Miracle-dz/UniFAR-FTUs huggingface dataset:
The CHERI capability model: Revisiting RISC in an age of risk

Motivated by contemporary security challenges, we reevaluate and refine capability-based addressing for the RISC era. We present CHERI, a hybrid capability model that extends the 64-bit MIPS ISA with byte-granularity memory protection. We demonstrate that CHERI enables language memory model enforcement and fault isolation in hardware rather than software, and that the CHERI mechanisms are easily adopted by existing programs for efficient in-program memory safety. In contrast to past capability models, CHERI complements, rather than replaces, the ubiquitous page-based protection mechanism, providing a migration path towards deconflating data-structure protection and OS memory management. Furthermore. CHERI adheres to a strict RISC philosophy: it maintains a load-store architecture and requires only single-cycle instructions, and supplies protection primitives to the compiler, language runtime, and operating system. We demonstrate a mature FPGA implementation that runs the FreeBSD operating system with a full range of software and an open-source application suite compiled with an extended LLVM to use CHERI memory protection. A limit study compares published memory safety mechanisms in terms of instruction count and memory overheads. The study illustrates that CHERI is performance-competitive even while providing assurance and greater flexibility with simpler hardware.
Suggested Involvement of PP1/PP2A Activity and De Novo Gene Expression in Anhydrobiotic Survival in a Tardigrade, Hypsibius dujardini, by Chemical Genetic Approach

Upon desiccation, some tardigrades enter an ametabolic dehydrated state called anhydrobiosis and can survive a desiccated environment in this state. For successful transition to anhydrobiosis, some anhydrobiotic tardigrades require pre-incubation under high humidity conditions, a process called preconditioning, prior to exposure to severe desiccation. Although tardigrades are thought to prepare for transition to anhydrobiosis during preconditioning, the molecular mechanisms governing such processes remain unknown. In this study, we used chemical genetic approaches to elucidate the regulatory mechanisms of anhydrobiosis in the anhydrobiotic tardigrade, Hypsibius dujardini. We first demonstrated that inhibition of transcription or translation drastically impaired anhydrobiotic survival, suggesting that de novo gene expression is required for successful transition to anhydrobiosis in this tardigrade. We then screened 81 chemicals and identified 5 chemicals that significantly impaired anhydrobiotic survival after severe desiccation, in contrast to little or no effect on survival after high humidity exposure only. In particular, cantharidic acid, a selective inhibitor of protein phosphatase (PP) 1 and PP2A, exhibited the most profound inhibitory effects. Another PP1/PP2A inhibitor, okadaic acid, also significantly and specifically impaired anhydrobiotic survival, suggesting that PP1/PP2A activity plays an important role for anhydrobiosis in this species. This is, to our knowledge, the first report of the required activities of signaling molecules for desiccation tolerance in tardigrades. The identified inhibitory chemicals could provide novel clues to elucidate the regulatory mechanisms underlying anhydrobiosis in tardigrades.
Neural correlates of audio‐visual object recognition: Effects of implicit spatial congruency

Multisensory integration assists us to identify objects by providing multiple cues with respect to object category and spatial location. We used a semantic audiovisual object matching task to determine the effect of spatial congruency on response behavior and fMRI brain activation. Fifteen subjects responded in a four‐alternative response paradigm, which visual quadrant contained the object best matched to the sound presented. Realistic sounds based on head‐related transfer functions were presented binaurally with the simulated sound source corresponding to one of the four quadrants. Following a random sequence, the location of the sound corresponded to the quadrant containing the semantically congruent target on half the trials, whereas on other trials the sound arose from an incongruent location. We examined the effects of spatial congruency on response latencies, hit‐rates and fMRI responses. Preliminary behavioral results revealed a significant effect of spatial congruency on response latency or performance for stimuli with noise added. In the fMRI experiment, spatial congruency had a significant effect on the BOLD response. A cluster in the right middle and superior temporal gyrus was more activated when the auditory sound sources were spatially congruent with the semantically matching visual stimulus. In an exploratory post‐hoc analysis, in which we correlated the BOLD signal with the subjects' ability to locate the sound sources, we found a significant cluster in the left inferior frontal cortex, where the BOLD response increased with sound‐source localization performance. Thus spatial congruency appears to enhance the semantic integration of audiovisual object information in these brain regions. Hum Brain Mapp, 2012. © 2011 Wiley Periodicals, Inc.
Systolic Mechanical Properties of the Left Ventricle: Effects of Volume and Contractile State

