nils-herrmann/clean_scirepeval huggingface dataset:
Hybrid Compression of Bitvectors for the FM-Index

Compressed bit vectors supporting rank and select operations are the workhorse of compressed data structures. We propose a hybrid scheme for implementing compressed bit vectors, which divides the bit vector into blocks and then chooses the encoding of each block separately from a number of different encoding methods. Hybrid encoding is particularly suitable for bit vectors that have lots of local and regional variation, such as those present in the FM-index, a popular compressed data structure for pattern matching. We propose a specific hybrid combination of three simple encoding methods for FM-index bit vectors achieving superior space-time tradeoffs in experiments.
Motor control and learning in altered dynamic environments

Dynamic perturbations of reaching movements are an important technique for studying motor learning and adaptation. Adaptation to non-contacting, velocity-dependent inertial Coriolis forces generated by arm movements during passive body rotation is very rapid, and when complete the Coriolis forces are no longer sensed. Adaptation to velocity-dependent forces delivered by a robotic manipulandum takes longer and the perturbations continue to be perceived even when adaptation is complete. These differences reflect adaptive self-calibration of motor control versus learning the behavior of an external object or 'tool'. Velocity-dependent inertial Coriolis forces also arise in everyday behavior during voluntary turn and reach movements but because of anticipatory feedforward motor compensations do not affect movement accuracy despite being larger than the velocity-dependent forces typically used in experimental studies. Progress has been made in understanding: the common features that determine adaptive responses to velocity-dependent perturbations of jaw and limb movements; the transfer of adaptation to mechanical perturbations across different contact sites on a limb; and the parcellation and separate representation of the static and dynamic components of multiforce perturbations.
Fine-grained ultrasound range finding for mobile devices: Sensing way beyond the 24 kHz limit of built-in microphones

Range finding is a core service in many applications for smart homes and cities. Recently studies have been exploring ultrasound-based range finding with commercial-off-the-shelf (COTS) mobile devices. Yet their accuracy is largely bounded by the limited sample rate (typically up to 48 kHz; i.e. only sensitive to sound below 24 kHz) of their built-in microphones and chips. In this paper, we introduce a novel coprime-sampling-based method that can enable current COTS mobile devices to achieve accurate range finding by sensing very-high-frequency (> 24 kHz) ultrasound. We show that, through smart algorithm design, the hardware limit will not be a barrier for COTS devices to derive such useful information as phase shift and power spectral density (PSD) from very-high-frequency ultrasound signals. We discuss how our method can achieve fine-grained range finding, as well as improve other applications such as motion tracking and data transport. Through evaluations of our prototype on the latest Android tablet model, we show that with an ultrasound signal at 42 kHz, our method can achieve fine-grained range finding with a median error of 1.2 mm and a median accuracy of 97.3%.
Iatrogenic occlusion of the ophthalmic artery after cosmetic facial filler injections: a national survey by the Korean Retina Society.

Iatrogenic occlusion of the ophthalmic artery and its branches is a rare but devastating complication of cosmetic facial filler injections.



To investigate clinical and angiographic features of iatrogenic occlusion of the ophthalmic artery and its branches caused by cosmetic facial filler injections.



Data from 44 patients with occlusion of the ophthalmic artery and its branches after cosmetic facial filler injections were obtained retrospectively from a national survey completed by members of the Korean Retina Society from 27 retinal centers. Clinical features were compared between patients grouped by angiographic findings and injected filler material.



Visual prognosis and its relationship to angiographic findings and injected filler material.



Ophthalmic artery occlusion was classified into 6 types according to angiographic findings. Twenty-eight patients had diffuse retinal and choroidal artery occlusions (ophthalmic artery occlusion, generalized posterior ciliary artery occlusion, and central retinal artery occlusion). Sixteen patients had localized occlusions (localized posterior ciliary artery occlusion, branch retinal artery occlusion, and posterior ischemic optic neuropathy). Patients with diffuse occlusions showed worse initial and final visual acuity and less visual gain compared with those having localized occlusions. Patients receiving autologous fat injections (n = 22) had diffuse ophthalmic artery occlusions, worse visual prognosis, and a higher incidence of combined brain infarction compared with patients having hyaluronic acid injections (n = 13).



