cssi/SciSciGPT-SciSciNet huggingface dataset:
Simulating low-energy neutrino interactions with MARLEY

Abstract Monte Carlo event generators are a critical tool for the interpretation of data obtained by neutrino experiments. Several modern event generators are available which are well-suited to the GeV energy scale used in studies of accelerator neutrinos. However, theoretical modeling differences make their immediate application to lower energies difficult. In this paper, I present a new event generator, MARLEY , which is designed to better address the simulation needs of the low-energy (tens of MeV and below) neutrino community. The code is written in C++14 with an optional interface to the popular ROOT data analysis framework. The current release of MARLEY (version 1.2.0) emphasizes simulations of the reaction 40Ar ( ν e , e − ) 40K⁎ but is extensible to other channels with suitable user input. This paper provides detailed documentation of MARLEY 's implementation and usage, including guidance on how generated events may be analyzed and how MARLEY may be interfaced with external codes such as Geant4. Further information about MARLEY is available on the official website at http://www.marleygen.org . Program summary Program title: MARLEY 1.2.0 CPC Library link to program files: https://doi.org/10.17632/4v7zxnc8j3.1 Developer's respository link: http://github.com/MARLEY-MC/marley Code Ocean capsule: https://codeocean.com/capsule/9868179 Licensing provisions: GNU General Public License 3.0 Programming language: C++14 External routines/libraries used: GNU Scientific Library [1] , [2] (required), ROOT [3] , [4] (optional) Nature of problem: Simulation of neutrino-nucleus scattering events at energies of tens-of-MeV and below Solution method: Initial two-to-two scattering kinematics are sampled using the allowed approximation differential cross section and tables of precomputed nuclear matrix elements. Subsequent de-excitations of the remnant nucleus are simulated using a Monte Carlo implementation of the Hauser-Feshbach statistical model and tabulated γ-ray decay schemes for discrete nuclear levels. Additional comments including restrictions and unusual features: Input data are provided with the code that are suitable for producing simulations of the charged-current reaction 40Ar ( ν e , e − ) 40K⁎, coherent elastic neutrino-nucleus scattering on spin-zero target nuclei, and neutrino-electron elastic scattering on any atomic target. Preparation of new reaction input files (whose format is documented in Appendix B ) would enable other reaction channels and nuclear targets to be handled by the existing code framework. Although there is no maximum neutrino energy enforced by the code itself, realistic neutrino-nucleus scattering events may be generated up to roughly 50 MeV. Above this energy, the effects of forbidden nuclear transitions, which are neglected in the current treatment of the cross sections (see section 2.1 ), become increasingly important.
Liquid-jet instability at high pressures with real-fluid interface thermodynamics

The injection of liquid fuel at supercritical pressures is a relevant topic in combustion but is usually overlooked. In the past, the wrong assumption whereby the liquid phase undergoes a fast transition to a supercritical state was made, thus neglecting any role of two-phase interface dynamics in the early stages of the atomization process. However, recent studies have shown that local thermodynamic phase equilibrium and mixing between the involved species allow the coexistence of both phases in this pressure range. In this work, a volume-of-fluid method adapted to variable-density real fluids is used to solve the low-Mach-number governing equations coupled with a thermodynamic model based on the Soave–Redlich–Kwong equation of state. The mixing process, interface thermodynamics, and early deformation of a cool liquid jet composed of n-decane surrounded by a hotter gas composed of oxygen at 150 bar are analyzed. Although heat conducts from the hotter gas into the liquid, net condensation can provide the proper local energy balance at high pressures. Then, vaporization and condensation may happen simultaneously at different interface locations. As pressure increases, liquid and gas mixtures become more alike in the vicinity of the interface. Thus, a combination of low surface tension force and gas-like liquid viscosities causes an early growth of surface instabilities. Early results indicate some similarity with high-Weber-number incompressible flows. The role of vortex dynamics on the interface deformation is analyzed by using the λρ dynamical vortex identification method.
Hyperbolic three-string vertex

We begin developing tools to compute off-shell string amplitudes with the recently proposed hyperbolic string vertices of Costello and Zwiebach. Exploiting the relation between a boundary value problem for Liouville’s equation and a monodromy problem for a Fuchsian equation, we construct the local coordinates around the punctures for the generalized hyperbolic three-string vertex and investigate their various limits. This vertex corresponds to the general pants diagram with three boundary geodesics of unequal lengths. We derive the conservation laws associated with such vertex and perform sample computations. We note the relevance of our construction to the calculations of the higher-order string vertices using the pants decomposition of hyperbolic Riemann surfaces.
Quantum metric and correlated states in two-dimensional systems

