nils-herrmann/clean_scirepeval huggingface dataset:
Dwarf germplasm: the key to giant Cannabis hempseed and cannabinoid crops

After a century of banishment, both euphoric (“marijuana”) and non-euphoric (“industrial hemp”) classes of Cannabis sativa are attracting billions of dollars of investment as new legitimate crops. Most domesticated C. sativa is very tall, a phenotype that is desirable only for hemp fibre obtained from the stems. However, because the principal demands today are for chemicals from the inflorescence and oilseeds from the infructescence, an architecture maximizing reproductive tissues while minimizing stems is appropriate. Such a design was the basis of the greatest short-term increases in crop productivity in the history of agriculture: the creation of short-stature (“semi-dwarf”), high-harvest-index grain cultivars, especially by ideotype breeding, as demonstrated during the “Green Revolution.” This paradigm has considerable promise for C. sativa. The most critical dwarfing character for breeding such productivity into C. sativa is contraction of internodes. This reduces stem tissues (essentially a waste product except for fibre hemp) and results in compact inflorescences (which, on an area basis, maximize cannabinoid chemicals) and infructescences (which maximize oilseed production), as well as contributing to ease of harvesting and efficiency of production on an area basis. Four sources of germplasm useful for breeding semi-dwarf biotypes deserve special attention: (1) Naturally short northern Eurasian wild plants (often photoperiodically day-neutral, unlike like most biotypes) adapted to the stress of very short seasons by maximizing relative development of reproductive tissues. (2) Short, high-harvest-index, oilseed plants selected in northern regions of Eurasia. (3) “Indica type” marijuana, an ancient semi-dwarf cultigen tracing to the Afghanistan-Pakistan area. (4) Semi-dwarf strains of marijuana bred illegally in recent decades to avoid detection when grown clandestinely indoors for the black market. Although the high THC content in marijuana strains limits their usage as germplasm for low-THC cultivars, modern breeding techniques can control this variable. The current elimination of all marijuana germplasm from breeding of hemp cultivars is short-sighted because marijuana biotypes possess a particularly wide range of genes. There is an urgent need to develop public gene bank collections of Cannabis.
Probabilistic information retrieval approach for ranking of database query results

We investigate the problem of ranking the answers to a database query when many tuples are returned. In particular, we present methodologies to tackle the problem for conjunctive and range queries, by adapting and applying principles of probabilistic models from information retrieval for structured data. Our solution is domain independent and leverages data and workload statistics and correlations. We evaluate the quality of our approach with a user survey on a real database. Furthermore, we present and experimentally evaluate algorithms to efficiently retrieve the top ranked results, which demonstrate the feasibility of our ranking system.
The description–experience gap in risky choice

According to a common conception in behavioral decision research, two cognitive processes-overestimation and overweighting-operate to increase the impact of rare events on people's choices. Supportive findings stem primarily from investigations in which people learn about options via descriptions thereof. Recently, a number of researchers have begun to investigate risky choice in settings in which people learn about options by experiential sampling over time. This article reviews work across three experiential paradigms. Converging findings show that when people make decisions based on experience, rare events tend to have less impact than they deserve according to their objective probabilities. Striking similarities in human and animal experience-based choices, ways of modeling these choices, and their implications for risk and precautionary behavior are discussed.
A fully connected layer elimination for a binarizec convolutional neural network on an FPGA

A pre-trained convolutional deep neural network (CNN) is widely used for embedded systems, which requires highly power-and-area efficiency. In that case, the CPU is too slow, the embedded GPU dissipates much power, and the ASIC cannot keep up with the rapidly progress of the CNN variations. This paper uses a binarized CNN which treats only binary 2-values for the inputs and the weights. Since the multiplier is replaced into an XNOR circuit, we can realize a high-performance MAC circuit by using many XNOR circuits. In the paper, we eliminate internal FC layers excluding the last one, then, insert a binarized average pooling layer, which can be realized by a majority circuit for binarized (1/0) values. In that case, since the weight memory is replaced into the 1's counter, we can realize a compact and faster CNN than the conventional ones. We implemented the VGG-11 benchmark CNN for the CIFAR10 image classification task on the Xilinx Inc. Zedboard. Compared with the conventional binarized implementations on an FPGA, the classification accuracy was almost the same, the performance per power efficiency is 5.1 better, as for the performance per area efficiency, it is 8.0 times better, and as for the performance per memory, it is 8.2 times better.
Helicopter induced propeller injuries.