To characterize the mechanical properties of the contracting left ventricle, we studied the changes in left ventricular systolic pressure following step-like perturbations (±3 ml) in ventricular volume, using an isovolumically beating, isolated canine heart preparation. Three mechanical properties (elasticity, resistance, and a deactivation effect) were identified. The elastic property differs from the traditional parallel and series elastic elements; it is a time-varying elasticity that includes active and passive effects of volume changes. Furthermore, it could not be represented by a simple time-varying elasticity, but required a second factor to express the dependence of end-systolic elasticity on the timing of the volume step. This effect was represented by a “volume influence factor,” which may arise from length-dependent activation. The resistive property appeared to be related to force-velocity behavior of the myocardium. Each mechanical property reacted characteristically to steady state changes in ventricular filling volume or contractile state produced by dobutamine (2–13 μg/min). Our findings indicate that elasticity was the property most sensitive to changes in contractile state; these changes increased peak isovolumetric pressure 54% on average, and raised elastic stiffness 40% above control (which was 5.1 mm Hg/ml). Changes in ventricular filling volume only prolonged, but did not alter, the level of elastic stiffness attained at peak pressure. These results support the view that elasticity-or the end-systolic pressure-volume relationship- serves in a given heart to quantify contractility. The “volume influence factor” was not affected by either filling volume or contractile state. Resistance increased in direct proportion with ventricular pressure, but this linear relation was not altered greatly by changes in contractile state or in ventricular filling volume. At 100 mm Hg, ventricular resistance averaged 0.11 mm Hg/ml per sec. Finally, deactivation was greater the later in systole a volume step was imposed, and this pattern was independent of changes in ventricular filling volume and in contractile state.
Recurrent Orthogonal Networks and Long-Memory Tasks

Although RNNs have been shown to be powerful tools for processing sequential data, finding architectures or optimization strategies that allow them to model very long term dependencies is still an active area of research. In this work, we carefully analyze two synthetic datasets originally outlined in (Hochreiter and Schmidhuber, 1997) which are used to evaluate the ability of RNNs to store information over many time steps. We explicitly construct RNN solutions to these problems, and using these constructions, illuminate both the problems themselves and the way in which RNNs store different types of information in their hidden states. These constructions furthermore explain the success of recent methods that specify unitary initializations or constraints on the transition matrices.
Neurosurgeon: Collaborative Intelligence Between the Cloud and Mobile Edge

The computation for today's intelligent personal assistants such as Apple Siri, Google Now, and Microsoft Cortana, is performed in the cloud. This cloud-only approach requires significant amounts of data to be sent to the cloud over the wireless network and puts significant computational pressure on the datacenter. However, as the computational resources in mobile devices become more powerful and energy efficient, questions arise as to whether this cloud-only processing is desirable moving forward, and what are the implications of pushing some or all of this compute to the mobile devices on the edge. In this paper, we examine the status quo approach of cloud-only processing and investigate computation partitioning strategies that effectively leverage both the cycles in the cloud and on the mobile device to achieve low latency, low energy consumption, and high datacenter throughput for this class of intelligent applications. Our study uses 8 intelligent applications spanning computer vision, speech, and natural language domains, all employing state-of-the-art Deep Neural Networks (DNNs) as the core machine learning technique. We find that given the characteristics of DNN algorithms, a fine-grained, layer-level computation partitioning strategy based on the data and computation variations of each layer within a DNN has significant latency and energy advantages over the status quo approach. Using this insight, we design Neurosurgeon, a lightweight scheduler to automatically partition DNN computation between mobile devices and datacenters at the granularity of neural network layers. Neurosurgeon does not require per-application profiling. It adapts to various DNN architectures, hardware platforms, wireless networks, and server load levels, intelligently partitioning computation for best latency or best mobile energy. We evaluate Neurosurgeon on a state-of-the-art mobile development platform and show that it improves end-to-end latency by 3.1X on average and up to 40.7X, reduces mobile energy consumption by 59.5% on average and up to 94.7%, and improves datacenter throughput by 1.5X on average and up to 6.7X.
Antimicrobial Resistance among Isolates Causing Invasive Pneumococcal Disease before and after Licensure of Heptavalent Conjugate Pneumococcal Vaccine