Abstract The recent realization of twisted, two-dimensional, bilayers exhibiting strongly correlated states has created a platform in which the relation between the properties of the electronic bands and the nature of the correlated states can be studied in unprecedented ways. The reason is that these systems allow extraordinary control of the electronic bands’ properties, for example by varying the relative twist angle between the layers forming the system. In particular, in twisted bilayers the low energy bands can be tuned to be very flat and with a nontrivial quantum metric. This allows the quantitative and experimental exploration of the relation between the metric of Bloch quantum states and the properties of correlated states. In this work we first review the general connection between quantum metric and the properties of correlated states that break a continuous symmetry. We then discuss the specific case when the correlated state is a superfluid and show how the quantum metric is related to its superfluid stiffness. To exemplify such relation we show results for the case of superconductivity in magic angle twisted bilayer graphene. We conclude by discussing possible research directions to further elucidate the connection between quantum metric and correlated states’ properties.
Adversarial machine learning in Network Intrusion Detection Systems

Abstract Adversarial examples are inputs to a machine learning system intentionally crafted by an attacker to fool the model into producing an incorrect output. These examples have achieved a great deal of success in several domains such as image recognition, speech recognition and spam detection. In this paper, we study the nature of the adversarial problem in Network Intrusion Detection Systems (NIDS). We focus on the attack perspective, which includes techniques to generate adversarial examples capable of evading a variety of machine learning models. More specifically, we explore the use of evolutionary computation (particle swarm optimization and genetic algorithm) and deep learning (generative adversarial networks) as tools for adversarial example generation. To assess the performance of these algorithms in evading a NIDS, we apply them to two publicly available data sets, namely the NSL-KDD and UNSW-NB15, and we contrast them to a baseline perturbation method: Monte Carlo simulation. The results show that our adversarial example generation techniques cause high misclassification rates in eleven different machine learning models, along with a voting classifier. Our work highlights the vulnerability of machine learning based NIDS in the face of adversarial perturbation.
Patch characteristics and domestic dogs differentially affect carnivore space use in fragmented landscapes in southern Chile

This article's aim is to determine whether (a) the spatial use of domestic dogs increases with habitat destruction, and (b) domestic dogs and habitat destruction drive the spatial use of native carnivores in a heavily degraded agricultural landscape. Conclusions highlight that domestic dog occupancy was positively correlated with habitat loss and future conditions of increased fragmentation and habitat loss will likely increase the potential contact between domestic dogs and native carnivores.
On the gradient flow structure of the isotropic Landau equation

We prove that the isotropic Landau equation equipped with the Coulomb potential introduced by Krieger-Strain and Gualdani-Guillen can be identified with the gradient flow of the entropy in the probability space with respect to a Riemannian metric tensor with nonlocal mobility. We give characterizations of the corresponding geodesics equations and present a convergence rate result by estimating its Hessian operator.
Design and user experience testing of a polygenic score report: a qualitative study of prospective users.

Background Polygenic scores-which quantify inherited risk by integrating information from many common sites of DNA variation-may enable a tailored approach to clinical medicine. However, alongside considerable enthusiasm, we and others have highlighted a lack of standardized approaches for score disclosure. Here, we review the landscape of polygenic score reporting and describe a generalizable approach for development of a polygenic score disclosure tool for coronary artery disease. Methods We assembled a working group of clinicians, geneticists, data visualization specialists, and software developers. The group reviewed existing polygenic score reports and then designed a two-page mock report for coronary artery disease. We then conducted a qualitative user-experience study with this report using an interview guide focused on comprehension, experience, and attitudes. Interviews were transcribed and analyzed for themes identification to inform report revision. Results Review of nine existing polygenic score reports from commercial and academic groups demonstrated significant heterogeneity, reinforcing the need for additional efforts to study and standardize score disclosure. Using a newly developed mock score report, we conducted interviews with ten adult individuals (50% females, 70% without prior genetic testing experience, age range 20-70 years) recruited via an online platform. We identified three themes from interviews: (1) visual elements, such as color and simple graphics, enable participants to interpret, relate to, and contextualize their polygenic score, (2) word-based descriptions of risk and polygenic scores presented as percentiles were the best recognized and understood, (3) participants had varying levels of interest in understanding complex genomic information and therefore would benefit from additional resources that can adapt to their individual needs in real time. In response to user feedback, colors used for communicating risk were modified to minimize unintended color associations and odds ratios were removed. All 10 participants expressed interest in receiving a polygenic score report based on their personal genomic information. Conclusions Our findings describe a generalizable approach to develop a polygenic score report understandable by potential patients. Although additional studies are needed across a wider spectrum of patient populations, these results are likely to inform ongoing efforts related to polygenic score disclosure within clinical practice.
Transition Motion Planning for Multi-Limbed Vertical Climbing Robots Using Complementarity Constraints

