Miracle-dz/UniFAR-FTUs huggingface dataset:
Artificial Neural Networks Analysis of Surface-Enhanced Laser Desorption/Ionization Mass Spectra of Serum Protein Pattern Distinguishes Colorectal Cancer from Healthy Population

Purpose: The low specificity and sensitivity of the carcinoembryonic antigen test makes it not an ideal biomarker for the detection of colorectal cancer. We developed and evaluated a proteomic approach for the simultaneous detection and analysis of multiple proteins for distinguishing individuals with colorectal cancer from healthy individuals. Experimental Design: We subjected serum samples (including 55 colorectal cancer patients and 92 age- and sex-matched healthy individuals) from 147 individuals, for analysis by surface-enhanced laser desorption/ionization (SELDI) mass spectrometry. Peaks were detected with Ciphergen SELDI software version 3.0. Using a multilayer artificial neural network with a back propagation algorithm, we developed a classifier for separating the colorectal cancer groups from the healthy groups. Results: The artificial neural network classifier separated the colorectal cancer from the healthy samples, with a sensitivity of 91% and specificity of 93%. Four top-scored peaks, at m/z of 5,911, 8,930, 8,817, and 4,476, were finally selected as the potential “fingerprints” for detection of colorectal cancer. Conclusions: The combination of SELDI-TOF mass spectrometry with the artificial neural networks in the analysis of serum protein yields significantly higher sensitivity and specificity values for the detection and diagnosis of colorectal cancer.
Explanation-Based Generalization of Infeasible Path

Recent code-based test input generators based on dynamic symbolic execution increase path coverage by solving path condition with a constraint or an SMT solver. When the solver considers path condition produced from an infeasible path, it tries to show unsatisfiability, which is a useless time-consuming process. In this paper, we propose a new method that takes opportunity of the detection of a single infeasible path to generalize to a (possibly infinite) family of infeasible paths, which will not have to be considered in further path conditions solving. The method exploits non-intrusive constraint-based explanations, a technique developed in Constraint Programming to explain unsatisfiability. Experimental results obtained with our prototype tool IPEG show that, whatever is the underlying constraint solving procedure (IC, Colibri and the SMT solver Z3), this approach can save considerable computational time.
Microscale spatial heterogeneity of protein structural transitions in fibrin matrices

Mechanical loading of fibrin biomaterials induces spatial heterogeneity in protein molecular structure on the microscale. Following an injury, a blood clot must form at the wound site to stop bleeding before skin repair can occur. Blood clots must satisfy a unique set of material requirements; they need to be sufficiently strong to resist pressure from the arterial blood flow but must be highly flexible to support large strains associated with tissue movement around the wound. These combined properties are enabled by a fibrous matrix consisting of the protein fibrin. Fibrin hydrogels can support large macroscopic strains owing to the unfolding transition of α-helical fibril structures to β sheets at the molecular level, among other reasons. Imaging protein secondary structure on the submicrometer length scale, we reveal that another length scale is relevant for fibrin function. We observe that the protein polymorphism in the gel becomes spatially heterogeneous on a micrometer length scale with increasing tensile strain, directly showing load-bearing inhomogeneity and nonaffinity. Supramolecular structural features in the hydrogel observed under strain indicate that a uniform fibrin hydrogel develops a composite-like microstructure in tension, even in the absence of cellular inclusions.
Define a function on gene order of DNA microarray data and use it to identify genes associated with Alzheimer's disease

Alzheimer's disease (AD) is the most ordinary kind of dementia. Identifying genes associated with AD is a new topic, and the key is to design algorithm to search AD genes. Gene order is a permutation of genes in which similar genes are ordered together. In this paper, a function is defined on gene order, and function value measures the similarity degree between a gene and its neighbors. Through the function value, the neighbors of a gene can be identified. The genes keeping as neighbor of AD gene (APOE, presenilins 1 or 2) at any stage (control, incipient, moderate, severe) are identified as the candidate of the gene associated with AD, where AD gene has been proved acting risk factor of AD. Experiment results of this paper have been proved some genes associated with AD.
Coupling delay optimization by temporal decorrelation using dual threshold voltage technique

