nils-herrmann/clean_scirepeval huggingface dataset:
A Portable 2-Transistor Picowatt Temperature-Compensated Voltage Reference Operating at 0.5 V

Sensing systems such as biomedical implants, infrastructure monitoring systems, and military surveillance units are constrained to consume only picowatts to nanowatts in standby and active mode, respectively. This tight power budget places ultra-low power demands on all building blocks in the systems. This work proposes a voltage reference for use in such ultra-low power systems, referred to as the 2T voltage reference, which has been demonstrated in silicon across three CMOS technologies. Prototype chips in 0.13 μm show a temperature coefficient of 16.9 ppm/°C (best) and line sensitivity of 0.033%/V, while consuming 2.22 pW in 1350 μm2. The lowest functional Vdd 0.5 V. The proposed design improves energy efficiency by 2 to 3 orders of magnitude while exhibiting better line sensitivity and temperature coefficient in less area, compared to other nanowatt voltage references. For process spread analysis, 49 dies are measured across two runs, showing the design exhibits comparable spreads in TC and output voltage to existing voltage references in the literature. Digital trimming is demonstrated, and assisted one temperature point digital trimming, guided by initial samples with two temperature point trimming, enables TC <; 50 ppm/°C and ±0.35% output precision across all 25 dies. Ease of technology portability is demonstrated with silicon measurement results in 65 nm, 0.13 μm, and 0.18 μm CMOS technologies.
Robust control of underactuated Aerial Manipulators via IDA-PBC

Aerial Manipulators (AMs) are a special class of underactuated mechanical systems formed by the join of Unmanned Aerial Vehicles (UAVs) and manipulators. A thorough analysis of the dynamics and a fully constructive controller design for a quadrotor plus n-link manipulator in a free-motion on an arbitrary plane is provided, via the lDA-PBC methodology. A controller is designed with the manipulator locked at any position ensuring global asymptotic stability in an open set and avoiding the AM goes upside down (autonomous). The major result of stability/robustness arises when it is proved that, additionally, the controller guarantees the boundedness of the trajectories for bounded movements of the manipulator, i.e. the robot manipulator executing planned tasks, giving rise to a non-autonomous port-controlled Hamiltonian system in closed loop. Moreover, all trajectories converge to a positive limit set, a strong result for matching-type controllers.
Toward Controlled Generation of Text

Generic generation and manipulation of text is challenging and has limited success compared to recent deep generative modeling in visual domain. This paper aims at generating plausible text sentences, whose attributes are controlled by learning disentangled latent representations with designated semantics. We propose a new neural generative model which combines variational auto-encoders (VAEs) and holistic attribute discriminators for effective imposition of semantic structures. The model can alternatively be seen as enhancing VAEs with the wake-sleep algorithm for leveraging fake samples as extra training data. With differentiable approximation to discrete text samples, explicit constraints on independent attribute controls, and efficient collaborative learning of generator and discriminators, our model learns interpretable representations from even only word annotations, and produces short sentences with desired attributes of sentiment and tenses. Quantitative experiments using trained classifiers as evaluators validate the accuracy of sentence and attribute generation.
A Novel Construction of Substitution Box Involving Coset Diagram and a Bijective Map

1Department of Mathematics, University of Education Lahore, Jauharabad Campus, Jauharabad, Pakistan 2Department of Mathematics, The Islamia University of Bahawalpur, Bahawalpur, Pakistan 3Department of Mathematics, Government College University Faisalabad, Faisalabad, Pakistan 4Department of Basic Sciences, University of Engineering and Technology, Taxila, Punjab, Pakistan 5Department of Mathematics, Quaid-i-Azam University, Islamabad, Pakistan 6Department of Information Technology, University of Education Lahore, Jauharabad Campus, Jauharabad, Pakistan
Lateralization of phonetic and pitch discrimination in speech processing.