In order to achieve autonomous vertical wall climbing, the transition phase from the ground to the wall requires extra consideration inevitably. This paper focuses on the contact sequence planner to transition between flat terrain and vertical surfaces for multi-limbed climbing robots. To overcome the transition phase, it requires planning both multicontact and contact wrenches simultaneously which makes it difficult. Instead of using a predetermined contact sequence, we consider various motions on different environment setups via modeling contact constraints and limb switchability as complementarity conditions. Two safety factors for toe sliding and motor over-torque are the main tuning parameters for different contact sequences. By solving as a nonlinear program (NLP), we can generate several feasible sequences of foot placements and contact forces to avoid failure cases. We verified feasibility with demonstrations on the hardware SiLVIA, a sixlegged robot capable of vertically climbing between two walls by bracing itself in-between using only friction.
Privacy-Preserving Dynamic Personalized Pricing with Demand Learning

The prevalence of e-commerce has made customers’ detailed personal information readily accessible to retailers, and this information has been widely used in pricing decisions. When using personaliz...
Stocks, flows, and flood insurance: A nationwide analysis of the capitalized impact of annual premium discounts on housing values

Abstract To approach fiscal solvency in the face of escalated intensity and frequency of natural disasters, The National Flood Insurance Program is increasing flood insurance premiums. Despite widespread concerns over the affordability of higher premiums, less attention has been paid to the impact of premium rate increases on housing values. Should housing values capitalize premium discounts, their removal could entail losses in home equity and net wealth, property tax revenue shortfalls for local governments, and relocation disincentives for vulnerable homeowners. We use the quasi-experimental nature of eligibility criteria for the largest class of flood insurance premium discounts to causally estimate the capitalization of flood insurance premium subsidies using nationwide and city-specific hedonic difference-in-difference regressions. We find that in a nationally pooled sample, the average capitalization of subsidy eligibility is $12,352 and show that capitalization exhibits significant and intuitive heterogeneity across municipalities. Our results inform policy discussions surrounding the transition to the national Risk Rating 2.0 premium schedule.
A Semi-Supervised Generative Adversarial Network for Prediction of Genetic Disease Outcomes

For most diseases, building large databases of labeled genetic data is an expensive and time-demanding task. To address this, we introduce genetic Generative Adversarial Networks (gGAN), a semi-supervised approach based on an innovative GAN architecture to create large synthetic genetic data sets starting with a small amount of labeled data and a large amount of unlabeled data. Our goal is to create a mechanism able to increase the sample size of the labeled data and generalize learning over different populations while keeping awareness of the quality of its own predictions. The proposed model achieved satisfactory results using real genetic data from different datasets and populations, in which the test populations may not have the same genetic profiles. The proposed model is self-aware and capable of determining whether a new genetic profile has enough compatibility with the data on which the network was trained and is thus suitable for prediction. The code and datasets used can be found at https://github.com/caio-davi/gGAN
Discovering the Unknown Knowns: Turning Implicit Knowledge in the Dataset into Explicit Training Examples for Visual Question Answering

Visual question answering (VQA) is challenging not only because the model has to handle multi-modal information, but also because it is just so hard to collect sufficient training examples — there are too many questions one can ask about an image. As a result, a VQA model trained solely on human-annotated examples could easily over-fit specific question styles or image contents that are being asked, leaving the model largely ignorant about the sheer diversity of questions. Existing methods address this issue primarily by introducing an auxiliary task such as visual grounding, cycle consistency, or debiasing. In this paper, we take a drastically different approach. We found that many of the “unknowns” to the learned VQA model are indeed “known” in the dataset implicitly. For instance, questions asking about the same object in different images are likely paraphrases; the number of detected or annotated objects in an image already provides the answer to the “how many” question, even if the question has not been annotated for that image. Building upon these insights, we present a simple data augmentation pipeline SimpleAug to turn this “known” knowledge into training examples for VQA. We show that these augmented examples can notably improve the learned VQA models’ performance, not only on the VQA-CP dataset with language prior shifts but also on the VQA v2 dataset without such shifts. Our method further opens up the door to leverage weakly-labeled or unlabeled images in a principled way to enhance VQA models. Our code and data are publicly available at https://github.com/heendung/simpleAUG.
Molecular Dynamics Simulations on Cloud Computing and Machine Learning Platforms