Following routine maintenance a military helicopter was returned to service. Due to negligence some hoses had not been connected correctly. The wrongly connected hoses resulted in a malfunction, causing the rotor blades of the helicopter to smash through the windows of the helicopter cockpit. Both the pilot and the co-pilot were hit by the rotor blades and decapitated. Other passengers in the helicopter were injured. Due to vibrations the helicopter fell to the ground and its tail partly broke away (Figs. 1, 2). The bodies and body parts of the pilot and co-pilot were found on the ground outside the helicopter cockpit.
Face detection using SURF cascade

We present a novel boosting cascade based face detection framework using SURF features. The framework is derived from the well-known Viola-Jones (VJ) framework but distinguished by two key contributions. First, the proposed framework deals with only several hundreds of multidimensional local SURF patches instead of hundreds of thousands of single dimensional haar features in the VJ framework. Second, it takes AUC as a single criterion for the convergence test of each cascade stage rather than the two conflicting criteria (false-positive-rate and detection-rate) in the VJ framework. These modifications yield much faster training convergence and much fewer stages in the final cascade. We made experiments on training face detector from large scale database. Results shows that the proposed method is able to train face detectors within one hour through scanning billions of negative samples on current personal computers. Furthermore, the built detector is comparable to the state-of-the-art algorithm not only on the accuracy but also on the processing speed.
UI on the Fly: Generating a Multimodal User Interface

UI on the Fly is a system that dynamically presents coordinated multimodal content through natural language and a small-screen graphical user interface. It adapts to the user’s preferences and situation. Multimodal Functional Unification Grammar (MUG) is a unification-based formalism that uses rules to generate content that is coordinated across several communication modes. Faithful variants are scored with a heuristic function.
Investigation of additional AC losses in tooth-coil winding PMSM with high electrical frequency

Stator winding structure and its manufacturing in permanent magnet synchronous machines (PMSM) is the vital part of the whole machine design. It is important to follow particular procedures in order to keep the winding losses at the acceptable level, which include DC resistance loss and additional losses due to alternative magnetic flux within the area of the stator winding. The winding transposition or using of Litz wire, which is effective way of proximity loss suppression, sometimes cannot be implemented due to challenges in assembling or cost aspects (especially in low cost PMSM solutions). In this case it is important to know consequences of using straight (non-twisting) windings in PMSMs with relatively high electrical frequency. This article studies impact of the number of stator winding parallel strands on the additional AC losses distribution in the slot where this winding is located. Also, thermal condition (which impacts the life time of the insulation) of the winding is analyzed with different number of parallel strands. Current and temperature distributions in the slot conductors were attained by finite element method (FEM). The total losses caused by additional AC losses in the winding were compared with the measurements results.
A probabilistic framework for object search with 6-DOF pose estimation

This article presents a systematic approach to the problem of autonomous 3D object search in indoor environments, using a two-wheeled non-holonomic robot equipped with an actuated stereo-camera head and processing done on a single laptop. A probabilistic grid-based map encodes the likelihood of object existence in each cell and is updated after each sensing action. The updating schema incorporates characteristic parameters modeled after the robot’s sensing modalities and allows for sequential updating via Bayesian recursion methods. Two types of sensing modalities are used to update the map: a coarse search method (global search) based on a color histogram approach, and a more refined search method (local search) based on Scale-Invariant Feature Transform (SIFT) feature matching. If the local search correctly locates the desired object, its 6-DOF pose is estimated using stereo applied to each SIFT feature (i.e. 3D SIFT feature), which is then fed as measurements into an Extended Kalman Filter (EKF) for sustained tracking. If the local search fails to locate the desired object in a particular cell, the cell is updated in the probability map and the next peak probability cell is identified and planned to using a separate grid-based costmap populated via obstacle detection from stereo, with planning done using an A* planner. Experimental results obtained from the use of this method on a mobile robot are presented to illustrate and validate the approach, confirming that the search strategy can be carried out with modest computation on a single laptop.
Current Trends in Educational Technology Research

Educational technology research has moved through several stages or “ages”, focusing at the beginning on the content to be learned, then on the format of instructional messages and, finally on the interaction between computers and students. The present paper reviews the research in technology-based learning environments in order to give both a historical perspective on educational technology research and a view of the current state of this discipline. We conclude that: 1) trends in educational technology research were forged by the evolution of learning theories and the technological changes, 2) a clear shift from the design of instruction to the design of learning environments can be noticed; 3) there is a positive effect of educational technology on learning, but the size of the effect varies considerably; 4) learning is much more dependent on the activity of the learner than on the quantity of information and processing opportunities provided by the environment.
Electromyographic analysis of the rotator cuff and deltoid musculature during common shoulder external rotation exercises.

Prospective single-group repeated-measures design.



To quantify electromyographic (EMG) muscle activity of the infraspinatus, teres minor, supraspinatus, posterior deltoid, and middle deltoid during exercises commonly used to strengthen the shoulder external rotators.



