Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical trial designs for predictive biomarker validation: theoretical considerations and practical challenges.

PURPOSE Biomarkers can add substantial value to current medical practice by providing an integrated approach to prediction using the genetic makeup of the tumor and the genotype of the patient to guide patient-specific treatment selection. We discuss and evaluate various clinical trial designs for the validation of biomarker-guided therapy. METHODS Designs for predictive marker validation are broadly classified as retrospective (ie, using data from previously well-conducted randomized controlled trials [RCTs]) versus prospective (enrichment, unselected, hybrid, or adaptive analysis). We discuss the salient features of each design in the context of real trials. RESULTS Well-designed retrospective analysis from well-conducted prospective RCTs can bring forward effective treatments to marker-defined subgroups of patients in a timely manner (eg, KRAS and colorectal cancer). Enrichment designs are appropriate when preliminary evidence suggest that patients with or without that marker profile do not benefit from the treatments in question; however, this may sometimes leave questions unanswered (eg, trastuzumab and breast cancer). An unselected design is optimal where preliminary evidence regarding treatment benefit and assay reproducibility is uncertain (eg, epidermal growth factor receptor and lung cancer). Hybrid designs are appropriate when preliminary evidence demonstrate the efficacy of certain treatments for a marker-defined subgroup, making it unethical to randomly assign patients with that marker status to other treatments (eg, multigene assay and breast cancer). Adaptive analysis designs allow for prespecified marker-defined subgroup analyses of data from an RCT. CONCLUSION The implementation of these design strategies will lead to a more rapid clinical validation of biomarker-guided therapy.
Solitons and admissible families of rational curves in twistor spaces

It is well known that twistor constructions can be used to analyse and to obtain solutions to a wide class of integrable systems. In this paper we express the standard twistor constructions in terms of the concept of an admissible family of rational curves in certain twistor spaces. Examples of such families can be obtained as subfamilies of a simple family of rational curves using standard operations of algebraic geometry. By examination of several examples, we give evidence that this construction is the basis of the construction of many of the most important solitonic and algebraic solutions to various integrable differential equations of mathematical physics. This is presented as evidence for a principle that, in some sense, all soliton-like solutions should be constructable in this way.
Thermodynamic Origin of Photoinstability in the CH3NH3Pb(I1–xBrx)3 Hybrid Halide Perovskite Alloy

The formation of solid-solutions of iodide, bromide, and chloride provides the means to control the structure, band gap, and stability of hybrid halide perovskite semiconductors for photovoltaic applications. We report a computational investigation of the CH3NH3PbI3/CH3NH3PbBr3 alloy from density functional theory with a thermodynamic analysis performed within the generalized quasi-chemical approximation. We construct the phase diagram and identify a large miscibility gap, with a critical temperature of 343 K. The observed photoinstability in some mixed-halide solar cells is explained by the thermodynamics of alloy formation, where an initially homogeneous solution is subject to spinodal decomposition with I and Br-rich phases, which is further complicated by a wide metastable region defined by the binodal line.
PATTERNS OF PARAPATRIC SPECIATION

Abstract Geographic variation may ultimately lead to the splitting of a subdivided population into reproductively isolated units in spite of migration. Here, we consider how the waiting time until the first split and its location depend on different evolutionary factors including mutation, migration, random genetic drift, genetic architecture, and the geometric structure of the habitat. We perform large-scale, individual-based simulations using a simple model of reproductive isolation based on a classical view that reproductive isolation evolves as a by-product of genetic divergence. We show that rapid parapatric speciation on the time scale of a few hundred to a few thousand generations is plausible even when neighboring subpopulations exchange several individuals each generation. Divergent selection for local adaptation is not required for rapid speciation. Our results substantiates the claims that species with smaller range sizes (which are characterized by smaller local densities and reduced dispersal ability) should have higher speciation rates. If mutation rate is small, local abundances are low, or substantial genetic changes are required for reproductive isolation, then central populations should be the place where most splits take place. With high mutation rates, high local densities, or with moderate genetic changes sufficient for reproductive isolation, speciation events are expected to involve mainly peripheral populations. Corresponding Editor: A. Caballero
Methods for Studying Group Interactions in HRI