Background The impact of the pneumococcal conjugate vaccine (PCV-7) on antibiotic resistance among pneumococcal strains causing invasive pneumococcal disease (IPD) has varied in different locales in the United States. We assessed trends in IPD including trends for IPD caused by penicillin non-susceptible strains before and after licensure of PCV-7 and the impact of the 2008 susceptibility breakpoints for penicillin on the epidemiology of resistance. Methodology/Principal Findings We performed a retrospective review of IPD cases at Morgan Stanley Children's Hospital of NewYork-Presbyterian, Columbia University Medical Center. Subjects were ≤18 years of age with Streptococcus pneumoniae isolated from sterile body sites from January 1995–December 2006. The rate of IPD from 1995–1999 versus 2002–2006 significantly decreased from 4.1 (CI95 3.4, 4.8) to 1.7 (CI95 1.3, 2.2) per 1,000 admissions. Using the breakpoints in place during the study period, the proportion of penicillin non-susceptible strains increased from 27% to 49% in the pre- vs. post-PCV-7 era, respectively (p = 0.001), although the rate of IPD caused by non-susceptible strains did not change from 1995–1999 (1.1 per 1,000 admissions, CI95 0.8, 1.5) when compared with 2002–2006 (0.8 per 1,000 admissions, CI95 0.6, 1.2). In the multivariate logistic regression model controlling for the effects of age, strains causing IPD in the post-PCV-7 era were significantly more likely to be penicillin non-susceptible compared with strains in the pre-PCV-7 era (OR 2.46, CI95 1.37, 4.40). However, using the 2008 breakpoints for penicillin, only 8% of strains were non-susceptible in the post-PCV-7 era. Conclusions/Significance To date, there are few reports that document an increase in the relative proportion of penicillin non-susceptible strains of pneumococci causing IPD following the introduction of PCV-7. Active surveillance of pneumococcal serotypes and antibiotic resistance using the new penicillin breakpoints is imperative to assess potential changes in the epidemiology of IPD.
Algorithms and data structures for massively parallel generic adaptive finite element codes

Today's largest supercomputers have 100,000s of processor cores and offer the potential to solve partial differential equations discretized by billions of unknowns. However, the complexity of scaling to such large machines and problem sizes has so far prevented the emergence of generic software libraries that support such computations, although these would lower the threshold of entry and enable many more applications to benefit from large-scale computing. We are concerned with providing this functionality for mesh-adaptive finite element computations. We assume the existence of an “oracle” that implements the generation and modification of an adaptive mesh distributed across many processors, and that responds to queries about its structure. Based on querying the oracle, we develop scalable algorithms and data structures for generic finite element methods. Specifically, we consider the parallel distribution of mesh data, global enumeration of degrees of freedom, constraints, and postprocessing. Our algorithms remove the bottlenecks that typically limit large-scale adaptive finite element analyses. We demonstrate scalability of complete finite element workflows on up to 16,384 processors. An implementation of the proposed algorithms, based on the open source software p4est as mesh oracle, is provided under an open source license through the widely used deal.II finite element software library.
Cognitive Neuroscience : Brain Mechanisms of Memory and Cognition

Last week we examined the effects of large medial temporal lobe lesions on memory in humans, together with attempts to model medial temporal lobe amnesia in animals, and we considered the nature of the information encoded by the hippocampus. Today we will consider in more detail the role of adjacent temporal cortex. We will examine the possibility that the hippocampus has a time-limited role in memory, considering models of consolidation, retrieval, and ‘reconsolidation’. We will then discuss the structures implicated in procedural memory.
Fidelity and yield in a volcano monitoring sensor network

We present a science-centric evaluation of a 19-day sensor network deployment at Reventador, an active volcano in Ecuador. Each of the 16 sensors continuously sampled seismic and acoustic data at 100 Hz. Nodes used an event-detection algorithm to trigger on interesting volcanic activity and initiate reliable data transfer to the base station. During the deployment, the network recorded 229 earthquakes, eruptions, and other seismoacoustic events. The science requirements of reliable data collection, accurate event detection, and high timing precision drive sensor networks in new directions for geophysical monitoring. The main contribution of this paper is an evaluation of the sensor network as a scientific instrument, holding it to the standards of existing instrumentation in terms of data fidelity (the quality and accuracy of the recorded signals) and yield (the quantity of the captured data). We describe an approach to time rectification of the acquired signals that can recover accurate timing despite failures of the underlying time synchronization protocol. In addition, we perform a detailed study of the sensor network's data using a direct comparison to a standalone data logger, as well as an investigation of seismic and acoustic wave arrival times across the network.
Aortic Impedance and Hydraulic Power in the Chick Embryo From Stages 18 to 29

Little is known about the hemodynamic properties of the rapidly expanding arterial bed during embryonic development. Using a servo-null pressure system and 20-MHz pulsed Doppler velocity meter, we recorded simultaneous dorsal aortic pressure and velocity waveforms. The waveforms were digitized at 3-msec intervals and subjected to Fourier analysis. We calculated hydraulic energy and the impedance spectrum to 10 Hz. From stages 18 to 29, heart rate (148±3 to 193±9 beats/min), systolic pressure (1.14±0.12 to 3.04±0.10 mm Hg), and mean dorsal aortic blood flow (21 ±2 to 214±19 mm3/min) increased. Peripheral vascular resistance (Z0: 30.4±4.8 to 6.4±0.7 dyneXsec/mm5), and the impedance moduli (Z1: 6.5±1.0 to 1.7±0.2 dyneYsec/mm5; Z2:6.1±1.2 to 1.7±0.1 dyneXsec/mm5; Z3: 7.3±1.1 to 1.7±0.2 dyneXsec/mm5) decreased. Total hydraulic power increased from 48±7 to 2,606±96 nW, while the proportion of oscillatory energy increased from 29±2percent; to 65±4percent;. With development hydraulic load decreases, total external work increases and the dorsal aorta and embryonic vascular bed becomes more compliant. A greater proportion of total energy is expanded in pulsatile blood flow, suggesting that ventricular-arterial coupling is less efficient later in development.
On the use of state-observers in compartmental systems control

