nils-herrmann/clean_scirepeval huggingface dataset:
Bandgap engineering of strained monolayer and bilayer MoS2.

We report the influence of uniaxial tensile mechanical strain in the range 0-2.2% on the phonon spectra and bandstructures of monolayer and bilayer molybdenum disulfide (MoS2) two-dimensional crystals. First, we employ Raman spectroscopy to observe phonon softening with increased strain, breaking the degeneracy in the E' Raman mode of MoS2, and extract a Grüneisen parameter of ~1.06. Second, using photoluminescence spectroscopy we measure a decrease in the optical band gap of MoS2 that is approximately linear with strain, ~45 meV/% strain for monolayer MoS2 and ~120 meV/% strain for bilayer MoS2. Third, we observe a pronounced strain-induced decrease in the photoluminescence intensity of monolayer MoS2 that is indicative of the direct-to-indirect transition of the character of the optical band gap of this material at applied strain of ~1%. These observations constitute a demonstration of strain engineering the band structure in the emergent class of two-dimensional crystals, transition-metal dichalcogenides.
Low-cost and Device-free Activity Recognition System with Energy Harvesting PIR and Door Sensors

Progress of IoT and ubiquitous computing technologies has strong anticipation to realize smart services in households such as efficient energy-saving appliance control and elderly monitoring. In order to put those applications into practice, high-accuracy and low-cost in-home living activity recognition is essential. Many researches have tackled living activity recognition so far, but the following problems remain: (i)privacy exposure due to utilization of cameras and microphones; (ii) high deployment and maintenance costs due to many sensors used; (iii) burden to force the user to carry the device and (iv) wire installation to supply power and communication between sensor node and server; (v) few recognizable activities; (vi) low recognition accuracy. In this paper, we propose an in-home living activity recognition method to solve all the problems. To solve the problems (i)--(iv), our method utilizes only energy harvesting PIR and door sensors with a home server for data collection and processing. The energy harvesting sensor has a solar cell to drive the sensor and wireless communication modules. To solve the problems (v) and (vi), we have tackled the following challenges: (a) determining appropriate features for training samples; and (b) determining the best machine learning algorithm to achieve high recognition accuracy; (c) complementing the dead zone of PIR sensor semipermanently. We have conducted experiments with the sensor by five subjects living in a home for 2-3 days each. As a result, the proposed method has achieved F-measure: 62.8% on average.
Fractal feature analysis and classification in medical imaging.

Following B.B. Mandelbrot's fractal theory (1982), it was found that the fractal dimension could be obtained in medical images by the concept of fractional Brownian motion. An estimation concept for determination of the fractal dimension based upon the concept of fractional Brownian motion is discussed. Two applications are found: (1) classification; (2) edge enhancement and detection. For the purpose of classification, a normalized fractional Brownian motion feature vector is defined from this estimation concept. It represented the normalized average absolute intensity difference of pixel pairs on a surface of different scales. The feature vector uses relatively few data items to represent the statistical characteristics of the medial image surface and is invariant to linear intensity transformation. For edge enhancement and detection application, a transformed image is obtained by calculating the fractal dimension of each pixel over the whole medical image. The fractal dimension value of each pixel is obtained by calculating the fractal dimension of 7x7 pixel block centered on this pixel.
Feature Mining through Distance Minimization Learning

The problem of joint feature selection across a group of related tasks has applications in many areas including biomedical informatics and computer vision. We consider the 2,1-norm regularized regression model for joint feature selection from multiple tasks, which can be derived in the probabilistic framework by assuming a suitable prior from the exponential family. One appealing feature of the 2,1-norm regularization is that it encourages multiple predictors to share similar sparsity patterns. However, the resulting optimization problem is challenging to solve due to the non-smoothness of the 2,1-norm regularization. In this paper, we propose to accelerate the computation by reformulating it as two equivalent smooth convex optimization problems which are then solved via the Nesterov’s method—an optimal first-order black-box method for smooth convex optimization. A key building block in solving the reformulations is the Euclidean projection. We show that the Euclidean projection for the first reformulation can be analytically computed, while the Euclidean projection for the second one can be computed in linear time. Empirical evaluations on several data sets verify the efficiency of the proposed algorithms.
Beyond 5G With UAVs: Foundations of a 3D Wireless Cellular Network

