nils-herrmann/clean_scirepeval huggingface dataset:
Comparative study on the mechanical and microstructural characterisation of AA 7075 nano and hybrid nanocomposites produced by stir and squeeze casting

In this research work, a comparative evaluation on the mechanical and microstructural characteristics of aluminium based single and hybrid reinforced nanocomposites was carried out. The manufacture of a single reinforced nanocomposite was conducted with the distribution of 2 wt.% nano alumina particles (avg. particle size 30-50 nm) in the molten aluminium alloy of grade AA 7075; while the hybrid reinforced nanocomposites were produced with of 4 wt.% silicon carbide (avg. particle size 5-10 µm) and 2 wt.%, 4 wt.% nano alumina particles. Three numbers of single reinforced nanocomposites were manufactured through stir casting with reinforcements preheated to different temperatures viz. 400 °C, 500 °C, and 600 °C. The stir cast procedure was extended to fabricate two hybrid reinforced nanocomposites with reinforcements preheated to 500 °C prior to their inclusion. A single reinforced nanocomposite was also developed by squeeze casting with a pressure of 101 MPa. Mechanical and physical properties such as density, hardness, ultimate tensile strength, and impact strength were evaluated on all the developed composites. The microstructural observation was carried out using optical and scanning electron microscopy. On comparison with base alloy, an improvement of 63.7% and 81.1% in brinell hardness was observed for single and hybrid reinforced nanocomposites respectively. About 16% higher ultimate tensile strength was noticed with the squeeze cast single reinforced nanocomposite over the stir cast.
Reinforcement Learning on a Futures Market Simulator

In recent years, market forecasting by machine learning methods has been flourishing. Most existing works use a past market data set, because they assume that each trader’s individual decisions do not affect market prices at all. Meanwhile, there have been attempts to analyze economic phenomena by constructing virtual market simulators, in which human and artificial traders really make trades. Since prices in a market are, in fact, determined by every trader’s decisions, a virtual market is more realistic, and the above assumption does not apply. In this work, we design several reinforcement learners on the futures market simulator U-Mart (Unreal Market as an Artificial Research Testbed) and compare our learners with the previous champions of U-Mart competitions empirically.
Calibration, validation, and sensitivity analysis: What's what

One very simple interpretation of calibration is to adjust a set of parameters associated with a computational science and engineering code so that the model agreement is maximized with respect to a set of experimental data. One very simple interpretation of validation is to quantify our belief in the predictive capability of a computational code through comparison with a set of experimental data. Uncertainty in both the data and the code are important and must be mathematically understood to correctly perform both calibration and validation. Sensitivity analysis, being an important methodology in uncertainty analysis, is thus important to both calibration and validation. In this paper, we intend to clarify the language just used and express some opinions on the associated issues. We will endeavor to identify some technical challenges that must be resolved for successful validation of a predictive modeling capability. One of these challenges is a formal description of a ‘‘model discrepancy’’ term. Another challenge revolves around the general adaptation of abstract learning theory as a formalism that potentially encompasses both calibration and validation in the face of model uncertainty.
La calidad de vida de las mujeres en edad media varía según el estado menopáusico

136 1 Médico ginecólogo. Profesor Titular, Jefe del Departamento de Investigaciones, Facultad de Medicina, Universidad de Cartagena, Colombia. 2 Médico. Estudiante de la Maestría de Epidemiología Clínica. Facultad de Medicina, Universidad de Cartagena, en convenio con la Universidad Nacional de Colombia. 3 Médica ginecóloga. Cali, Colombia. Correspondencia: Álvaro Monterrosa; alvaromonterrosa@gmail.com Edificio City Bank Oficina 6-A. La Matuna, teléfono 57-5-66542211, fax: 57-5-6600084, móvil: 57-3157311275, CartagenaColombia
The biology of CD45 and its use as a therapeutic target.

All mature hemopoietic lineage cells, with exclusion of platelets and mature erythrocytes, share the surface expression of a transmembrane phosphatase, the CD45 molecule. It is also present on hemopoietic stem cells and most leukemic clones and therefore presents as an appropriate target for immunotherapy with anti-CD45 antibodies. This short review details the biology of CD45 and its recent targeting for both treatment of malignant disorders and tolerance induction. In particular, the question of potential stem cell depletion for induction of central tolerance or depletion of malignant hemopoietic cells is addressed. Mechanisms underlying the effects downstream of CD45 binding to the cell surface are discussed.
Towards robust instruction-level trace alignment of binary code