In recent years, we have conducted several Human-Robot Interaction (HRI) experiments with small groups of people. To do so, we developed four diﬀerent protocols to investigate human spatial behavior or trust in robots. We now look back at these eﬀorts and highlight the opportunities and challenges of each experimental method. We also describe various group phenomena that we observed during the interactions. By sharing our experience, we hope to inform the community of the lessons that we learned in HRI and emphasize the importance of studying group interactions to enable robots to operate in public human environments.
A new approach for evaluating clipping distortion in multicarrier systems

Multicarrier signals are known to suffer from a high peak-to-average power ratio, caused by the addition of a large number of independently modulated subcarriers in parallel at the transmitter. When subjected to a peak-limiting channel, such as a nonlinear power amplifier, these signals may undergo significant spectral distortion, leading to both in-band and out-of-band interference, and an associated degradation in system performance. This paper characterizes the distortion caused by the clipping of multicarrier signals in a peak-limiting (nonlinear) channel. Rather than modeling the effects of distortion as additive noise, as is widespread in the literature, we identify clipping as a rare event and focus on evaluating system performance based on the conditional probability of bit error given the occurrence of such an event. Our analysis is based on the asymptotic properties of the large excursions of a stationary Gaussian process, and offers important insights into both the true nature of clipping distortion, as well as the consequent design of schemes to alleviate this problem.
An exogenous mouse mammary tumor virus with properties of Mls-1a (Mtv- 7)

The classical minor lymphocyte stimulating (Mls) antigens, which induce a strong primary T cell response in vitro, are closely linked to endogenous copies of mouse mammary tumor viruses (MMTV). Expression of Mls genes leads to clonal deletion of T cell subsets expressing specific T cell receptor (TCR) V beta chains. We describe the isolation and characterization of a new exogenous (infectious) MMTV with biological properties similar to the Mls antigen Mls-1a. In vivo administration of either Mls-1a-expressing B cells or the infectious MMTV (SW) led to an increase of T cells expressing V beta 6 followed by their deletion. Surprisingly, different kinetics of deletion were observed with the exogenous virus depending upon the route of infection. Infection through the mucosa led to a slow deletion of V beta 6+ T cells, whereas deletion was rapid after subcutaneous infection. Sequence analysis of the open reading frames in the 3' long terminal repeat of both this exogenous MMTV (SW) and of Mtv-7 (which is closely linked to Mls-1a) revealed striking similarities, particularly in the COOH terminus, which has been implicated in TCR V beta recognition. The identification of an infectious MMTV with the properties of a strong Mls antigen provides a new, powerful tool to study immunity and tolerance in vivo.
MIMO channel estimation in spatially correlated environments

We present in this paper a novel model-based scheme for estimating MIMO block fading channels. The proposed method can be applied to estimate the conventional independent and identically distributed (i.i.d.) complex Gaussian as well as the more realistic spatial-correlated channels. Excellent mean squared identification error (MSIE) performance can be attained with proper designed system parameters. We also derive an adaptive least squares (RLS) version that can be used for estimating a static channel or tracking time-varying channels. Furthermore, when the angle spread (AS) at the transmit site is small and thus the correlations amongst the transmit antennas are high, we show that it is possible to extract the information about the transmitter's angle of departure (AOD) for potential postprocessing applications.
Consistent code generation from UML models

Relational calculus of object systems (rCOS) is an OO-language which is equipped with an observation-oriented semantics and a refinement calculus based on the Hoare and He's unifying theories of programming (UTP). In this paper, we give syntactic definitions for class diagrams and sequence diagrams in UML 2.0. Based on these definitions, we give an algorithm for checking the consistency of a class diagram and a sequence diagram. Furthermore, we develop an algorithm to generate rCOS code from any given consistent class diagram and sequence diagram.
Biodiversity's Big Wet Secret: The Global Distribution of Marine Biological Records Reveals Chronic Under-Exploration of the Deep Pelagic Ocean