In this paper, a novel concept of three-dimensional (3D) cellular networks, that integrate drone base stations (drone-BS) and cellular-connected drone users (drone-UEs), is introduced. For this new 3D cellular architecture, a novel framework for network planning for drone-BSs and latency-minimal cell association for drone-UEs is proposed. For network planning, a tractable method for drone-BSs’ deployment based on the notion of truncated octahedron shapes is proposed, which ensures full coverage for a given space with a minimum number of drone-BSs. In addition, to characterize frequency planning in such 3D wireless networks, an analytical expression for the feasible integer frequency reuse factors is derived. Subsequently, an optimal 3D cell association scheme is developed for which the drone-UEs’ latency, considering transmission, computation, and backhaul delays, is minimized. To this end, first, the spatial distribution of the drone-UEs is estimated using a kernel density estimation method, and the parameters of the estimator are obtained using a cross-validation method. Then, according to the spatial distribution of drone-UEs and the locations of drone-BSs, the latency-minimal 3D cell association for drone-UEs is derived by exploiting tools from an optimal transport theory. The simulation results show that the proposed approach reduces the latency of drone-UEs compared with the classical cell association approach that uses a signal-to-interference-plus-noise ratio (SINR) criterion. In particular, the proposed approach yields a reduction of up to 46% in the average latency compared with the SINR-based association. The results also show that the proposed latency-optimal cell association improves the spectral efficiency of a 3D wireless cellular network of drones.
Growth mindset development pattern

In this paper we present a pattern for growth mindset development. We believe that students can be taught to positively change their mindset, where experience, training, and personal effort can add to a unique student's genetic endowment. We use our long years' experience and synthesized facilitation methods and techniques to assess insight mentoring and to improve it through growth mindset development. These can help students make creative changes in their life and see the world with new eyes in a new way. The pattern allows developing a growth mindset and improving our lives and the lives of those around us.
How I Do It Adjunctive Tenotomy During Middle Ear Surgery

We describe indications and surgical technique for dividing the stapedius and tensor tympani tendons during middle ear surgery. Middle ear muscle reflexes involve contraction of the tensor tympani muscle (TTM) and stapedius muscle (SM) to increase impedance of the middle ear, and may shield the inner ear from loud, continuous nonimpact noise. Sectioning SM and TTM tendons has been advocated for a number of conditions, including improving access to anterior epitympanic (supratubal) recess, releasing a medialized malleus during tympanoplasty and ossiculoplasty, tensor or stapedial myoclonus, reflexive vertigo, and Meniere disease.
The health benefits of wine.

Epidemiologic studies from numerous disparate populations reveal that individuals with the habit of daily moderate wine consumption enjoy significant reductions in all-cause and particularly cardiovascular mortality when compared with individuals who abstain or who drink alcohol to excess. Researchers are working to explain this observation in molecular and nutritional terms. Moderate ethanol intake from any type of beverage improves lipoprotein metabolism and lowers cardiovascular mortality risk. The question now is whether wine, particularly red wine with its abundant content of phenolic acids and polyphenols, confers additional health benefits. Discovering the nutritional properties of wine is a challenging task, which requires that the biological actions and bioavailability of the >200 individual phenolic compounds be documented and interpreted within the societal factors that stratify wine consumption and the myriad effects of alcohol alone. Further challenge arises because the health benefits of wine address the prevention of slowly developing diseases for which validated biomarkers are rare. Thus, although the benefits of the polyphenols from fruits and vegetables are increasingly accepted, consensus on wine is developing more slowly. Scientific research has demonstrated that the molecules present in grapes and in wine alter cellular metabolism and signaling, which is consistent mechanistically with reducing arterial disease. Future research must address specific mechanisms both of alcohol and of polyphenolic action and develop biomarkers of their role in disease prevention in individuals.
Unusual self-electrocution simulating judicial electrocution by an adolescent.