Scientific computing applications have benefited greatly from high performance computing infrastructure such as supercomputers. However, we are seeing a paradigm shift in the computational structure, design, and requirements of these applications. Increasingly, data-driven and machine learning approaches are being used to support, speed-up, and enhance scientific computing applications, especially molecular dynamics simulations. Concurrently, cloud computing platforms are increasingly appealing for scientific computing, providing “infi-nite” computing powers, easier programming and deployment models, and access to computing accelerators such as TPUs (Tensor Processing Units). This confluence of machine learning (ML) and cloud computing represents exciting opportunities for cloud and systems researchers. ML-assisted molecular dynamics simulations are a new class of workload, and exhibit unique computational patterns. These simulations present new challenges for low-cost and high-performance execution. We argue that transient cloud resources, such as low-cost preemptible cloud VMs, can be a viable platform for this new workload. Finally, we present some low-hanging fruits and long-term challenges in cloud resource management, and the integration of molecular dynamics simulations into ML platforms (such as TensorFlow).
Reinforcement Learning based Disease Progression Model for Alzheimer’s Disease

We model Alzheimer's disease (AD) progression by combining differential equations (DEs) and reinforcement learning (RL) with domain knowledge. DEs provide relationships between some, but not all, factors relevant to AD. We assume that the missing relationships must satisfy general criteria about the working of the brain, for e.g., maximizing cognition while minimizing the cost of supporting cognition. This allows us to extract the missing relationships by using RL to optimize an objective (reward) function that captures the above criteria. We use our model consisting of DEs (as a simulator) and the trained RL agent to predict individualized 10-year AD progression using baseline (year 0) features on synthetic and real data. The model was comparable or better at predicting 10-year cognition trajectories than state-of-the-art learning-based models. Our interpretable model demonstrated, and provided insights into, "recovery/compensatory" processes that mitigate the effect of AD, even though those processes were not explicitly encoded in the model. Our framework combines DEs with RL for modelling AD progression and has broad applicability for understanding other neurological disorders.
Re-identification of individuals in genomic datasets using public face images.

Recent studies suggest that genomic data can be matched to images of human faces, raising the concern that genomic data can be re-identified with relative ease. However, such investigations assume ...
MLP-Mixer: An all-MLP Architecture for Vision

Convolutional Neural Networks (CNNs) are the go-to model for computer vision. Recently, attention-based networks, such as the Vision Transformer, have also become popular. In this paper we show that while convolutions and attention are both sufficient for good performance, neither of them are necessary. We present MLP-Mixer, an architecture based exclusively on multi-layer perceptrons (MLPs). MLP-Mixer contains two types of layers: one with MLPs applied independently to image patches (i.e. "mixing" the per-location features), and one with MLPs applied across patches (i.e. "mixing" spatial information). When trained on large datasets, or with modern regularization schemes, MLP-Mixer attains competitive scores on image classification benchmarks, with pre-training and inference cost comparable to state-of-the-art models. We hope that these results spark further research beyond the realms of well established CNNs and Transformers.
AI and the Everything in the Whole Wide World Benchmark

There is a tendency across different subfields in AI to valorize a small collection of influential benchmarks. These benchmarks operate as stand-ins for a range of anointed common problems that are frequently framed as foundational milestones on the path towards flexible and generalizable AI systems. State-of-the-art performance on these benchmarks is widely understood as indicative of progress towards these long-term goals. In this position paper, we explore the limits of such benchmarks in order to reveal the construct validity issues in their framing as the functionally "general" broad measures of progress they are set up to be.
Unmasking partisanship: Polarization undermines public response to collective risk

Abstract Political polarization may undermine public policy response to collective risk, especially in periods of crisis when political actors have incentives to manipulate public perceptions. We study these dynamics in the U.S., focusing on how partisanship has influenced the use of face masks to stem the spread of COVID-19. Using a variety of approaches, we find partisanship is the single most important predictor of mask use and local policy interventions do not offset this relationship.
Trajectory design for a cislunar CubeSat leveraging dynamical systems techniques: The Lunar IceCube mission

Abstract Lunar IceCube is a 6U CubeSat that is designed to detect and observe lunar volatiles from a highly inclined orbit. This spacecraft, equipped with a low-thrust engine, is expected to be deployed from the upcoming Exploration Mission-1 vehicle. However, significant uncertainty in the deployment conditions for secondary payloads impacts both the availability and geometry of transfers that deliver the spacecraft to the lunar vicinity. A framework that leverages dynamical systems techniques is applied to a recently updated set of deployment conditions and spacecraft parameter values for the Lunar IceCube mission, demonstrating the capability for rapid trajectory design.
Antimicrobial Prophylaxis of Infections Associated with Foreign Bodies