Background Understanding the distribution of marine biodiversity is a crucial first step towards the effective and sustainable management of marine ecosystems. Recent efforts to collate location records from marine surveys enable us to assemble a global picture of recorded marine biodiversity. They also effectively highlight gaps in our knowledge of particular marine regions. In particular, the deep pelagic ocean – the largest biome on Earth – is chronically under-represented in global databases of marine biodiversity. Methodology/Principal Findings We use data from the Ocean Biogeographic Information System to plot the position in the water column of ca 7 million records of marine species occurrences. Records from relatively shallow waters dominate this global picture of recorded marine biodiversity. In addition, standardising the number of records from regions of the ocean differing in depth reveals that regardless of ocean depth, most records come either from surface waters or the sea bed. Midwater biodiversity is drastically under-represented. Conclusions/Significance The deep pelagic ocean is the largest habitat by volume on Earth, yet it remains biodiversity's big wet secret, as it is hugely under-represented in global databases of marine biological records. Given both its value in the provision of a range of ecosystem services, and its vulnerability to threats including overfishing and climate change, there is a pressing need to increase our knowledge of Earth's largest ecosystem.
Dynamic role assignment for cooperative robots

Proposes a methodology for coordinating multi-robot teams in the execution of cooperative tasks. It is based on a dynamic role-assignment mechanism in which the robots assume and exchange roles during cooperation. We model the role assignment under a hybrid systems framework, using a hybrid automaton to represent roles, transitions and controllers. Using a multi-robot simulator, the methodology is demonstrated in a cooperative transportation task, in which a group of robots must find and cooperatively transport several objects scattered in the environment.
Signs of myocardial ischemia on electrocardiogram correlate with elevated plasma cardiac troponin and right ventricular systolic dysfunction in acute pulmonary embolism.

BACKGROUND Plasma cardiac troponins (cTn) are frequently elevated in acute pulmonary embolism (APE). ST-segment abnormalities on electrocardiography are also commonly observed in APE patients. However, it has not been defined which ventricle is a potential source of cTn release. We assessed the potential relationship between electrocardiographic signs of myocardial ischemia, systolic dysfunction of both ventricles at echocardiography and cTn levels in APE. METHODS We evaluated 94 consecutive patients (42 male, 52 female, aged 63 +/- 19 years) with APE. On admission, blood samples were collected for cTnI or cTnT and standard 12-lead electrocardiogram was performed. The following signs of myocardial ischemia were analyzed: T-wave inversion [T (-)] and ST-depression or elevation (> or = 1 mV, at > or = 2 leads). The assessment of systolic function of both ventricles was performed by echocardiography. RESULTS In 33 (35%) patients, cTn exceeded the upper reference limit of our laboratory. The history of coronary artery disease (27% vs. 31%) and previous myocardial infarction (12% vs. 10%) did not differ in patients with elevated cTn [cTn (+)] and non-elevated cTn [cTn (-)]. In cTn (+) group T (-) or ST-depression were observed more frequently than in cTn (-) [32 (97%) vs. 46 (75%), p < 0.01]. However, both groups presented similar frequency of ST-elevation [7 (21%) vs. 11 (18%), p = NS). Interestingly, cTn levels correlated with the number of leads with T (-) or ST-depression (R = 0.30, p < 0.01). Moreover, in cTn (+) group right ventricular systolic dysfunction was more frequent [15 (54%) vs. 4 (7%), p = 0.0001], while left ventricle contractility abnormalities occurred similarly in both groups [3 (11%) vs. 8 (15%), p = NS]. CONCLUSIONS Signs of myocardial ischemia (ST-segment changes) on electrocardiography in APE correlate with an elevated cTn and with the impairment of right, but not left, ventricle systolic function at echocardiography.
Convolution Kernels for Subjectivity Detection