Electrocution is one of the rarest modes of suicide. In this case, one school going adolescent committed suicide by electrocution using bare electric wire. This is a rare case of suicidal death by applying live wires around the wrists, simulating the act of judicial electrocution. He positioned himself on armed chair and placed the nude wire loops from a cable around both wrists and switched on the current by plugging in to nearest socket by foot. There were linear electric contact wounds completely encircling around the both wrists. In addition to these linear electric burns all around wrists, there were electrical burns over both hands. This death highlights the need of supervision and close watch on children for self-destructing activities and behavior. This case also highlights unusual method adopted by adolescent to end his life.
Designing of android head system by applying facial muscle mechanism of humans

The facial system plays an important role in human-robot interaction. EveR-4 H33 is a head system for an android face controlled by thirty-three motors. It consists of three layers: a mechanical layer, an inner cover layer and an outer cover layer. Motors are attached under the skin and some motors are correlated with each other. Some expressions cannot be shown by moving just one motor. In addition, moving just one motor can cause damage to other motors or the skin. To solve these problems, a facial muscle control method that controls motors in a correlated manner is required. We designed a facial muscle control method and applied it to EveR-4 H33. We develop the actress robot EveR-4A by applying the EveR-4 H33 to the 24 degrees of freedom upper body and mannequin legs. EveR-4A shows various facial expressions with lip synchronization using our facial muscle control method.
Production objectives and trait preferences of village poultry producers of Ethiopia: implications for designing breeding schemes utilizing indigenous chicken genetic resources

To generate information essential for the implementation of breeding schemes suitable for village poultry producers in Ethiopia, a survey was conducted aimed at defining the socioeconomic characteristics of the production environments in different geographic regions, understanding the important functions of chickens, identifying farmers’ choice of chicken breeds and the underlying factors that determine the choice of genetic stock used. The survey included both questionnaire survey and a participatory group discussion. A total of 225 households (45 households from each of five Woredas) were interviewed. The questionnaire was designed to collect data covering general information on village poultry production such as socio-management characteristics, production objectives, population structure, breed choice and trait preferences, market preferences of specific traits, and farmers’ selection practices. The participatory farmers’ discussions were designed to involve stakeholders in defining the breeding objective “traits” and deriving their relative importance in the production environment based on the different functions of chickens and “traits” identified in the interviews. The results showed that production of eggs for consumption is the principal function of chickens in most regions followed by the use as source of income and meat for home consumption. The production system in all geographic regions studied revealed similar features generally characterized by extensive scavenging management, absence of immunization programs, increased risk of exposure of birds to disease and predators, and reproduction entirely based on uncontrolled natural mating and hatching of eggs using broody hens. Farmers’ ratings of indigenous chickens with respect to modern breeds showed the highest significance of the adaptive traits in general, and the superior merits of indigenous chickens to high yielding exotic breeds in particular. Adaptation to the production environment was the most important attribute of chickens in all the study areas. The high significance attributed to reproduction traits indicates the need for maintaining broody behavior and high level of hatchability while breeding for improved productivity of indigenous chickens for village conditions. The market price of chickens is primarily dictated by weight, but farmers rated growth (males) and number of eggs followed by growth (females) as the production traits they would like the most to be improved. Therefore, the ultimate breeding goal should be to develop a dual-purpose breed based on indigenous chicken genetic resources with any of the comb types other than single for all the regions studied having the most preferred white body plumage for farmers in the Amhara region and red body plumage for those in Oromia, Benshangul-Gumuz, and Southern regions.
Design and measurement of a kind of dual polarized Vivaldi antenna