Cerebral activation was measured with positron emission tomography in ten human volunteers. The primary auditory cortex showed increased activity in response to noise bursts, whereas acoustically matched speech syllables activated secondary auditory cortices bilaterally. Instructions to make judgments about different attributes of the same speech signal resulted in activation of specific lateralized neural systems. Discrimination of phonetic structure led to increased activity in part of Broca's area of the left hemisphere, suggesting a role for articulatory recoding in phonetic perception. Processing changes in pitch produced activation of the right prefrontal cortex, consistent with the importance of right-hemisphere mechanisms in pitch perception.
Personalized Microblog Sentiment Classification via Adversarial Cross-lingual Multi-task Learning

Sentiment expression in microblog posts can be affected by user’s personal character, opinion bias, political stance and so on. Most of existing personalized microblog sentiment classification methods suffer from the insufficiency of discriminative tweets for personalization learning. We observed that microblog users have consistent individuality and opinion bias in different languages. Based on this observation, in this paper we propose a novel user-attention-based Convolutional Neural Network (CNN) model with adversarial cross-lingual learning framework. The user attention mechanism is leveraged in CNN model to capture user’s languagespecific individuality from the posts. Then the attention-based CNN model is incorporated into a novel adversarial cross-lingual learning framework, in which with the help of user properties as bridge between languages, we can extract the language-specific features and language-independent features to enrich the user post representation so as to alleviate the data insufficiency problem. Results on English and Chinese microblog datasets confirm that our method outperforms state-of-the-art baseline algorithms with large margins.
Fuzzy logic Controller Design for gun-turret system

High precision control is desirable for future weapon systems. In this paper, several control design methodologies are applied to a weapon system to assess the applicability of each control design method and to characterize the achievable performance of the gun-turret system in precision control. The design objective of the gun-turret control system is to achieve a rapid and precise tracking response with respect to the turret motor command from the fire control system under the influences of disturbances, nonlinearities, and modeling uncertainties. A fuzzy scheme is proposed for control of multi-body, multi-input and multioutput nonlinear systems with joints represented by a gun turret-barrel model which consists of two subsystems: two motors driving two loads (turret and barrel) coupled by nonlinear dynamics. Fuzzy control schemes are employed for compensation and nonlinear feedback control laws are used for control of nonlinear dynamics. Fuzzy logic control (FLC) provides an effective means of capturing the approximate, inexact nature of the real world, and to address unexpected parameter variations and anomalies. Viewed in this perspective, the essential part of the FLC is a set of linguistic control rules related by the dual concepts of fuzzy implication and the compositional rule of inference. In essence, the FLC provides an algorithm which can convert the linguistic control strategy based on expert knowledge into an automatic control strategy. Accordingly, the design must be robust, adaptive, and, hopefully, intelligent in order to accommodate these uncertainties. Simulation results verify the desired system tracking performance.
Matching dicrotic notch and mean pulmonary artery pressures: implications for effective arterial elastance.

It has been suggested that pulmonary artery pressure at the end of ejection is close to mean pulmonary artery pressure, thus contributing to the optimization of external power from the right ventricle. We tested the hypothesis that dicrotic notch and mean pulmonary artery pressures could be of similar magnitude in 15 men (50 +/- 12 yr) referred to our laboratory for diagnostic right and left heart catheterization. Beat-to-beat relationships between dicrotic notch and mean pulmonary artery pressures were studied 1) at rest over 10 consecutive beats and 2) in 5 patients during the Valsalva maneuver (178 beats studied). At rest, there was no difference between dicrotic notch and mean pulmonary artery pressures (21.8 +/- 12.0 vs. 21.9 +/- 11.1 mmHg). There was a strong linear relationship between dicrotic notch and mean pressures 1) over the 10 consecutive beats studied in each patient (mean r = 0.93), 2) over the 150 resting beats (r = 0.99), and 3) during the Valsalva maneuver in each patient (r = 0.98-0.99) and in the overall beats (r = 0.99). The difference between dicrotic notch and mean pressures was -0.1 +/- 1.7 mmHg at rest and -1.5 +/- 2.3 mmHg during the Valsalva maneuver. Substitution of the mean pulmonary artery pressure by the dicrotic notch pressure in the standard formula of the pulmonary vascular resistance (PVR) resulted in an equation relating linearly end-systolic pressure and stroke volume. The slope of this relation had the dimension of a volume elastance (in mmHg/ml), a simple estimate of volume elastance being obtained as 1.06(PVR/T), where T is duration of the cardiac cycle. In conclusion, dicrotic notch pressure was of similar magnitude as mean pulmonary artery pressure. These results confirmed our primary hypothesis and indicated that human pulmonary artery can be treated as if it is an elastic chamber with a volume elastance of 1.06(PVR/T).
A systematic review of dietary protein during caloric restriction in resistance trained lean athletes: a case for higher intakes.