Clinical features of iatrogenic occlusion of the ophthalmic artery and its branches following cosmetic facial filler injections were diverse according to the location and extent of obstruction and the injected filler material. Autologous fat injections were associated with a worse visual prognosis and a higher incidence of combined cerebral infarction. Extreme caution and care should be taken during these injections, and physicians should be aware of a diverse spectrum of complications following cosmetic facial filler injections.
A Routing Protocol Based on Energy and Link Quality for Internet of Things Applications

The Internet of Things (IoT) is attracting considerable attention from the universities, industries, citizens and governments for applications, such as healthcare, environmental monitoring and smart buildings. IoT enables network connectivity between smart devices at all times, everywhere, and about everything. In this context, Wireless Sensor Networks (WSNs) play an important role in increasing the ubiquity of networks with smart devices that are low-cost and easy to deploy. However, sensor nodes are restricted in terms of energy, processing and memory. Additionally, low-power radios are very sensitive to noise, interference and multipath distortions. In this context, this article proposes a routing protocol based on Routing by Energy and Link quality (REL) for IoT applications. To increase reliability and energy-efficiency, REL selects routes on the basis of a proposed end-to-end link quality estimator mechanism, residual energy and hop count. Furthermore, REL proposes an event-driven mechanism to provide load balancing and avoid the premature energy depletion of nodes/networks. Performance evaluations were carried out using simulation and testbed experiments to show the impact and benefits of REL in small and large-scale networks. The results show that REL increases the network lifetime and services availability, as well as the quality of service of IoT applications. It also provides an even distribution of scarce network resources and reduces the packet loss rate, compared with the performance of well-known protocols.
Cognitive Screening Instruments

Cognitive disorders are common and likely to become more so as the world population ages. Pending the definition of reliable disease biomarkers, the identification of such disorders is likely to involve the use of cognitive screening instruments, as a prelude to effective management. The rationale and desiderata for effective cognitive screening instruments are considered in this chapter, prior to the description of methods for their assessment and in-depth analysis of specific instruments in subsequent chapters. The potential role of factors such as age, education, and culture on test performance and interpretation are also considered.
Classification of motor imagery hands movement using levenberg-marquardt algorithm based on statistical features of EEG signal

Motor Imagery (MI) is a highly supervised method nowadays for the disabled patients to give them hope. This paper proposes a differentiation method between imagery left and right hands movement using Daubechies wavelet of Discrete Wavelet Transform (DWT) and Levenberg-Marquardt back propagation training algorithm of Neural Network (NN). DWT decomposes the raw EEG data to extract significant features that provide feature vectors precisely. Levenberg-Marquardt Algorithm (LMA) based neural network uses feature vectors as input for classification of the two class data and outcomes overall classification accuracy of 92%. Previously various features and methods used but this recommended method exemplifies that statistical features provide better accuracy for EEG classification. Variation among features indicates differences between neural activities of two brain hemispheres due to two imagery hands movement. Results from the classifier are used to interface human brain with machine for better performance that requires high precision and accuracy scheme.
The characteristics of online sex offenders: a meta-analysis.

There is much debate as to whether online offenders are a distinct group of sex offenders or if they are simply typical sex offenders using a new technology. A meta-analysis was conducted to examine the extent to which online and offline offenders differ on demographic and psychological variables. Online offenders were more likely to be Caucasian and were slightly younger than offline offenders. In terms of psychological variables, online offenders had greater victim empathy, greater sexual deviancy, and lower impression management than offline offenders. Both online and offline offenders reported greater rates of childhood physical and sexual abuse than the general population. Additionally, online offenders were more likely to be Caucasian, younger, single, and unemployed compared with the general population. Many of the observed differences can be explained by assuming that online offenders, compared with offline offenders, have greater self-control and more psychological barriers to acting on their deviant interests.
A 5.6 nV/ $\surd $ Hz Chopper Operational Amplifier Achieving a 0.5  $\mu$ V Maximum Offset Over Rail-to-Rail Input Range With Adaptive Clock Boosting Technique

This paper presents a standalone 5.6 nV/√Hz chopper op-amp that operates from a 2.1-5.5 V supply. Frequency compensation is achieved in a power-and area-efficient manner by using a current attenuator and a dummy differential output. As a result, the overall op-amp only consumes 1.4 mA supply current and 1.26 mm2 die area. Up-modulated chopper ripple is suppressed by a local feedback technique, called auto correction feedback (ACFB). The charge injection of the input chopping switches can cause residual offset voltages, especially with the wider switches needed to reduce thermal noise. By employing an adaptive clock boosting technique with NMOS input switches, the amount of charge injection is minimized and kept constant as the input common-mode voltage changes. This results in a 0.5 μV maximum offset and 0.015 μV/°C maximum drift over the amplifier's entire rail-to-rail input common-mode range and from -40 °C to 125 °C. The design is implemented in a 0.35 μm CMOS process augmented by 5 V CMOS transistors.
Interface Representation Patterns: Crafting and Consuming Message-Based Remote APIs