This paper designed and fabricated a dual polarized ultra wide band (UWB) Vivaldi antenna in order to meet the requirement of the practical work. The discussed working frequency range of the designed antenna is 3.1∼10.6GHz, the designed dual polarized Vivaldi antenna is composed of two single polarized Vivaldi antennas which are orthogonally laid. For each single polarized Vivaldi antenna, a linear tapered microstrip feeding structure is designed to realize the impedance matching. These two feeding microstrip lines are separated to realize independent feeding of each polarized port. The structure and parameters of the dual polarized Vivaldi antenna is designed and simulated. The fabricated dual polarized Vivaldi antenna is measured in the anechoic chamber. The isolation degree is about 20dB and the gain o f each polarization port is larger than 1.37dBi. Some measured patterns and gain curves are given. Yet the performances of two ports are not symmetric and some characteristic parameters are not ideal compared with the simulation results which should be further improved through improving the fabrication level. The design and experimental results in this paper can provide a technical reference for the fabrication of other dual polarized UWB antennas.
Propagation through alginate encapsulation of axillary buds of Cannabis sativa L. — an important medicinal plant

Cannabis sativa L. (Cannabaceae) is an important medicinal plant well known for its pharmacologic and therapeutic potency. Because of allogamous nature of this species, it is difficult to maintain its potency and efficacy if grown from the seeds. Therefore, chemical profile-based screening, selection of high yielding elite clones and their propagation using biotechnological tools is the most suitable way to maintain their genetic lines. In this regard, we report a simple and efficient method for the in vitro propagation of a screened and selected high yielding drug type variety of Cannabis sativa, MX-1 using synthetic seed technology. Axillary buds of Cannabis sativa isolated from aseptic multiple shoot cultures were successfully encapsulated in calcium alginate beads. The best gel complexation was achieved using 5 % sodium alginate with 50 mM CaCl2.2H2O. Regrowth and conversion after encapsulation was evaluated both under in vitro and in vivo conditions on different planting substrates. The addition of antimicrobial substance — Plant Preservative Mixture (PPM) had a positive effect on overall plantlet development. Encapsulated explants exhibited the best regrowth and conversion frequency on Murashige and Skoog medium supplemented with thidiazuron (TDZ 0.5 μM) and PPM (0.075 %) under in vitro conditions. Under in vivo conditions, 100 % conversion of encapsulated explants was obtained on 1:1 potting mix- fertilome with coco natural growth medium, moistened with full strength MS medium without TDZ, supplemented with 3 % sucrose and 0.5 % PPM. Plantlets regenerated from the encapsulated explants were hardened off and successfully transferred to the soil. These plants are selected to be used in mass cultivation for the production of biomass as a starting material for the isolation of THC as a bulk active pharmaceutical.
Travel time prediction for dynamic routing using Ant Based Control

Currently most car drivers use static routing devices based on the shortest distance between start and end position. But the shortest route can differ from the shortest route in time. To compute alternative routes it is necessary to have good prediction models of expected congestions and a fast algorithm to compute the shortest path while being able to react to dynamic changes in the network caused by special incidents. In this paper we present a dynamic routing system based on Ant Based Control (ABC). Starting from historical traffic data, ants are used to compute and predict the travel times along the road segments. They are finding the fastest routes not only looking to the past and present traffic conditions but also trying to anticipate and avoid future congestions.
Quadriceps strengthening with and without blood flow restriction in the treatment of patellofemoral pain: a double-blind randomised trial.

Quadriceps strengthening exercises are part of the treatment of patellofemoral pain (PFP), but the heavy resistance exercises may aggravate knee pain. Blood flow restriction (BFR) training may provide a low-load quadriceps strengthening method to treat PFP.