Caloric restriction occurs when athletes attempt to reduce body fat or make weight. There is evidence that protein needs increase when athletes restrict calories or have low body fat.



The aims of this review were to evaluate the effects of dietary protein on body composition in energy-restricted resistance-trained athletes and to provide protein recommendations for these athletes.



Database searches were performed from earliest record to July 2013 using the terms protein, and intake, or diet, and weight, or train, or restrict, or energy, or strength, and athlete. Studies (N = 6) needed to use adult (≥ 18 yrs), energy-restricted, resistance-trained (> 6 months) humans of lower body fat (males ≤ 23% and females ≤ 35%) performing resistance training. Protein intake, fat free mass (FFM) and body fat had to be reported.



Body fat percentage decreased (0.5-6.6%) in all study groups (N = 13) and FFM decreased (0.3-2.7kg) in nine of 13. Six groups gained, did not lose, or lost nonsignificant amounts of FFM. Five out of these six groups were among the highest in body fat, lowest in caloric restriction, or underwent novel resistance training stimuli. However, the one group that was not high in body fat that underwent substantial caloric restriction, without novel training stimuli, consumed the highest protein intake out of all the groups in this review (2.5-2.6g/kg).



Protein needs for energy-restricted resistance-trained athletes are likely 2.3-3.1g/kg of FFM scaled upwards with severity of caloric restriction and leanness.
Communities of practice and social learning systems 1 Communities of practice and social learning systems : the career of a concept

The concept of community of practice was not born in the systems theory tradition. It has its roots in attempts to develop accounts of the social nature of human learning inspired by anthropology and social theory (Lave, 1988; Bourdieu, 1977; Giddens, 1984; Foucault, 1980; Vygostsky, 1978). But the concept of community of practice is well aligned with the perspective of the systems tradition. A community of practice itself can be viewed as a simple social system. And a complex social system can be viewed as constituted by interrelated communities of practice. In this essay I first explore the systemic nature of the concept at these two levels. Then I use this foundation to look at the applications of the concept, some of its main critiques, and its potential for developing a social discipline of learning.
A Neural Temporal Model for Human Motion Prediction

We propose novel neural temporal models for predicting and synthesizing human motion, achieving state-of-theart in modeling long-term motion trajectories while being competitive with prior work in short-term prediction, with significantly less required computation. Key aspects of our proposed system include: 1) a novel, two-level processing architecture that aids in generating planned trajectories, 2) a simple set of easily computable features that integrate derivative information into the model, and 3) a novel multi-objective loss function that helps the model to slowly progress from the simpler task of next-step prediction to the harder task of multi-step closed-loop prediction. Our results demonstrate that these innovations facilitate improved modeling of long-term motion trajectories. Finally, we propose a novel metric, called Normalized Power Spectrum Similarity (NPSS), to evaluate the long-term predictive ability of motion synthesis models, complementing the popular mean-squared error (MSE) measure of the Euler joint angles over time. We conduct a user study to determine if the proposed NPSS correlates with human evaluation of longterm motion more strongly than MSE and find that it indeed does.
Wearable textile microstrip patch antenna for multiple ISM band communications

A wearable probe-fed microstrip antenna manufactured from conductive textile fabric designed for multiple Industrial-Scientific-Medical (ISM) band communications is presented in this paper. The proposed antenna operating at 2.450 GHz, 4.725 Hz and 5.800 GHz consists of a patch and ground plane made of silver fabric mounted on a substrate of flexible low-permittivity foam. For verification, a reference prototype is manufactured from copper. The measurement of both antennas demonstrates the expected resonances, with some unexpected loss especially in the higher frequency range. Simulation results for the antenna in various bending condition indicate the robustness of the design with deviations of resonant frequencies in an acceptable range.
Building Software-Defined Radios in MATLAB Simulink - A Step Towards Cognitive Radios