Program trace alignment is the process of establishing a correspondence between dynamic instruction instances in executions of two semantically similar but syntactically different programs. In this paper we present what is, to the best of our knowledge, the first method capable of aligning realistically long execution traces of real programs. To maximize generality, our method works entirely on the machine code level, i.e. it does not require access to source code. Moreover, the method is based entirely on dynamic analysis, which avoids the many challenges associated with static analysis of binary code, and which additionally makes our approach inherently resilient to e.g. static code obfuscation. Therefore, we believe that our trace alignment method could prove to be a useful aid in many program analysis tasks, such as debugging, reverse-engineering, investigating plagiarism, and malware analysis. We empirically evaluate our method on 11 popular Linux programs, and show that it is capable of producing meaningful alignments in the presence of various code transformations such as optimization or obfuscation, and that it easily scales to traces with tens of millions of instructions.
All-electric ships—A review of the present state of the art

Modern navies are exploring ways to power all-electric ships (AES), enabling ships' loads to be powered from the same electrical source as that of the propulsion system, thus avoiding a separate generation system for these loads. AES are envisioned to be equipped with a variety of high power electronic components, pulsed loads like electromagnetic guns and electromagnetic aircraft launchers, machines and cables made of high temperature superconductors that improve efficiency, and highly intelligent controls for adaptability and reconfiguration. This paper presents a review of present state-of-the-art in the field of AES covering all the technological aspects.
Automated big text security classification

In recent years, traditional cybersecurity safeguards have proven ineffective against insider threats. Famous cases of sensitive information leaks caused by insiders, including the WikiLeaks release of diplomatic cables and the Edward Snowden incident, have greatly harmed the U.S. government's relationship with other governments and with its own citizens. Data Leak Prevention (DLP) is a solution for detecting and preventing information leaks from within an organization's network. However, state-of-art DLP detection models are only able to detect very limited types of sensitive information, and research in the field has been hindered due to the lack of available sensitive texts. Many researchers have focused on document-based detection with artificially labeled “confidential documents” for which security labels are assigned to the entire document, when in reality only a portion of the document is sensitive. This type of whole-document based security labeling increases the chances of preventing authorized users from accessing non-sensitive information within sensitive documents. In this paper, we introduce Automated Classification Enabled by Security Similarity (ACESS), a new and innovative detection model that penetrates the complexity of big text security classification/detection. To analyze the ACESS system, we constructed a novel dataset, containing formerly classified paragraphs from diplomatic cables made public by the WikiLeaks organization. To our knowledge this paper is the first to analyze a dataset that contains actual formerly sensitive information annotated at paragraph granularity.
MDL for Causal Inference on Discrete Data

The algorithmic Markov condition states that the most likely causal direction between two random variables X and Y can be identified as the direction with the lowest Kolmogorov complexity. This notion is very powerful as it can detect any causal dependency that can be explained by a physical process. However, due to the halting problem, it is also not computable. In this paper we propose an computable instantiation that provably maintains the key aspects of the ideal. We propose to approximate Kolmogorov complexity via the Minimum Description Length (MDL) principle, using a score that is mini-max optimal with regard to the model class under consideration. This means that even in an adversarial setting, the score degrades gracefully, and we are still maximally able to detect dependencies between the marginal and the conditional distribution. As a proof of concept, we propose CISC, a linear-time algorithm for causal inference by stochastic complexity, for pairs of univariate discrete variables. Experiments show that CISC is highly accurate on synthetic, benchmark, as well as real-world data, outperforming the state of the art by a margin, and scales extremely well with regard to sample and domain sizes.
Removing Shadows from Images of Documents

In this work, we automatically detect and remove distracting shadows from photographs of documents and other text-based items. Documents typically have a constant colored background; based on this observation, we propose a technique to estimate background and text color in local image blocks. We match these local background color estimates to a global reference to generate a shadow map. Correcting the image with this shadow map produces the final unshadowed output. We demonstrate that our algorithm is robust and produces high-quality results, qualitatively and quantitatively, in both controlled and real-world settings containing large regions of significant shadow.
Streaming active learning strategies for real-life credit card fraud detection: assessment and visualization

Credit card fraud detection is a very challenging problem because of the specific nature of transaction data and the labeling process. The transaction data are peculiar because they are obtained in a streaming fashion, and they are strongly imbalanced and prone to non-stationarity. The labeling is the outcome of an active learning process, as every day human investigators contact only a small number of cardholders (associated with the riskiest transactions) and obtain the class (fraud or genuine) of the related transactions. An adequate selection of the set of cardholders is therefore crucial for an efficient fraud detection process. In this paper, we present a number of active learning strategies and we investigate their fraud detection accuracies. We compare different criteria (supervised, semi-supervised and unsupervised) to query unlabeled transactions. Finally, we highlight the existence of an exploitation/exploration trade-off for active learning in the context of fraud detection, which has so far been overlooked in the literature.
A Survey on Security in Named Data Networking