Remote Application Programming Interfaces (APIs) are technology enablers for major distributed system trends such as mobile and cloud computing and the Internet of Things. In such settings, message-based APIs dominate over procedural and object-oriented ones. It is hard to design such APIs so that they are easy and efficient to use for client developers. Maintaining their runtime qualities while preserving backward compatibility is equally challenging for API providers. For instance, finding a well suited granularity for services and their operations is a particularly important design concern in APIs that realize service-oriented software architectures. Due to the fallacies of distributed computing, the forces for message-based APIs and service interfaces differ from those for local APIs -- for instance, network latency and security concerns deserve special attention. Existing pattern languages have dealt with local APIs in object-oriented programming, with remote objects, with queue-based messaging and with service-oriented computing platforms. However, patterns or equivalent guidance for the structural design of request and response messages in message-based remote APIs is still missing. In this paper, we outline such a pattern language and introduce five basic interface representation patterns to promote platform-independent design advice for common remote API technologies such as RESTful HTTP and Web services (WSDL/SOAP). Known uses and examples of the patterns are drawn from public Web APIs, as well as application development and software integration projects the authors have been involved in.
Extreme cerebrospinal fluid amyloid beta levels identify family with late-onset Alzheimer's disease presenilin 1 mutation.

Aggregation and deposition of amyloid beta (Abeta) in the brain is thought to be central to the pathogenesis of Alzheimer's disease (AD). Recent studies suggest that cerebrospinal fluid (CSF) Abeta levels are strongly correlated with AD status and progression, and may be a meaningful endophenotype for AD. Mutations in presenilin 1 (PSEN1) are known to cause AD and change Abeta levels. In this study, we have investigated DNA sequence variation in the presenilin (PSEN1) gene using CSF Abeta levels as an endophenotype for AD.



We sequenced the exons and flanking intronic regions of PSEN1 in clinically characterized research subjects with extreme values of CSF Abeta levels.



This novel approach led directly to the identification of a disease-causing mutation in a family with late-onset AD.



This finding suggests that CSF Abeta may be a useful endophenotype for genetic studies of AD. Our results also suggest that PSEN1 mutations can cause AD with a large range in age of onset, spanning both early- and late-onset AD.
Development of newly bump support film (BSF) for WLCSP

Solder joint crack is increasing with increasing of warpage caused by larger Wafer Level Chip Size Package (WLCSP). Bump Support Film (BSF) were proposed as a protect material for preventing a solder joint crack of bumps. The BSF was constructed of a back grind tape and Bump Support Layer (BSL) which was composed of thermosetting epoxy resin. One of the key points of forming the BSL on a wafer which have bumps on circuit surface is to remove organic residues of BSL on the bump top for keeping a good electric connection. In this study, we selected a plasma cleaning process as a removal method of the slightly amount of BSL residue on the bump top. We succeeded to optimize a plasma condition for a good electric connection, and quantify the removal amount of BSL residue by XPS analysis.
A facile technique to prepare biodegradable coaxial electrospun nanofibers for controlled release of bioactive agents.

A one-step, mild procedure based on coaxial electrospinning was developed for incorporation and controlled release of two model proteins, BSA and lysozyme, from biodegradable core-shell nanofibers with PCL as shell and protein-containing PEG as core. The thickness of the core and shell could be adjusted by the feed rate of the inner dope, which in turn affected the release profiles of the incorporated proteins. It was revealed that the released lysozyme maintained its structure and bioactivity. The current method may find wide applications for controlled release of proteins and tissue engineering.
Probabilistic Dense Reconstruction from a Moving Camera

This paper presents a probabilistic approach for online dense reconstruction using a single monocular camera moving through the environment. Compared to spatial stereo, depth estimation from motion stereo is challenging due to insufficient parallaxes, visual scale changes, pose errors, etc. We utilize both the spatial and temporal correlations of consecutive depth estimates to increase the robustness and accuracy of monocular depth estimation. An online, recursive, probabilistic scheme to compute depth estimates, with corresponding covariances and inlier probability expectations, is proposed in this work. We integrate the obtained depth hypotheses into dense 3D models in an uncertainty-aware way. We show the effectiveness and efficiency of our proposed approach by comparing it with state-of-the-art methods in the TUM RGB-D SLAM & ICL-NUIM dataset. Online indoor and outdoor experiments are also presented for performance demonstration.
An introduction to voice search

Voice search is the technology underlying many spoken dialog systems (SDSs) that provide users with the information they request with a spoken query. The information normally exists in a large database, and the query has to be compared with a field in the database to obtain the relevant information. The contents of the field, such as business or product names, are often unstructured text. This article categorized spoken dialog technology into form filling, call routing, and voice search, and reviewed the voice search technology. The categorization was made from the technological perspective. It is important to note that a single SDS may apply the technology from multiple categories. Robustness is the central issue in voice search. The technology in acoustic modeling aims at improved robustness to environment noise, different channel conditions, and speaker variance; the pronunciation research addresses the problem of unseen word pronunciation and pronunciation variance; the language model research focuses on linguistic variance; the studies in search give rise to improved robustness to linguistic variance and ASR errors; the dialog management research enables graceful recovery from confusions and understanding errors; and the learning in the feedback loop speeds up system tuning for more robust performance. While tremendous achievements have been accomplished in the past decade on voice search, large challenges remain. Many voice search dialog systems have automation rates around or below 50% in field trials.
Concept and design of a modular lower limb exoskeleton