Software Defined Radio (SDR) is a flexible architecture which can be configured to adapt various wireless standards, waveforms, frequency bands, bandwidths, and modes of operations. This paper presents a detailed survey of the existing hardware and software platform for SDRs. It also presents prototype system for designing and testing of software defined radios in MATLAB/Simulink and briefly discusses the salient functions of the prototype system for Cognitive Radio (CR). A prototype system for wireless personal area network is built and interfaced with a Universal Software Radio Peripheral-2 (USRP2) main-board and RFX2400 daughter board from Ettus Research LLC. The philosophy behind the prototype is to do all waveform-specific processing such as channel coding, modulation, filtering etc. on a host (PC) and general purpose high-speed operations like digital up and down conversion, decimation and interpolation etc. inside FPGA on an USRP2. MATLAB has a rich family of toolboxes that allows building software-defined and cognitive radio to explore various spectrum sensing, prediction and management techniques.
On the Structure of Resultative Participles in English

The article examines the structure of resultative participles in English: participles that denote a state resulting from a prior event, such as The cake is flattened or The metal is hammered.The analysis identifies distinct stative participles that derive from the different heights at which aspectual morphemes attach in a verbalizing structure.The Aspect head involved in resultative participles is shown to attach to a vP that is also found in (a) the formation of deadjectival verbs and (b) verb phrases with resultative secondary predicates, like John hammered the metal flat. These distinct constructions are shown to have a shared structural subcomponent.The analysis proposed here is compared with Lexicalist approaches employing the verbal versus adjectival passive distinction.It is shown that a uniformly syntactic analysis of the participles is superior to the Lexicalist alternative.
Sketch retrieval via local dense stroke features

Article history: Received 13 August 2014 Received in revised form 11 July 2015  Sketch retrieval aims at retrieving the most similar sketches from a large database based on one hand-drawn query. Successful retrieval hinges on an effective representation of sketch images and an efficient searchmethod. In this paper, we propose a representation scheme which takes sketch strokes into account with local features, thereby facilitating efficient retrieval with codebooks. Stroke features are detected via densely sampled points on stroke lines with crucial corners as anchor points, from which local gradients are enhanced and described by a quantized histogramof gradients. A codebook is organized in a hierarchical vocabulary tree,whichmaintains structural information of visual words and enables efficient retrieval in sub-linear time. Experimental results on three data sets demonstrate the merits of the proposed algorithm for effective and efficient sketch retrieval.
Moderate treadmill exercise ameliorates amyloid-β-induced learning and memory impairment, possibly via increasing AMPK activity and up-regulation of the PGC-1α/FNDC5/BDNF pathway

Alzheimer's disease (AD) is a neurodegenerative disorder associated with loss of memory and cognitive abilities. Previous evidence suggested that exercise ameliorates learning and memory deficits by increasing brain derived neurotrophic factor (BDNF) and activating downstream pathways in AD animal models. However, upstream pathways related to increase BDNF induced by exercise in AD animal models are not well known. We investigated the effects of moderate treadmill exercise on Aβ-induced learning and memory impairment as well as the upstream pathway responsible for increasing hippocampal BDNF in an animal model of AD. Animals were divided into five groups: Intact, Sham, Aβ1-42, Sham-exercise (Sham-exe) and Aβ1-42-exercise (Aβ-exe). Aβ was microinjected into the CA1 area of the hippocampus and then animals in the exercise groups were subjected to moderate treadmill exercise (for 4 weeks with 5 sessions per week) 7 days after microinjection. In the present study the Morris water maze (MWM) test was used to assess spatial learning and memory. Hippocampal mRNA levels of BDNF, peroxisome proliferator-activated receptor gamma co-activator 1 alpha (PGC-1α), fibronectin type III domain-containing 5 (FNDC5) as well as protein levels of AMPK-activated protein kinase (AMPK), PGC-1α, BDNF, phosphorylation of AMPK were measured. Our results showed that intra-hippocampal injection of Aβ1-42 impaired spatial learning and memory which was accompanied by reduced AMPK activity (p-AMPK/total-AMPK ratio) and suppression of the PGC-1α/FNDC5/BDNF pathway in the hippocampus of rats. In contrast, moderate treadmill exercise ameliorated the Aβ1-42-induced spatial learning and memory deficit, which was accompanied by restored AMPK activity and PGC-1α/FNDC5/BDNF levels. Our results suggest that the increased AMPK activity and up-regulation of the PGC-1α/FNDC5/BDNF pathway by exercise are likely involved in mediating the beneficial effects of exercise on Aβ-induced learning and memory impairment.
Whale optimization algorithm for optimal sizing of renewable resources for loss reduction in distribution systems