Over the past three decades, since its invention, the Internet has evolved in both its sheer volume and usage. The Internet’s core protocol, Internet Protocol (IP), has proven its usability and effectiveness to support a communication network. However, current Internet usage requires more than a communication network due to a shift in the nature of Internet applications from simple email application to large content producers such as NetFlix, Google, Amazon, etc. Named Data Networking (NDN) is one of the few initiatives/projects addressing the shortcomings of the current Internet architecture and intends to move the Internet toward a content distribution architecture. In this paper, we conduct a brief survey of security topics/problems inherent to the NDN architecture. Specifically, we describe current known problems and propose solutions to major security problems.
An approach for smart parking system based on cloud using IoT

in the most of the modern cities it is difficult and expensive to create more parking spaces for vehicles since the numbers of vehicles are running on the road are increasing day by day and the count of the free spaces in the cities are the same. This problem leads to congestion for parking seekers and drivers. To develop an IoT framework that targets Parking Management which is biggest challenges in modern cities. Using embedded systems, there is a chance to develop an application which can solve these problems. The proposed smart parking solution gives an onsite deployment in which, IoT application monitors and indicate the availability of each parking space. This system helps in improvising the management of parking system by following rules of the government, for example handling different parking spaces in the city. The intuition of presenting this paper is to reduce smart city issue such as the traffic on road and reduces the pollution in the city and the parking.  Cloud; Internet of Things; MQTT; Raspberry pi; Parking
Agarose Gel Electrophoresis for the Separation of DNA Fragments

Agarose gel electrophoresis is the most effective way of separating DNA fragments of varying sizes ranging from 100 bp to 25 kb(1). Agarose is isolated from the seaweed genera Gelidium and Gracilaria, and consists of repeated agarobiose (L- and D-galactose) subunits(2). During gelation, agarose polymers associate non-covalently and form a network of bundles whose pore sizes determine a gel's molecular sieving properties. The use of agarose gel electrophoresis revolutionized the separation of DNA. Prior to the adoption of agarose gels, DNA was primarily separated using sucrose density gradient centrifugation, which only provided an approximation of size. To separate DNA using agarose gel electrophoresis, the DNA is loaded into pre-cast wells in the gel and a current applied. The phosphate backbone of the DNA (and RNA) molecule is negatively charged, therefore when placed in an electric field, DNA fragments will migrate to the positively charged anode. Because DNA has a uniform mass/charge ratio, DNA molecules are separated by size within an agarose gel in a pattern such that the distance traveled is inversely proportional to the log of its molecular weight(3). The leading model for DNA movement through an agarose gel is "biased reptation", whereby the leading edge moves forward and pulls the rest of the molecule along(4). The rate of migration of a DNA molecule through a gel is determined by the following: 1) size of DNA molecule; 2) agarose concentration; 3) DNA conformation(5); 4) voltage applied, 5) presence of ethidium bromide, 6) type of agarose and 7) electrophoresis buffer. After separation, the DNA molecules can be visualized under uv light after staining with an appropriate dye. By following this protocol, students should be able to: Understand the mechanism by which DNA fragments are separated within a gel matrix Understand how conformation of the DNA molecule will determine its mobility through a gel matrix Identify an agarose solution of appropriate concentration for their needs Prepare an agarose gel for electrophoresis of DNA samples Set up the gel electrophoresis apparatus and power supply Select an appropriate voltage for the separation of DNA fragments Understand the mechanism by which ethidium bromide allows for the visualization of DNA bands Determine the sizes of separated DNA fragments.
MULTICOMMUNICATING : A PRACTICE WHOSE TIME HAS COME ?

We offer the concept of multicommunicating to describe overlapping conversations, an increasingly common occurrence in the technology-enriched workplace. We define multicommunicating, distinguish it from other behaviors, and develop propositions for future research. Our work extends the literature on technology-stimulated restructuring and reveals one of the opportunities provided by lean media—specifically, an opportunity to multicommunicate. We conclude that the concept of multicommunicating has value both to the scholar and to the practicing manager.
Reflections of Consciousness: The Mirror Test

Humans and some animals are able to recognize themselves in a mirror. This ability has been taken as a demonstration of self-consciousness. Consequently, it has been proposed that the self-recognition in the mirror image, the mirror test, could also be used to determine the potential self-consciousness of cognitive machines. It is shown that very simple machinery is able to pass the mirror test and consequently it is argued that the passing of the mirror test per se does not demonstrate the existence of self-consciousness. Next, the realization of more complex machinery that passes the mirror test and could be considered to possess self-consciousness is outlined.
Continuous hand-eye calibration using 3D points