The administration of antimicrobial agents prophylactically during the perioperative period has become standard practice for surgical procedures involving the implantation of prosthetic material, and most authorities in the field of surgical wound prophylaxis have endorsed this practice. A recent meta-analysis of nine randomized, controlled studies involving 1,045 patients undergoing placement of ventricular shunts suggested that antimicrobial prophylaxis reduced infection risk twofold, but was of apparent benefit only if infection rates in the control group were greater than 5%. While clinical studies verifying that perioperative antibiotics significantly reduce implant infection rates are not available for the majority of such procedures, significant benefits frequently have been demonstrated when infections within any part of the surgical incision, not just the prosthetic device, are included in the evaluation. Although these differences did not achieve statistical significance because of the paucity of infections observed in either group, the authors advocated the three-dose regimen pending more definitive data. In prophylaxis of prosthetic valve endocarditis, however, anecdotal associations between episodes of transient bacteremia and endocarditis have led to an almost universal recommendation for aggressive antimicrobial prophylaxis for patients with prosthetic valves who undergo dental procedures and surgery. The choice of an antimicrobial regimen and the duration of use remain matters of great confusion. When recurrent pathogens are encountered, a systematic evaluation of new prophylactic regimens, possibly in the form of ongoing randomized trials, may provide a database for a rational approach to infection prevention in implantation surgery.
Chapter 3 Applications of CW Beam Processing to Ion Implanted Crystalline Silicon

Publisher Summary This chapter discusses the analytical techniques used in the evaluation of CW laser and e-beam annealing of ion implanted single crystal silicon. Solid phase epitaxy is discussed and the results of CW beam processing in amorphous and nonamorphous Si are reviewed. The crystalline quality, as judged by transmission electron microscopy (TEM), is good in CW laser annealed silicon layers. Results obtained using a scanning e-beam, both in an electron beam welder and in a scanning electron microscope, are largely similar to those for CW laser scanning. The most significant difference between these methods and the use of a laser occurs if the silicon sample to be annealed is covered by an oxide or other dielectric layer. If a laser is used, the dielectric layer will act as an antireflective coating, and the laser power must then be adjusted accordingly. This may cause problems in device structures, where the oxide thickness is not uniform throughout the scanned area. For the e-beam, however, this problem does not exist, because no reflection takes place either from the silicon or from silicon dioxide. On the other hand, charging of the oxide may be important for certain choices of the beam current and voltage.
Memory Distortion: Can Accurate Memory be Preserved?

A single experiment is reported which attempts to prevent or attenuate the distortion in memory produced by inaccurate postevent information. Specifically, after viewing a videotape, some participants received misieading information regarding the events depicted in the videotape. Further, some of these participants were given an inoculation procedure intended to educate them about the effects of misieading postevent information prior to receiving the misleading information. This material was presented in written form, videotape, or a combination of written and video form. Contrary to expectations, participants who were misled and received an inoculation procedure evidenced greatest memory distortion. Results are discussed in terms of the wording used in a warning about memory distortion.
Physical design of optoelectronic system-on-a-package: a CAD tool and algorithms

We propose a new approach to the physical design of optoelectronic system-on-a-package (SOP) using optical waveguide interconnect technology. The objective is to improve the performance of SOP by replacing long distance electrical interconnects with optical waveguide interconnects. A new simultaneous optimization algorithm for module placement and routing of electrical and optical interconnects is introduced. It not only improves the performance of SOP, but reduces the simulation time. Even though a small portion of electrical interconnects are replaced with optical interconnects, more than 21% improvement of the SOP performance is achieved.
Reasoning about operationality for explanation-based learning

The results of explanation-based learning must be operational. This paper argues that since the generalizations created by explanation-based learning may be conditionally operational for finer-grained definitions of operationality, the conditions on the operationality of a generalization should be determined and included with the generalization. This paper describes an implementation of explanation-based learning called ROE that proves that the predicates used in a generalization are operational for the training instance upon which it is based, and generalizes the proof of operationality to determine the weakest conditions on when the generalization should be used. These conditions are included in the results of ROE to restrict their use to situations in which they are operational. Reasoning about and generalizing operationality is accomplished by using ROE itself on a domain theory that concludes whether predicates are operational for whatever notion of operationality the user encodes. A PROLOG implementation of ROE is included as an appendix.
Fiber-Matrix Adhesion and Its Effect on Composite Mechanical Properties: I. Inplane and Interlaminar Shear Behavior of Graphite/Epoxy Composites:

An experimental investigation was performed to establish the relationships between fiber-matrix adhesion as determined by single fiber interfacial shear strength tests with the inplane and interlaminar shear properties of graphite/epoxy composites. ±45°-tension, Iosipescu, and short beam shear tests were conducted on three identical sets of composites differing only in their fiber-matrix interfacial shear strength. The fiber-matrix interphase and consequently the interfacial shear strength was varied by using the same graphite fiber was different surface modifications, namely untreated, surface treated, and surface treated and coated with a thin layer of epoxy. The surface modification changed the interfacial shear strength by more than a factor of two, while the properties of fibers remained unchanged. The experimental results showed that both inplane and interlaminar shear strengths increased approximately in the same ratio as the interfacial shear strength, however, the inplane shear modulus was relati...
Experimental measurement of weak band intensities