Exercises to strengthen the external rotators are commonly prescribed in rehabilitation, but the amount of EMG activity of the infraspinatus, teres minor, supraspinatus, and deltoid during these exercises has not been thoroughly studied to determine which exercises would be most effective to achieve strength gains.



EMG measured using intramuscular electrodes were analyzed in 10 healthy subjects during 7 shoulder exercises: prone horizontal abduction at 100 degrees of abduction and full external rotation (ER), prone ER at 90 degrees of abduction, standing ER at 90 degrees of abduction, standing ER in the scapular plane (45 degrees abduction, 30 degrees horizontal adduction), standing ER at 0 degrees of abduction, standing ER at 0 degrees of abduction with a towel roll, and sidelying ER at 0 degrees of abduction. The peak percentage of maximal voluntary isometric contraction (MVIC) for each muscle was compared among exercises using a 1-way repeated-measures analysis of variance (P<.05).



EMG activity varied significantly among the 7 exercises. Sidelying ER produced the greatest amount of EMG activity for the infraspinatus (62% MVIC) and teres minor (67% MVIC). The greatest amount of activity of the supraspinatus (82% MVIC), middle deltoid (87% MVIC), and posterior deltoid (88% MVIC) was observed during prone horizontal abduction at 100 degrees with full ER.



Results from this study provide initial information to develop rehabilitation programs. It also provides information helpful for the design and conduct of future studies.
Efficient Self-Interpretation in Lambda Calculus

We start by giving a compact representation schema for λ-terms and show how this leads to an exceedingly small and elegant self-interpreter. We then define the notion of a self-reducer, and show how this too can be written as a small λ-term. Both the self-interpreter and the self-reducer are proved correct. We finally give a constructive proof for the second fixed point theorem for the representation schema. All the constructions have been implemented on a computer, and experiments verify their correctness. Timings show that the self-interpreter and self-reducer are quite efficient, being about 35 and 50 times slower than direct execution using a call-byneed reduction strategy.
Dynamic adaptive streaming over HTTP dataset

The delivery of audio-visual content over the Hypertext Transfer Protocol (HTTP) got lot of attention in recent years and with dynamic adaptive streaming over HTTP (DASH) a standard is now available. Many papers cover this topic and present their research results, but unfortunately all of them use their own private dataset which -- in most cases -- is not publicly available. Hence, it is difficult to compare, e.g., adaptation algorithms in an objective way due to the lack of a common dataset which shall be used as basis for such experiments. In this paper, we present our DASH dataset including our DASHEncoder, an open source DASH content generation tool. We also provide basic evaluations of the different segment lengths, the influence of HTTP server settings, and, in this context, we show some of the advantages as well as problems of shorter segment lengths.
Energy disaggregation for real-time building flexibility detection

Energy is a limited resource which has to be managed wisely, taking into account both supply-demand matching and capacity constraints in the distribution grid. One aspect of the smart energy management at the building level is given by the problem of real-time detection of flexible demand available. In this paper we propose the use of energy disaggregation techniques to perform this task. Firstly, we investigate the use of existing classification methods to perform energy disaggregation. A comparison is performed between four classifiers, namely Naive Bayes, k-Nearest Neighbors, Support Vector Machine and AdaBoost. Secondly, we propose the use of Restricted Boltzmann Machine to automatically perform feature extraction. The extracted features are then used as inputs to the four classifiers and consequently shown to improve their accuracy. The efficiency of our approach is demonstrated on a real database consisting of detailed appliance-level measurements with high temporal resolution, which has been used for energy disaggregation in previous studies, namely the REDD. The results show robustness and good generalization capabilities to newly presented buildings with at least 96% accuracy.
ETHEREUM: A SECURE DECENTRALISED GENERALISED TRANSACTION LEDGER

The blockchain paradigm when coupled with cryptographically-secured transactions has demonstrated its utility through a number of projects, with Bitcoin being one of the most notable ones. Each such project can be seen as a simple application on a decentralised, but singleton, compute resource. We can call this paradigm a transactional singleton machine with shared-state. Ethereum implements this paradigm in a generalised manner. Furthermore it provides a plurality of such resources, each with a distinct state and operating code but able to interact through a message-passing framework with others. We discuss its design, implementation issues, the opportunities it provides and the future hurdles we envisage.
Millimeter-wave antennas for radio access and backhaul in 5G heterogeneous mobile networks

Millimeter-wave communications are expected to play a key role in future 5G mobile networks to overcome the dramatic traffic growth expected over the next decade. Such systems will severely challenge antenna technologies used at mobile terminal, access point or backhaul/fronthaul levels. This paper provides an overview of the authors' recent achievements in the design of integrated antennas, antenna arrays and high-directivity quasi-optical antennas for high data-rate 60-GHz communications.
Cannabis improves night vision: a case study of dark adaptometry and scotopic sensitivity in kif smokers of the Rif mountains of northern Morocco.