The recent development of calibration algorithms has been driven into two major directions: (1) an increasing accuracy of mathematical approaches and (2) an increasing flexibility in usage by reducing the dependency on calibration objects. These two trends, however, seem to be contradictory since the overall accuracy is directly related to the accuracy of the pose estimation of the calibration object and therefore demanding large objects, while an increased flexibility leads to smaller objects or noisier estimation methods. The method presented in this paper aims to resolves this problem in two steps: First, we derive a simple closed-form solution with a shifted focus towards the equation of translation that only solves for the necessary hand-eye transformation. We show that it is superior in accuracy and robustness compared to traditional approaches. Second, we decrease the dependency on the calibration object to a single 3D-point by using a similar formulation based on the equation of translation which is much less affected by the estimation error of the calibration object's orientation. Moreover, it makes the estimation of the orientation obsolete while taking advantage of the higher accuracy and robustness from the first solution, resulting in a versatile method for continuous hand-eye calibration.
Stresssense: skin conductivity monitoring garment with a mobile app

StressSense is smart clothing made of fabric sensors that monitor the stress level of the wearers. The fabric sensors are comfortable, allowing for long periods of monitoring and the electronic components are waterproof and detachable for ease of care. This design project is expected to be beneficial for people who have a lot of stress in their daily life and who care about their mental health. It can be also used for people who need to control their stress level critically, such as analysts, stock managers, athletes, and patients with chronic diseases and disorders.
Synchronous Generator Brushless Field Excitation and Voltage Regulation via Capacitive Coupling Through Journal Bearings

Wound field synchronous generators (WFSG) are the standard electromechanical converter for back-up and utility scale power generation. Maintenance costs may be minimized by adopting noncontact or “brushless” technologies to replace sliding slip ring connections for rotor field excitation. This paper presents a brushless excitation approach using ceramic insulated sleeve (journal) bearings with oil lubrication to form capacitively coupled slip rings, in contrast to more traditional inductive brushless exciters and rotary transformers. This capacitive power transfer (CPT) approach exhibits advantages including low weight, low volume, and has a relatively simple construction using off-the-shelf components. Analysis, design, and prototype construction of the CPT system are presented. Experimental results demonstrate that 1.7 nF of capacitive coupling transfers 340 W to the rotor field winding of a 10 kW 208 V WFSG. Voltage regulation of a WFSG is demonstrated during steady state and 1 per unit load step changes yielding a NEMA-MG1 class G2 rating.
A multimodal biometrie system for personal identification based on deep learning approaches

Multimodal biometrie systems seek to alleviate some of the limitations of unimodal biometrie systems by combining multiple pieces of evidence of the same person in the deeision-making process. In this paper, a novel multimodal biometric identification system is proposed based on fusing the results obtained from both the face and the left and right irises using deep learning approaches. Firstly, the facial features are extracted using a Deep Belief Network (DBN) architecture consisting of 3-layers. The first two RBMs are used as features detectors, while the last one is used as a discriminative model associated with softmax units for the multi-class classification purpose. Secondly, an efficient deep learning system is employed for iris recognition, whose architecture is based on a combination of Convolutional Neural Network (CNN) and Softmax classifier to extract discriminative features from an iris image. Extensive experiments on large-scale challenging databases, including FERET, CASIA V1.0 and MMU1, and SDUMLA-HMT have demonstrated the superiority of the proposed approaches by achieving new state-of-the-art Rank-1 identification rates on all the employed databases.
Neck infections.

Understanding fascial planes and potential spaces within the neck is integral to determining routes of spread and mandatory when surgical intervention is necessary. Imaging is critical in the stable patient to determine the location and severity of infection as well as provide a guide when surgery is indicated. Pharmacologic treatment initially includes empiric broad-spectrum antibiotics against gram-positive, gram-negative, and anaerobic bacteriadlater refined based on culture and sensitivity results. Surgical intervention is reserved for complicated or unstable patients, or those who are unresponsive to medical therapy.
Repair of the Malpositioned Lower Lid.

Facial fractures can lead to long-term sequelae if not repaired. Complications from surgical approaches can be equally detrimental to the patient. Periorbital approaches via the lower lid can lead to ectropion, entropion, scleral show, canthal malposition, and lid edema.1–6 Ectropion can cause epiphora, whereas entropion often causes pain and irritation due to contact between the cilia and cornea. Transcutaneous and tranconjunctival approaches are commonly used to address fractures of the infraorbital rim and orbital floor. The transconjunctival approach is popular among otolaryngologists and ophthalmologists, whereas transcutaneous approaches are more commonly used by oral maxillofacial surgeons and plastic surgeons.7Ridgwayet al reported in theirmeta-analysis that lid complications are highest with the subciliary approach (19.1%) and lowest with transconjunctival approach (2.1%).5 Raschke et al also found a lower incidence of lower lid malpositionvia the transconjunctival approach comparedwith the subciliary  Regardless of approach, complications occur and thefacial traumasurgeonmustknowhowtomanage these issues. In this article, we will review the common complications of lower lid surgery and their treatment.