Seventy-nine participants were randomly allocated to a standardised quadriceps strengthening (standard) or low-load BFR. Both groups performed 8 weeks of leg press and leg extension, the standard group at 70% of 1 repetition maximum (1RM) and the BFR group at 30% of 1RM. Interventions were compared using repeated-measures analysis of variance for Kujala Patellofemoral Score, Visual Analogue Scale for 'worst pain' and 'pain with daily activity', isometric knee extensor torque (Newton metre) and quadriceps muscle thickness (cm). Subgroup analyses were performed on those participants with painful resisted knee extension at 60°.



Sixty-nine participants (87%) completed the study (standard, n=34; BFR, n=35). The BFR group had a 93% greater reduction in pain with activities of daily living (p=0.02) than the standard group. Participants with painful resisted knee extension (n=39) had greater increases in knee extensor torque with BFR than standard (p<0.01). No between-group differences were found for change in Kujala Patellofemoral Score (p=0.31), worst pain (p=0.24), knee extensor torque (p=0.07) or quadriceps thickness (p=0.2). No difference was found between interventions at 6 months.



Compared with standard quadriceps strengthening, low load with BFR produced greater reduction in pain with daily living at 8 weeks in people with PFP. Improvements were similar between groups in worst pain and Kujala score. The subgroup with painful resisted knee extension had larger improvements in quadriceps strength from BFR.
The moderating effect of the business strategic orientation on eCommerce adoption: Evidence from UK family run SMEs

This study investigates eCommerce adoption in family run SMEs (small and medium sized enterprises). Specifically, the objectives of the study are twofold: (a) to examine environmental and organisational determinants of eCommerce adoption in the family business context; (b) to explore the moderating effect of business strategic orientation on the relationships between adoption determinants and adoption decision. A quantitative questionnaire survey was executed. The sampling frame was outlined based on the OneSource database and 88 companies were involved. Results of logistic regression analyses proffer support that ‘external pressure’ and ‘perceived benefits’ are predictors of eCommerce adoption. Moreover, the findings indicate that the strategic orientation of family businesses will function as a moderator in the adoption process.
Hotel reviews sentiment analysis based on word vector clustering

In traditional text sentiment analysis methods, text feature vector has the problem of high dimensionality and high sparseness. In view of this situation, we can cluster the similar words together and use the generated clusters to fit into a new dimension so that the text feature vector dimension will be decreased. By using Word2Vec tool and K-means clustering algorithm, this task can be completed. However, clustering result of K-means clustering algorithm is sensitive to initial number of clusters. Therefore, we propose a text feature vector representation method based on Word2Vec and ISODATA clustering algorithm. This method can solve the problem that word clustering result is sensitive to the initial number of clusters. By using this method, text feature vector can be represented better, moreover, accuracy of text sentiment classification will be improved. The experimental results show that, under different initial number of clusters, the accuracy of our method is about 0.25% higher than that of text feature vector representation based on Word2Vec and K-means clustering method in hotel reviews sentiment analysis, and the AUC value is increased by about 0.31% on average.
A custom microarray platform for analysis of microRNA gene expression

MicroRNAs are short, noncoding RNA transcripts that post-transcriptionally regulate gene expression. Several hundred microRNA genes have been identified in Caenorhabditis elegans, Drosophila, plants and mammals. MicroRNAs have been linked to developmental processes in C. elegans, plants and humans and to cell growth and apoptosis in Drosophila. A major impediment in the study of microRNA function is the lack of quantitative expression profiling methods. To close this technological gap, we have designed dual-channel microarrays that monitor expression levels of 124 mammalian microRNAs. Using these tools, we observed distinct patterns of expression among adult mouse tissues and embryonic stem cells. Expression profiles of staged embryos demonstrate temporal regulation of a large class of microRNAs, including members of the let-7 family. This microarray technology enables comprehensive investigation of microRNA expression, and furthers our understanding of this class of recently discovered noncoding RNAs.