Previous reports have documented an improvement in night vision among Jamaican fishermen after ingestion of a crude tincture of herbal cannabis, while two members of this group noted that Moroccan fishermen and mountain dwellers observe an analogous improvement after smoking kif, sifted Cannabis sativa mixed with tobacco (Nicotiana rustica). Field-testing of night vision has become possible with a portable device, the LKC Technologies Scotopic Sensitivity Tester-1 (SST-1). This study examines the results of double-blinded graduated THC administration 0-20 mg (as Marinol) versus placebo in one subject on measures of dark adaptometry and scotopic sensitivity. Analogous field studies were performed in Morocco with the SST-1 in three subjects before and after smoking kif. In both test situations, improvements in night vision measures were noted after THC or cannabis. It is believed that this effect is dose-dependent and cannabinoid-mediated at the retinal level. Further testing may assess possible clinical application of these results in retinitis pigmentosa or other conditions.
Author ' s personal copy Narcissism and recollections of early life experiences

Recent studies have found associations between narcissistic personality features and retrospective accounts of early experiences. The current study sought to extend these previous findings by examining whether adaptive and maladaptive features of narcissism were associated with recollections of early life experiences in a non-clinical sample of undergraduate students (N = 334). Results revealed that the Entitlement/Exploitativeness feature of narcissism was associated with low security, high parental discipline, and high threats of separation. Narcissistic Grandiosity was positively associated with peer affectional support and parental discipline, whereas Narcissistic Vulnerability was not uniquely associated with memories of early life experiences. The results provide partial support for models of narcissism in which parents are recalled as failing to provide a secure base while inducing threats of separation and discipline.
An Experimentally Verified Active Gate Control Method for the Series Connection of IGBT/Diodes

The series connection of insulated gate bipolar transistor (IGBT)/diode devices allows the operation at voltage levels higher than the rated voltage of one IGBT/diode. However, due to individual parameter differences of the series-connected IGBT/diodes, it is difficult to ensure a proper voltage balance between them, and transient or steady-state voltage unbalances could cause the failure of these devices. This paper presents an active gate driver developed by the authors that is suitable for the series connection of IGBTs. The proposed active gate driver achieves the transient and steady-state voltage balance between the series-connected IGBT/diode devices. The effectiveness of the gate driver and the active gate control method has been experimentally validated, and promising results have been obtained.
Explicit Solution for Constrained Stochastic Linear-Quadratic Control with Multiplicative Noise

We study in this paper a class of constrained linear-quadratic (LQ) optimal control problem formulations for the scalar-state stochastic system with multiplicative noise, which has various applications, especially in the financial risk management. The linear constraint on both the control and state variables considered in our model destroys the elegant structure of the conventional LQ formulation and has blocked the derivation of an explicit control policy so far in the literature. We successfully derive in this paper the analytical control policy for such a class of problems by utilizing the state separation property induced from its structure. We reveal that the optimal control policy is a piece-wise affine function of the state and can be computed off-line efficiently by solving two coupled Riccati equations. Under some mild conditions, we also obtain the stationary control policy for infinite time horizon. We demonstrate the implementation of our method via some illustrative examples and show how to calibrate our model to solve dynamic constrained portfolio optimization problems.
ReDeBug: Finding Unpatched Code Clones in Entire OS Distributions

Programmers should never fix the same bug twice. Unfortunately this often happens when patches to buggy code are not propagated to all code clones. Unpatched code clones represent latent bugs, and for security-critical problems, latent vulnerabilities, thus are important to detect quickly. In this paper we present ReDeBug, a system for quickly finding unpatched code clones in OS-distribution scale code bases. While there has been previous work on code clone detection, ReDeBug represents a unique design point that uses a quick, syntax-based approach that scales to OS distribution-sized code bases that include code written in many different languages. Compared to previous approaches, ReDeBug may find fewer code clones, but gains scale, speed, reduces the false detection rate, and is language agnostic. We evaluated ReDeBug by checking all code from all packages in the Debian Lenny/Squeeze, Ubuntu Maverick/Oneiric, all Source Forge C and C++ projects, and the Linux kernel for unpatched code clones. ReDeBug processed over 2.1 billion lines of code at 700,000 LoC/min to build a source code database, then found 15,546 unpatched copies of known vulnerable code in currently deployed code by checking 376 Debian/Ubuntu security-related patches in 8 minutes on a commodity desktop machine. We show the real world impact of ReDeBug by confirming 145 real bugs in the latest version of Debian Squeeze packages.