In modeling the opacity of astronomical objects, such as stellar atmospheres, the most important transitions are those with absorbance = αL ∼ 1, where α is the absorption coefficient of the atmosphere and L is the pathlength that light travels in leaving the atmosphere. Transitions with much smaller absorbance are not important, while those with much larger absorbance are effectively opaque. The relevant absorption lengths L are typically orders of magnitude larger than can be realized in the laboratory, and thus obtaining the needed laboratory data is a significant experimental challenge. This volume contains several examples of the power of modern ab initio methods to predict spectra of simple triatomic molecules, such as H 2 O, but it is still necessary to at least calibrate the predictions against laboratory bands of similar oscillator strength. The theoretical treatment of molecules with four or more atoms lags far behind the theoretical treatment of triatomics and present experimental capabilities.
Sex determination of human embryos using the polymerase chain reaction and confirmation by fluorescence in situ hybridization

Objective To use fluorescence in situ hybridization to corroborate the polymerase chain reaction (PCR) preimplantation diagnosis of human embryos in three couples carrying a chromosome X-linked disease. Setting Clinical and research IVF laboratories. Patients Individuals undergoing preimplantation diagnosis. Results Four ETs were performed in couples undergoing preimplantation diagnosis by multiplex PCR or fluorescence in situ hybridization, resulting in the birth of two normal female twins. The result of another is pending. A total of 22 embryos were analyzed by PCR. Embryos that were diagnosed as being at risk of carrying the genetic abnormality (n = 8), embryos that failed diagnosis (n = 4), and genetically normal embryos that arrested development (n = 4) were further analyzed by fluorescence in situ hybridization. The sex of all 16 embryos was determined and confirmed the previous 12 preimplantation diagnoses by multiplex PCR. In addition, fluorescence in situ hybridization analysis allowed the detection of two aneuploid embryos, one XO and one XYY, previously diagnosed by PCR as a normal female and male. Two mosaics were also detected. Conclusion Polymerase chain reaction and fluorescence in situ hybridization are possible for preimplantation sex determination in cases of genetic sex-linked disease. Fluorescence in situ hybridization, however, supplies additional information about sex chromosome aneuploidy and is not susceptible to contamination or misdiagnosis of monosomy X.
Financial Crisis Versus Debate on Urban Space, Challenge, and Research Agenda

Unstable economic conditions due to the financial crisis in 1997 and 2008 have made it necessary for Indonesia to seek alternative ways to escape such uncertain global economic conditions. In doing so, several development policies and innovative scenarios have been applied by the Indonesian Republic. The government has also attempted to relate such initiatives with global development actors, starting from the policy level up until the formulation of action plans. Nevertheless these efforts must be accompanied by a comprehensive approach, covering all activity aspects from the actors of development to collectively participate in development. This may also effect development of Indonesian urban space of which cannot be separated from such global conditions. This article attempts to describe the impacts of development beyond the limits of administration as a result of globalization, occurring particularly in large cities, but also involving other cities Indonesia. In relation to this, the discourse on ‘space’ emerges in the context of urban planning, whether remaining to be oriented towards physical organization, or shifted to the new paradigm of which tends to view space as a product of global economic situations, community conditions, as well as values of local culture and foreign values (imported from the west). Therefore, this article begins its discussion on urban systems within the context of globalization and financial crisis, then proceeding with discussions concerning impacts towards urban structure, regional competition, urban identity, followed by discussions on financial crisis and the debate on urban space, and finally concluded with the research agenda. Paradigm shifts have become one of the most urgent matters to study considering the challenges of inter-regional competition, regional autonomy, and financial crisis. Furthermore, this study may assist the space planners in better understanding the reasons that cause failures of policy and planning implementation that have been formulated. This article aims to awaken academicians in developing a research agenda in line with the debates of understanding urban space (particularly in times of financial crisis) but also serves as a critic and enrichment towards the literature related to global impacts towards urban structure, regional competition, and urban identity. Keywords: globalization, space, urban structure, regional competitiveness, urban identity.
Voyager EUV and FUV Observations

The Voyager 1 and 2 ultraviolet spectrometers are sensitive over the wavelength range 500 to 1700 A. In the extreme ultraviolet (EUV), at wavelengths shortward of the Lyman limit (912 A), Voyager observations detected emission from three out of a sample of 11 nearly hot DA white dwarfs. These observations imply very low HI column densities in the directions of the three stars detected. In the far ultraviolet (FUV), at wavelengths between 912 and 1200 A, Voyager observations of O and B stars can be used to study interstellar reddening at the shortest wavelengths and to provide useful estimates of interstellar H2 column densities.
LYSP: a Lisp dialect for programming small applications