In this paper, we explore different linguistic structures encoded as convolution kernels for the detection of subjective expressions. The advantage of convolution kernels is that complex structures can be directly provided to a classifier without deriving explicit features. The feature design for the detection of subjective expressions is fairly difficult and there currently exists no commonly accepted feature set. We consider various structures, such as constituency parse structures, dependency parse structures, and predicateargument structures. In order to generalize from lexical information, we additionally augment these structures with clustering information and the task-specific knowledge of subjective words. The convolution kernels will be compared with a standard vector kernel.
Simultaneous Analysis of Time and Space for Conflict Detection in Time-Based Firewall Policies

Firewalls are one of the most deployed mechanisms to protect the network from unauthorized access and security threats. However, maintenance of firewall policy is an error-prone and complicated task for a dynamic network environment. Conflict is a misconfiguration that happens when a packet matches two or more filters resulting in shadowing and redundancy of the filters. Network administrators reconfigure the filters to minimize the effect of conflicts, as the filters do not reflect for what it was intended. Nowadays, time-based filters are used in CISCO firewalls and LINUX Iptables to control network traffic in time. Conflict occurs when a packet matches two or more time-based filters active in the same timing. Detection of conflicts in time-based filters is necessary, because the existing conflict detection techniques turns ineffective, as analysis of filters in time is not considered. This problem is not been addressed in research regardless of its significance. To resolve it, in this paper, we propose an n+1 dimensional approach (n refers the number of key fields in a packet header) to detect conflicts by analyzing time and space simultaneously. We compute characterization vectors to detect the conflicting filters which discards the non-conflicting filters in the initial stage of computation and remove the unnecessary steps. Further, we implemented a prototype system and conducted experiments on time-based filters with and without considering time. We found that approximately 50% of conflicting filters becomes non-conflicting when time is considered. Hence, our conflict detection system for time-based filters reduces the workload of the administrator as the filters for reconfiguration is considerably reduced.
Induction of apoptosis by diethylstilbestrol in hormone-insensitive prostate cancer cells.

BACKGROUND Diethylstillbestrol (DES) and diethylstilbestrol diphosphate (DESdP) are effective agents for the treatment of advanced prostate cancers. Tumor-inhibiting effects of DES and DESdP are presumed secondary to suppression of androgen production in vivo. Little is known, however, about the direct cellular mechanisms of the tumor inhibition. Estrogens have been reported not only to stimulate growth but also to disrupt microtubule formation in prostate cancer cells. PURPOSE The study was designed to examine and compare mechanisms of in vitro growth inhibition of DES and DESdP in human androgen-insensitive prostate cancer cells (DU145, 1-LN, and PC-3) and human androgen-sensitive prostate cancer cells (LNCaP) and to examine estrogen receptor modulation of such effects. METHODS The cytotoxic effects of DES and DESdP were examined in vitro by use of a standard microculture tetrazolium assay to quantitate numbers of viable cells. Immunofluorescence microscopy, DNA fragmentation analysis, and fluorescence flow cytometry were used to investigate microtubules, the induction of apoptosis, and changes in cell cycle distribution. The degree of estrogen receptor positivity of untreated and treated cells was determined by immunohistochemistry and quantitative image analysis. RESULTS LD50 levels (the dose at which 50% of cells are no longer viable) in the concentration range of 19-25 microM were observed for both DES and DESdP in all cell lines examined. DESdP-induced growth inhibition was found to be dependent on heat-labile phosphatases present in fetal calf serum. DES-induced cytotoxicity was not affected by the presence of 17 beta-estradiol, and it was not dependent on the presence of estrogen receptor. Estrogen receptor-positive cells and estrogen receptor-negative cells were equally responsive to DES. PC-3 cells stained with fluorescent anti-tubulin, phalloidin (actin stain), and 4',6-diamidino-2-phenylindole (DNA stain) showed no inhibition of microtubules or actin filaments but revealed the presence of apoptotic bodies in the nuclei. Fluorescence flow cytometry of nuclear DNA content of propidium iodide-stained nuclei from androgen-insensitive prostate cancer cells treated with 15 or 30 microM DES or DESdP revealed an increase in relative numbers of hypodiploid (apoptotic) nuclei, a depletion of G1- and S-phase cells, and an accumulation of cells in G2/M phase. Conversely, androgen-sensitive cells contained a lower percentage of hypodiploid nuclei but no accumulation of cells in G2/M phase. CONCLUSIONS Direct cytotoxic effects of DES in prostate cancer cells are estrogen receptor independent and do not involve disruption of microtubule architecture but do involve the promotion of cell cycle arrest and apoptosis. These are the first data confirming direct cytotoxic effects of DES and DESdP in prostate cancer cells via an apoptotic mechanism. IMPLICATIONS. These results suggest that DES and DESdP have potential value as agents against androgen-insensitive prostate neoplasms through induction of an apoptotic cascade.
Energy efficient Localization Technique in Wireless Sensor Network