Coupling effect due to line-to-line capacitance is of serious concern in timing analysis of circuits in ultra deep submicron CMOS technology. Often coupling delay is strongly dependent on temporal correlation of signal switching in relevant wires. Temporal decorrelation by shifting timing window can alleviate performance degradation induced by tight coupling. This paper presents an algorithm for minimizing circuit delay through timing window modulation in dual V/sub t/ technology. Experimental results on the ISCAS85 benchmark circuits indicate that the critical delay will be reduced significantly when low V/sub t/ is applied properly.
A critique of reporting on ethical, social and environmental issues: the case of ICI

The purpose of this paper is twofold. Firstly, it assesses the extent to which corporate reporting on ethical, social and environmental issues reflects corporate performance in ICI. This ‘reporting-performance’ gap is a key measure of the extent to which an organisation is accountable to its stakeholders. ICI’s disclosures concerning its ethical, social and environmental performance for the years 1993 and 1999 were compared with information obtained on ICI’s performance from other sources. Two very different pictures of performance emerged leading to the conclusion that ICI reports do not demonstrate accountability. Of particular concern is the lack of completeness of reporting. Secondly, the paper assesses the potential of recent standards or guidelines developed by the Global Reporting Initiative and the Institute of Social and Ethical Accountability as well as the chemical industry’s own ‘Responsible Care’ initiative to reduce this ‘reporting-performance’ gap and improve corporate accountability.
A systematic review and meta-analysis of familial colorectal cancer risk

OBJECTIVE:The aim of this study was to identify published studies quantifying familial colorectal cancer (CRC) risks in first-degree relatives of CRC and colorectal adenoma (CRA) cases and, through a meta-analysis, obtain more precise estimates of familial risk according to the nature of the family history and type of neoplasm.METHODS:Twenty-seven case-control and cohort studies were identified, which reported risks of CRC in relatives of CRC cases and nine, which reported the risk of CRC in relatives of CRA cases. Pooled estimates of risk for various categories of family history were obtained by calculating the weighted average of the log relative risk estimates from studies.RESULTS:The pooled estimates of relative risk were as follows: a first-degree relative with CRC 2.25 (95% CI = 2.00–2.53), colon 2.42 (95% CI = 2.20–2.65), and rectal 1.89 (95% CI = 1.62–2.21) cancer; parent with CRC 2.26 (95% CI = 1.87–2.72); sibling with CRC 2.57 (95% CI = 2.19–3.02); more than one relative with CRC 4.25 (95% CI = 3.01–6.08); relative diagnosed with CRC before age 45, 3.87 (95% CI = 2.40–6.22); and a relative with CRA 1.99 (95% CI = 1.55–2.55). CONCLUSIONS:Individuals with a family history of CRC and CRA have a significantly elevated risk of developing CRC compared with those without such a history. Risks are greatest for relatives of patients diagnosed young, those with two or more affected relatives, and relatives of patients with colonic cancers.
Atomic Scale Characterization of LSFMO Thin Films Using Aberration Corrected STEM

Superlattices consisting of ferromagnetic metal La (1-x) Sr x MnO 3 (LSMO) and the antiferromagnetic insulator La (1-x) Sr x FeO 3 (LSFO) a of for their potential application as next generation data storage materials. this epitaxial thin films of the LSMO/LSFO solid solution, La 0.3 Sr 0.7 Fe 0.5 Mn 0.5 O 3 (LSFMO), were grown on single crystal LaAlO 3 (LAO) substrates by pulsed laser These are chemically equivalent to the LSMO/LSFO superlattices but without the presence of the high density of interfaces. Previous studies show that Fe doping in LSMO bulk crystal suppresses on the conduction and ferromagnetism and changes the density of states near Fermi level. performed a detailed characterization of the atomic structure of LSFMO thin films by combining dark field and bright field images acquired simultaneously by an aberration-corrected scanning transmission electron microscopy (STEM).
Super-Resolution Channel Estimation for mmWave Massive MIMO