Some ten years ago, a small group of us at IBM Research undertook to write a new kind of text editor, to run in the VM/370 environment, based on our experience with the experimental Business Definition System (BDS) we had implemented previously. This new editor, called the Parametric Editor, or P-EDIT, was to be upwards compatible with an existing popular editor in use at that time, while providing the ability to edit multiple versions of a file simultaneously, and providing a general UNDO command which could be used to return to any previous state of the editing session, and which itself was UNDOable.
Learning in artificial neural systems

This paper presents an overview and analysis of learning in Artificial Neural Systems (ANS's). It begins with a general introduction to neural networks and connectionist approaches to information processing. The basis for learning in ANS's is then described, and compared with classical Machine learning. While similar in some ways, ANS learning deviates from tradition in its dependence on the modification of individual weights to bring about changes in a knowledge representation distributed across connections in a network. This unique form of learning is analyzed from two aspects: the selection of an appropriate network architecture for representing the problem, and the choice of a suitable learning rule capable of reproducing the desired function within the given network. The various network architectures are classified, and then identified with explicit restrictions on the types of functions they are capable of representing. The learning rules, i.e., algorithms that specify how the network weights are modified, are similarly taxonomized, and where possible, the limitations inherent to specific classes of rules are outlined.
Phonetic imitation by young children and its developmental changes.

Purpose In the current study, the author investigated the developmental course of phonetic imitation in childhood, and further evaluated existing accounts of phonetic imitation. Method Sixteen preschoolers, 15 third graders, and 18 college students participated in the current study. An experiment with a modified imitation paradigm with a picture-naming task was conducted, in which participants' voice-onset time (VOT) was compared before and after they were exposed to target speech with artificially increased VOT. Results Extended VOT in the target speech was imitated by preschoolers and 3rd graders as well as adults, confirming previous findings in phonetic imitation. Furthermore, an age effect of phonetic imitation was observed; namely, children showed greater imitation than adults, whereas the degree of imitation was comparable between preschoolers and 3rd graders. No significant effect of gender or word specificity was observed. Conclusions Young children imitated fine phonetic details of the target sp...
Broadband high-optical-density filters in the infrared.

A new concept for the design of broadband (2–25 μm and beyond) neutral-density filters in the infrared region without etaloning effects is proposed and demonstrated. One important aspect of the technique is to use metallic-thin-film (10–200-nm-thick) multilayer combinations deposited onto different substrates (ZnSe, CdTe, Lexan). Neutral-density filters with optical densities as high as 4 are designed and built in the broadband region (2–25 μm). Another key innovation is the use of ultrathin substrates (∼100 nm thick) for elimination of etaloning effects normally present in thick (>0.5-mm) substrates. Neutral-density filters with such ultrathin substrates are also designed and investigated.
The Momentum of Real Population Under Linear Fertility Transition

Population momentum is the ratio of a population's ultimate size after a demographic transition to its initial size before the transition. For stable population and instantaneous drop to replacement fertility, Keyfitz found a simple formula for the momentum. Although Keyfitz's formula has been extended to cover gradual demographic transitions, the stable initial population, however, is still an obstacle to approaching reality. Using the solution of the Lotka equation with time-varying vital rates and extending it to negative values of time, exact and accurate formulae for the momentum of any initial population that undergoes a linear fertility transition are expressed. Examples using the data from the United Nations indicate that the accurate formula works well for the age structures that are far from stable such as the more and less developed regions, as well as that close to stable such as the least developed region.
On the components of X0(pn)

Abstract We show he ordinary locus of X 0 ( p n ) ( C p ) is normally the set of C p -valued points on 2 n affinoids which correspond to components of the stable model of X 0 ( p n ) . We then show the points on Edixhoven's “horizontal” components of X 0 ( p 2 ) correspond to elliptic curves which are p -isogenous to curves which Buzzard calls “too supersingular.”
Spectral Patterns of Chaotic Acetylene

A diabatic correlation diagram procedure, first applied (Rose, J. P.; Kellman, M. E., J. Chem. Phys. 1996, 105, 7348) to H2O, is used to classify energy and intensity patterns in the highly excited...
Phytoestrogen Genistein Protects Against Endothelial Barrier Dysfunction in Vascular Endothelial Cells Through PKA-Mediated Suppression of RhoA Signaling