Powered lower limb exoskeletons become more and more common and are used for different applications such as rehabilitation and human strength augmentation. However, many of the existing designs are limited to a very specific task. We present the concept and design of a modular, reconfigurable lower limb exoskeleton that can be adapted with respect to it's kinematics and actuation to a wide range of users and applications. The introduced modular design allows to compose lower limb exoskeletons with up to four degrees of freedom per leg: abduction/adduction of the hip and flexion/extension of the hip, knee, and ankle. Each passive joint can be extended by a module in terms of functionality, e.g. by actuation or spring stabilization. Three different modules are introduced: one actuator for active support and two spring modules that stabilize the joint around an equilibrium position. Using the presented components, three exemplary systems are composed and discussed: An active hip support exoskeleton, a fully articulated lower limb exoskeleton for gait support and a system for treadmill based gait rehabilitation. The three designs show that the concept of a modular exoskeleton is feasible and that it can be an alternative to a specialized system for environments with changing requirements, for example in rehabilitation or research.
Visual attention as a multilevel selection process.

Natural visual scenes are cluttered and contain many different objects that cannot all be processed simultaneously. Therefore, attentional mechanisms are needed to select relevant and to filter out irrelevant information. Evidence from functional brain imaging reveals that attention operates at various processing levels within the visual system and beyond. First, the lateral geniculate nucleus appears to be the first stage in the processing of visual information that is modulated by attention, consistent with the idea that it may play an important role as an early gatekeeper in controlling neural gain. Second, areas at intermediate cortical-processing levels, such as V4 and TEO, appear to be important sites at which attention filters out unwanted information by means of receptive field mechanisms. Third, the attention mechanisms that operate in the visual system appear to be controlled by a distributed network of higher order areas in the frontal and parietal cortex, which generate top-down signals that are transmitted via feedback connections to the visual system. And fourth, the pulvinar of the thalamus may operate by integrating and coordinating attentional functions in concert with the fronto-parietal network, although much needs to be learned about its functional properties. The overall view that emerges from the studies reviewed in this article is that neural mechanisms of selective attention operate at multiple stages in the visual system and beyond and are determined by the visual processing capabilities of each stage. In this respect, attention can be considered in terms of a multilevel selection process.
0.01-50 GHz power detector MMICs

This work presents a pass-type ultrawideband power detector MMICs designed for operation from 10 MHz to 50 GHz in a wide dynamic range from -40 dBm to +25 dBm which were fabricated using GaAs zero bias diode process. Directional and non-directional detector designes are reviwed. For good wideband matching with transmission line, bonding wires parameters were taken into account at the stage of MMIC design. Result of this work includes on-wafer measurements of MMICs S-parameters and transfer characteristics.
Permutation inference for the general linear model

Permutation methods can provide exact control of false positives and allow the use of non-standard statistics, making only weak assumptions about the data. With the availability of fast and inexpensive computing, their main limitation would be some lack of flexibility to work with arbitrary experimental designs. In this paper we report on results on approximate permutation methods that are more flexible with respect to the experimental design and nuisance variables, and conduct detailed simulations to identify the best method for settings that are typical for imaging research scenarios. We present a generic framework for permutation inference for complex general linear models (GLMS) when the errors are exchangeable and/or have a symmetric distribution, and show that, even in the presence of nuisance effects, these permutation inferences are powerful while providing excellent control of false positives in a wide range of common and relevant imaging research scenarios. We also demonstrate how the inference on GLM parameters, originally intended for independent data, can be used in certain special but useful cases in which independence is violated. Detailed examples of common neuroimaging applications are provided, as well as a complete algorithm - the "randomise" algorithm - for permutation inference with the GLM.
Equity market momentum : A synthesis of the literature and suggestions for future work

I review the literature on equity market momentum, a seminal and intriguing finding in finance. This phenomenon is the ability of returns over the past one to four quarters to predict future returns over the same period in the cross-section of equities. I am able to document about ten different theories for momentum, and a large volume of empirical work on the topic. I find, however, that after a quarter century following the discovery of momentum by Jegadeesh and Titman (1993), we are still no closer to finding a discernible cause for this phenomenon, in spite of the extensive work on the topic. More needs to be done to develop tests that are focused not so much on testing one specific theory, but on ruling out alternative