Distributed generator (DG) resources are small scale electric power generating plants that can provide power to homes, businesses or industrial facilities in distribution systems. Power loss reductions, voltage profile improvement and increasing reliability are some advantages of DG units. The above benefits can be achieved by optimal placement of DGs. Whale optimization algorithm (WOA), a novel metaheuristic algorithm, is used to determine the optimal DG size. WOA is modeled based on the unique hunting behavior of humpback whales. The WOA is evaluated on IEEE 15, 33, 69 and 85-bus test systems. WOA was compared with different types of DGs and other evolutionary algorithms. When compared with voltage sensitivity index method, WOA and index vector methods gives better results. From the analysis best results have been achieved from type III DG operating at 0.9 pf.
Speech production: Wernicke, Broca and beyond.

We investigated the brain systems engaged during propositional speech (PrSp) and two forms of non- propositional speech (NPrSp): counting and reciting overlearned nursery rhymes. Bilateral cerebral and cerebellar regions were involved in the motor act of articulation, irrespective of the type of speech. Three additional, left-lateralized regions, adjacent to the Sylvian sulcus, were activated in common: the most posterior part of the supratemporal plane, the lateral part of the pars opercularis in the posterior inferior frontal gyrus and the anterior insula. Therefore, both NPrSp and PrSp were dependent on the same discrete subregions of the anatomically ill-defined areas of Wernicke and Broca. PrSp was also dependent on a predominantly left-lateralized neural system distributed between multi-modal and amodal regions in posterior inferior parietal, anterolateral and medial temporal and medial prefrontal cortex. The lateral prefrontal and paracingulate cortical activity observed in previous studies of cued word retrieval was not seen with either NPrSp or PrSp, demonstrating that normal brain- language representations cannot be inferred from explicit metalinguistic tasks. The evidence from this study indicates that normal communicative speech is dependent on a number of left hemisphere regions remote from the classic language areas of Wernicke and Broca. Destruction or disconnection of discrete left extrasylvian and perisylvian cortical regions, rather than the total extent of damage to perisylvian cortex, will account for the qualitative and quantitative differences in the impaired speech production observed in aphasic stroke patients.
An improved endpoint detector for isolated word recognition

Accurate location of the endpoints of an isolated word is important for reliable and robust word recognition. The endpoint detection problem is nontrivial for nonstationary backgrounds where artifacts (i.e., nonspeech events) may be introduced by the speaker, the recording environment, and the transmission system. Several techniques for the detection of the endpoints of isolated words recorded over a dialed-up telephone line were studied. The techniques were broadly classified as either explicit, implicit, or hybrid in concept. The explicit techniques for endpoint detection locate the endpoints prior to and independent of the recognition and decision stages of the system. For the implicit methods, the endpoints are determined solely by the recognition and decision stages Of the system, i.e., there is no separate stage for endpoint detection. The hybrid techniques incorporate aspects from both the explicit and implicit methods. Investigations showed that the hybrid techniques consistently provided the best estimates for both of the word endpoints and, correspondingly, the highest recognition accuracy of the three classes studied. A hybrid endpoint detector is proposed which gives a rejection rate of less than 0.5 percent, while providing recognition accuracy close to that obtained from hand-edited endpoints.