Millimeter-wave massive MIMO with hybrid precoding can significantly reduce the number of required radio frequency (RF) chains. However, due to the limited number of RF chains, the requirement of large pilot overhead will be used to estimate the high-dimensional mmWave massive MIMO channel. To solve this problem, we propose a super-resolution channel estimation scheme based on modified two- dimensional (2D) unitary ESPRIT algorithm in this paper, which can jointly estimate the continuously distributed angle of arrivals/departures (AoAs/AoDs) with high accuracy. Specifically, we first estimate a low-dimensional effective channel by designing the uplink training signals. Then, since the low- dimensional effective channel has the same shift- invariance of array response as the highdimensional mmWave MIMO channel to be estimated, we jointly estimate the super-resolution estimates of AoAs and AoDs by exploiting the modified 2D unitary ESPRIT algorithm. Furthermore, we can obtain the associated path gains based on the least squares (LS) criterion. Finally, the high-dimensional mmWave MIMO channel will be reconstructed according to the obtained parameters. Simulation results verify that the proposed scheme is more accuracy than conventional schemes, even with a much lower pilot overhead.
Human Urine Proteomics: Analytical Techniques and Clinical Applications in Renal Diseases

Urine has been in the center of attention among scientists of clinical proteomics in the past decade, because it is valuable source of proteins and peptides with a relative stable composition and easy to collect in large and repeated quantities with a noninvasive procedure. In this review, we discuss technical aspects of urinary proteomics in detail, including sample preparation, proteomic technologies, and their advantage and disadvantages. Several recent experiments are presented which applied urinary proteome for biomarker discovery in renal diseases including diabetic nephropathy, immunoglobulin A (IgA) nephropathy, focal segmental glomerulosclerosis, lupus nephritis, membranous nephropathy, and acute kidney injury. In addition, several available databases in urinary proteomics are also briefly introduced.
Calculating confidence intervals for continuous and discontinuous functions of parameters

Applied researchers often need to estimate confidence intervals for functions of parameters, such as the effects of counterfactual policy changes. If the function is continuously differentiable and has non-zero and bounded derivatives, then they can use the delta method. However, if the function is nondifferentiable (as in the case of simulating functions with zero-one outcomes), has zero derivatives, or unbounded derivatives, then researchers usually use the nonparametric bootstrap or sample from the asymptotic distribution of the estimated parameter vector. Researchers also use these bootstrap approaches when the function is well-behaved but complicated. Indeed, these approaches are advocated by two very influential published articles. We first show that both of these bootstrap procedures can produce confidence intervals whose asymptotic coverage is less than advertised, i.e. confidence intervals that are too small. We then propose two procedures that provide correct coverage. In applications, we find that the bootstrap approaches mentioned above produce confidence intervals that are significantly smaller than their consistent counterparts, suggesting that previous empirical work is likely to have been overly optimistic in terms of the precision of estimated counterfactual effects.
Stochastic Interchange Scheduling in the Real-Time Electricity Market

The problem of inter-regional interchange scheduling in the presence of stochastic generation and load is considered. An interchange scheduling technique based on a two-stage stochastic minimization of expected operating cost is proposed. Because directly solving the stochastic optimization is intractable, an equivalent problem that maximizes the expected social welfare is formulated. The proposed technique leverages the operator's capability of forecasting locational marginal prices and obtains the optimal interchange schedule without iterations among operators. Several extensions of the proposed technique are also discussed.
MinJ (YvjD) is a topological determinant of cell division in Bacillus subtilis

