results. In this paper, we apply Ranking SVM, a Learning to Rank technique to construct a ranking model for accurate bug report search. Based on the search results, a topic model is used to cluster the bug reports into multiple facets. Each facet contains similar bug reports of the same topic. Users and testers can locate relevant bugs more efficiently through a simple query. We perform evaluations on more than 16,340 Eclipse and Mozilla bug reports. The evaluation results show that the proposed approach can achieve better search results than the existing search functions.