In this paper we analyse the performance of state-observers in the control of compartmental systems under the presence of uncertainties in the system initial state. We combine a state feedback law with positivity constraints and a state observer and prove that, as expected, the mass control objective is still attained. Moreover we show that, for a class of three-compartmental systems of interest, the resulting mass control law also allows reaching a desired steady state. Our results are illustrated by several simulations for the control of the administration of a neuromuscular relaxant to patients undergoing surgery, which show the relevance of incorporating an observer for convergence acceleration even in case the original system is asymptotically stable.
THE OPTIMAL LEVEL OF METHIONINE AND LYSINE FOR TILPAIA FINGERLINGS ( OREOCHROMIS NILOTICUS )

This study was carried out in the fish laboratory of the Central Laboratory for Food and Feeds Agriculture Research Center and was designed to determine the optimal level of methionine and lysine in tilapia fingerling diets. Six experimental groups and a control treatment were assigned to one of the methionine or lysine levels. The control group contained methionine and lysine levels which were recommended by Santiago and Lovell (1988). All experimental diets were isonitrogenus (30% crude protein) and isocaloric (430 kcal / 100 g diet). Four dietary treatments with ascending levels of methionine (2.02, 2.72 (control), 3.45 and 4.11 g / 100 g crude protein), and varying levels of lysine (3.93, 5.12 (control), 6.2 and 7.87 g/ 100 g crude protein) were formulated. The seven tested diets were fed to 7 tilapia fingerling groups with initial body weight of 1.25 g / fish. Each experimental group consisted of 3 aquaria. The experiment duration was 14 weeks and the fish were fed at a rate of 3.5% of fish body weight daily. The daily allowances were fed at 5 meals. Results in terms of the highest final body weight, weight gain, specific growth rate, best feed conversion, protein efficiency and feed utilization showed that tilapia fingerlings require 2.72 g methionine and 5.12 g lysine / 100 g crude protein. Quadratic regression analysis of weight gain (%) against dietary methionine and lysine levels indicated that the optimal dietary methionine and lysine levels required for maximum growth was determined to be 3.05 % and 5.69 % of the dietary protein diet in the presence of 1.25 % cystine of the dietary protein diet, respectively. The results of the present study showed that the dietary requirements of methionine and lysine for tilapia fingerlings were 3.05% and 5.69% of the dietary crude protein, respectively.
Temporal-spatial variations and influencing factors of Lakes in inland arid areas from 2000 to 2017: a case study in Xinjiang

Abstract Lakes are the most important water resource in arid and semi-arid regions and are good indicators of climate change. The study of lake expansion and contraction can reveal important information about climate change and regional responses. In this study, MOD09A1 global surface reflectance data of MODIS are used to extract the water areas of 12 main lakes in Xinjiang using a support vector machine method to investigate the temporal-spatial dynamics and driving factors of lake area variations between 2000 and 2017. The results indicate that (1) In general, the Xinjiang lakes exhibited large fluctuations between 2000 and 2017; the area of the lakes shrunk by 16.98 km2/year during 2007–2009 but expanded by 80.67 km2/year after 2010. (2) The changes in the Xinjiang lakes exhibited obvious spatial differences. There were strong fluctuations in the areas of the Tail-end lakes and the K value describing the degree of fluctuation in the lake area was 0.2%. The fluctuations in the areas of the Mountain lakes were more stable with a K value of 0.09% and the area of the Plateau lakes increased every year, with an annual increase of 19.90 km2. (3) The lakes with the larger fluctuations in the area were Ebinur Lake, Manasi Lake, and Barkol Lake, and the range of the areas was 370.85, 276.55, and 61.5 km2, respectively. Because of the regional diversity of Xinjiang, the driving forces that affect the area of the lakes differ in different areas. The main factors affecting the lake area change in the Tail-end lakes are the amount of inflowing water and the water use by agriculture and animal husbandry. The main reason for the stability of the Mountain lakes is the balance between water inflow and outflow. The main factor contributing to the expansion of the Plateau lakes area is the abundant supply of glacier/snow melt water. Overall, the main factor contributing to the expansion of Plateau lakes area is abundant glacier snow melt water supply. On the whole, the main factors affecting the temporal and spatial variation of the lake areas in Xinjiang are precipitation (r = .67, p = .003 < .01), temperature (r = .611, p = .007 < .01), and the increase in cultivated land area (r = −.021, p = .004 < .01).