The soy-derived phytoestrogen genistein has received attention for its potential to improve vascular function, but its mechanism remains unclear. Here, we report that genistein at physiologically relevant concentrations (0.1–10 μM) significantly inhibited thrombin-induced increase in endothelial monolayer permeability. Genistein also reduced the formation of stress fibers by thrombin and suppressed thrombin-induced phosphorylation of myosin light chain (MLC) on Ser19/Thr18 in endothelial cells (ECs). Genistein had no effect on resting intracellular [Ca2+] or thrombin-induced increase in Ca2+ mobilization. Addition of the inhibitors of endothelial nitric oxide synthase or estrogen receptor did not alter the protective effect of genistein. RhoA is a small GTPase that plays an important role in actin-myosin contraction and endothelial barrier dysfunction. RhoA inhibitor blocked the protective effect of genistein on endothelial permeability and also ablated thrombin-induced MLC-phosphorylation in ECs. Inhibit...
Spherizing a Seven-Power, Wide-Field Eyepiece Design

A seven-power, wide-field, eyepiece design incorporating two paraboloidal surfaces was redesigned. The aspherical surfaces presented a manufacturing problem that precluded large-scale production of an otherwise satisfactory design. The LASL Lens Design Code was utilized to replace the aspherical surfaces with spherical ones and to exceed the performance of the original design. The improved design has all-spherical surfaces, and a report on a prototype eyepiece indicates the design to be an excellent one.
Simple model of double adiabatic inversion (DAI) efficiency.

Multislice continuous arterial spin labeling (CASL) using alternating single adiabatic inversion (SAI) and double adiabatic inversion (DAI) (ASD) suffers from control inefficiencies that reduce the perfusion signal-to-noise ratio (SNR). A simple analytic model for DAI efficiency (χ) is presented, and compared with simulation and experimental data. The DAI efficiency (defined as the ratio of uninverted to equilibrium spins) depends primarily on the effective adiabaticity (β′) and the inversion time (both determined from the labeling RF field and gradient amplitudes, and flow velocities). In this study, χ behaved like a damped oscillator, starting from 1 at β′ = 0 (no spin inversion), dropping to 0.5 at β′ = 0.5 (spin saturation), rising again to a peak at β′ ∼ 3, and subsequently oscillating at higher β′. The simple model matched the flow phantom data for β′ < 2, with an accuracy of better than 10%, but it diverged from the flow phantom data as the data oscillated at higher β′. The relative inversion efficiencies of ASD and simultaneous proximal and distal irradiation (SPDI) were measured in 28 elderly volunteers. The ratio of CASL difference (control - label) signals measured in gray matter (= 1.16 ± 0.05), and the simple efficiency models (= 1.13 ± 0.02) had a correlation coefficient of 0.974. Magn Reson Med 52:941–946, 2004. © 2004 Wiley-Liss, Inc.
Linearity conditions for optimal estimation from multiple noisy measurements

Source estimation from several noisy observations, each of which are corrupted with additive independent noise is arguably among the most fundamental problems in estimation theory. Estimating multiple independent sources, corrupted by identical noise realization is important in various communication applications. It is well-known for both cases that when all sources and noises are Gaussian, linear estimator minimizes the mean square estimation error. This paper analyzes the conditions for linearity of optimal estimation in these two settings, for general source and noise distributions and distortion measures. Specifically, we show that these settings depart from the single source-single channel setting in that Gaussianity of all system components is necessary to render the L p optimal estimator linear at a given signal-to-noise ratio (SNR). Moreover, we show for both settings that at asymptotically high SNR, for Gaussian sources the optimal estimator converges to linear, irrespective of the distribution of the noises; similarly, at low SNR, it is asymptotically linear for Gaussian noises regardless of the sources.
Unconventional Translation of C9ORF72 GGGGCC Expansion Generates Insoluble Polypeptides Specific to c9FTD/ALS

Frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS) are devastating neurodegenerative disorders with clinical, genetic, and neuropathological overlap. Hexanucleotide (GGGGCC) repeat expansions in a noncoding region of C9ORF72 are the major genetic cause of FTD and ALS (c9FTD/ALS). The RNA structure of GGGGCC repeats renders these transcripts susceptible to an unconventional mechanism of translation-repeat-associated non-ATG (RAN) translation. Antibodies generated against putative GGGGCC repeat RAN-translated peptides (anti-C9RANT) detected high molecular weight, insoluble material in brain homogenates, and neuronal inclusions throughout the CNS of c9FTD/ALS cases. C9RANT immunoreactivity was not found in other neurodegenerative diseases, including CAG repeat disorders, or in peripheral tissues of c9FTD/ALS. The specificity of C9RANT for c9FTD/ALS is a potential biomarker for this most common cause of FTD and ALS. These findings have significant implications for treatment strategies directed at RAN-translated peptides and their aggregation and the RNA structures necessary for their production.