Localization is one of the essential problems in wireless sensor networks (WSNs), since the locations of the sensor nodes are significant to both network operations and application level tasks. Although the Global Positioning System based localization techniques can be used to determine node locations within a few meters, the cost of Global Positioning System devices and non-availability of Global Positioning System signals in limited environments avoid their utilization in large scale sensor networks. There exists an extensive body of research that aims at obtaining locations as well as spatial associations of nodes in wireless sensor networks without requiring specific hardware or employing only a limited number of anchors that are aware of their own locations. In this paper, we propose an anchor free localization technique for single hop WSN. The simulation result shows that the proposed technique outperforms its comparatives.
Random coverage with guaranteed connectivity: joint scheduling for wireless sensor networks

Sensor scheduling plays a critical role for energy efficiency of wireless sensor networks. Traditional methods for sensor scheduling use either sensing coverage or network connectivity, but rarely both. In this paper, we deal with a challenging task: without accurate location information, how do we schedule sensor nodes to save energy and meet both constraints of sensing coverage and network connectivity? Our approach utilizes an integrated method that provides statistical sensing coverage and guaranteed network connectivity. We use random scheduling for sensing coverage and then turn on extra sensor nodes, if necessary, for network connectivity. Our method is totally distributed, is able to dynamically adjust sensing coverage with guaranteed network connectivity, and is resilient to time asynchrony. We present analytical results to disclose the relationship among node density, scheduling parameters, coverage quality, detection probability, and detection delay. Analytical and simulation results demonstrate the effectiveness of our joint scheduling method
Cognition-Emotion Dysinteraction in Schizophrenia

Evolving theories of schizophrenia emphasize a “disconnection” in distributed fronto-striatal-limbic neural systems, which may give rise to breakdowns in cognition and emotional function. We discuss these diverse domains of function from the perspective of disrupted neural circuits involved in “cold” cognitive vs. “hot” affective operations and the interplay between these processes. We focus on three research areas that highlight cognition-emotion dysinteractions in schizophrenia: First, we discuss the role of cognitive deficits in the “maintenance” of emotional information. We review recent evidence suggesting that motivational abnormalities in schizophrenia may in part arise due to a disrupted ability to “maintain” affective information over time. Here, dysfunction in a prototypical “cold” cognitive operation may result in “affective” deficits in schizophrenia. Second, we discuss abnormalities in the detection and ascription of salience, manifest as excessive processing of non-emotional stimuli and inappropriate distractibility. We review emerging evidence suggesting deficits in some, but not other, specific emotional processes in schizophrenia – namely an intact ability to perceive emotion “in-the-moment” but poor prospective valuation of stimuli and heightened reactivity to stimuli that ought to be filtered. Third, we discuss abnormalities in learning mechanisms that may give rise to delusions, the fixed, false, and often emotionally charged beliefs that accompany psychosis. We highlight the role of affect in aberrant belief formation, mostly ignored by current theoretical models. Together, we attempt to provide a consilient overview for how breakdowns in neural systems underlying affect and cognition in psychosis interact across symptom domains. We conclude with a brief treatment of the neurobiology of schizophrenia and the need to close our explanatory gap between cellular-level hypotheses and complex behavioral symptoms observed in this illness.