In Bacillus subtilis, FtsZ ring formation and cell division is favoured at the midcell because the inhibitor proteins MinC and MinD are indirectly restricted to the cell poles by the protein DivIVA. Here we identify MinJ, a topological determinant of medial FtsZ positioning that acts as an intermediary between DivIVA and MinD. Due to unrestricted MinD activity, cells mutated for minJ exhibited pleiotropic defects in homologous recombination, swarming motility and cell division. MinJ restricted MinD activity by localizing MinD to the cell poles through direct protein–protein interaction. MinJ itself localized to cell poles in a manner that was dependent on DivIVA. MinJ is conserved in other low G+C Gram‐positive bacteria and may be an important component of cell division site selection in these organisms.
Fuzzy control of stochastic global optimization algorithms and very fast simulated rean- nealing

This paper presents a fuzzy control approach for improving convergence time in stochastic global minimization algorithms . We show concrete results when the method is applied to an efficient algorithm based on ideas related to Simulated Annealing.We describe a well-succeeded approach to accelerate ASA (Adaptive Simulated Annealing) algorithm using a simple Mamdani fuzzy controller that dynamically adjusts certain user parameters related to quenching. It is shown that, by increasing the algorithm’s perception of slow convergence, it is possible to speed it up significantly and to reduce enormously (perhaps eliminate) the user task of parameter tuning . That is done without changing the original ASA code . The algorithm was sucessfully applied to neurofuzzy (data driven) synthesis of Takagi-Sugeno-Kang and Mamdani fuzzy systems and MLE (Maximum Likelihood Estimation).
Threshold powers and delays for igniting propane and butane-air mixtures by cw laser-heated small particles

The National Institute for Occupational Safety and Health, Pittsburgh Research Laboratory conducted a study of laser safety in potentially flammable environments. Researchers measured threshold igniting powers as a function of beam diameter for butane and propane-air mixtures by laser-heating targets placed on optical fiber tips using a 1064 nm laser. The minimum igniting powers for propane-air and butane-air were about 250 and 300 mW, respectively. Threshold igniting powers for propane-air were approximately proportional to beam diameter for beam diameters from 0.1 to 2.0 mm. Results suggest that relatively powerful beams may be used in these atmospheres without causing ignition, provided the beam diameter is controlled. Threshold ignition delay times using 9/125 and 62.5/125 μm fibers were approximately proportional to the inverse square of the laser power. Ignition delays were about 45 ms or longer for laser powers up to 800 mW. Preproduction samples of a commercial optical fuse prevented ignitions und.
Markov-based reordering model for English-Myanmar translation

In statistical machine translation, reordering is crucial component for translation of the different languages with different word orders. Without reordering during language translation, sentences can only be translated properly into a language with similar word order. An effective reordering scheme is essential to model translation between languages with different word orders, such as SVO-languages (English or Chinese) and SOV-languages (Japanese or Turkish or Myanmar). Our Language, Myanmar is a verb final language and reordering is needed when it is translated from other languages with different orders. In this paper, we focus on reordering rule generation and Markov-based reordering model implementation that can be incorporated into our English-Myanmar translation model. Parallel tagged aligned corpus is used as a resource for reordering rule generation and First Order Markov theory is applied for reordering model. Moreover, the alignment parameters for the reordering model are taken from the reordering rules automatically extracted from parallel tagged aligned corpus.
Semantic Cross-View Matching

Matching cross-view images is challenging because the appearance and viewpoints are significantly different. While low-level features based on gradient orientations or filter responses can drastically vary with such changes in viewpoint, semantic information of images however shows an invariant characteristic in this respect. Consequently, semantically labeled regions can be used for performing cross-view matching. In this paper, we therefore explore this idea and propose an automatic method for detecting and representing the semantic information of an RGB image with the goal of performing cross-view matching with a (non-RGB) geographic information system (GIS). A segmented image forms the input to our system with segments assigned to semantic concepts such as traffic signs, lakes, roads, foliage, etc. We design a descriptor to robustly capture both, the presence of semantic concepts and the spatial layout of those segments. Pairwise distances between the descriptors extracted from the GIS map and the query image are then used to generate a shortlist of the most promising locations with similar semantic concepts in a consistent spatial layout. An experimental evaluation with challenging query images and a large urban area shows promising results.
This Work Is Licensed under a Creative Commons Attribution 4.0 International License Date Deposited: Single Unit Action Potentials in Humans and the Effect of Seizure Activity

permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Spike-sorting algorithms have been used to identify the firing patterns of isolated neurons ('single units') from implanted electrode recordings in patients undergoing assessment for epilepsy surgery, but we do not know their potential for providing helpful clinical information. It is important therefore to characterize both the stability of these recordings and also their context. A critical consideration is where the units are located with respect to the focus of the pathology. Recent analyses of neuronal spiking activity, recorded over extended spatial areas using microelectrode arrays, have demonstrated the importance of considering seizure activity in terms of two distinct spatial territories: the ictal core and penumbral territories. The pathological information in these two areas, however, is likely to be very different. We investigated, therefore, whether units could be followed reliably over prolonged periods of times in these two areas, including during seizure epochs. We isolated unit recordings from several hundred neurons from four patients undergoing video-telemetry monitoring for surgical evaluation of focal neocortical epilepsies. Unit stability could last in excess of 40 h, and across multiple seizures. A key finding was that in the penumbra, spike stereotypy was maintained even during the seizure. There was a net tendency towards increased penumbral firing during the seizure, although only a minority of units (10–20%) showed significant changes over the baseline period, and notably, these also included neurons showing significant reductions in firing. In contrast, within the ictal core territories, regions characterized by intense hypersyn-chronous multi-unit firing, our spike sorting algorithms failed as the units were incorporated into the seizure activity. No spike sorting was possible from that moment until the end of the seizure, but recovery of the spike shape was rapid following seizure termination: some units reappeared within tens of seconds of the end of the seizure, and over 80% reappeared within 3 min (recov = 104 AE 22 s). The recovery of the mean firing rate was close to pre-ictal levels also within this time frame, suggesting that the more protracted post-ictal state cannot be explained by persistent cellular neurophysiological dysfunction in either the pen-umbral or the core territories. These studies lay the foundation for future investigations of how these recordings may inform clinical practice. distribution, and reproduction in any medium, provided the original work is properly cited.
Porcine Streptococcus Suis in Minnesota

the number of new water acres used for catfish production in the delta region of west-central Mississippi. This increase in production was reflected by the establishment of the fish health diagnostic laboratory at Belzoni in June 1986 and the subsequent increase in the aquatic diagnostic case load of the Mississippi Cooperative Extension Service. The fish health diagnostic laboratory case load has remained relatively constant since 1986, which may reflect a decreasing growth rate of this industry in Mississippi or failure of producers to seek diagnostic laboratory support. However, the industry continues to expand within Mississippi and in adjoining states and other areas of the country. Bacterial diseases continue to be a major economic factor for commercial catfish farmers. Motile Aeromonas septicemia, columnar-is disease (Cytophaga spp.), and enteric septicemia of catfish (E. ictaluri) were the most prevalent bacterial diseases identified. During epizootics, early and accurate disease diagnosis is critical to catfish producers to minimize losses. Affected fish frequently eat less and thus have limited exposure to antimicrobials. Therapeutic administration of antibiotics is expensive and too frequently is not cost effective. Therefore, prevention of diseases by minimizing stress and exposure to pathogens is the best management strategy. Acknowledgements. We acknowledge Dr. T. E. Wellbom for the development of, implementation of, and perseverance in maintaining the quality of this data base. T. E. Schwedler, Rachel H. Josey, and Virgie L. Freund were instrumental in maintaining collection and entry of these data. We thank Paula Rogers and Debbie Wright for assistance in preparation of this manuscript, which is submitted as publication #J-7773, Mississippi Agriculture and Forestry Experiment Station, Mississippi State, MS.