nils-herrmann/clean_scirepeval huggingface dataset:
Overview of the 2017 WHO Classification of Pituitary Tumors.

This review focuses on discussing the main changes on the upcoming fourth edition of the WHO Classification of Tumors of the Pituitary Gland emphasizing histopathological and molecular genetics aspects of pituitary neuroendocrine (i.e., pituitary adenomas) and some of the non-neuroendocrine tumors involving the pituitary gland. Instead of a formal review, we introduced the highlights of the new WHO classification by answering select questions relevant to practising pathologists. The revised classification of pituitary adenomas, in addition to hormone immunohistochemistry, recognizes the role of other immunohistochemical markers including but not limited to pituitary transcription factors. Recognizing this novel approach, the fourth edition of the WHO classification has abandoned the concept of "a hormone-producing pituitary adenoma" and adopted a pituitary adenohypophyseal cell lineage designation of the adenomas with subsequent categorization of histological variants according to hormone content and specific histological and immunohistochemical features. This new classification does not require a routine ultrastructural examination of these tumors. The new definition of the Null cell adenoma requires the demonstration of immunonegativity for pituitary transcription factors and adenohypophyseal hormones Moreover, the term of atypical pituitary adenoma is no longer recommended. In addition to the accurate tumor subtyping, assessment of the tumor proliferative potential by mitotic count and Ki-67 index, and other clinical parameters such as tumor invasion, is strongly recommended in individual cases for consideration of clinically aggressive adenomas. This classification also recognizes some subtypes of pituitary neuroendocrine tumors as "high-risk pituitary adenomas" due to the clinical aggressive behavior; these include the sparsely granulated somatotroph adenoma, the lactotroph adenoma in men, the Crooke's cell adenoma, the silent corticotroph adenoma, and the newly introduced plurihormonal Pit-1-positive adenoma (previously known as silent subtype III pituitary adenoma). An additional novel aspect of the new WHO classification was also the definition of the spectrum of thyroid transcription factor-1 expressing pituitary tumors of the posterior lobe as representing a morphological spectrum of a single nosological entity. These tumors include the pituicytoma, the spindle cell oncocytoma, the granular cell tumor of the neurohypophysis, and the sellar ependymoma.
Mobile Applications for Control and Self Management of Diabetes: A Systematic Review

Mobile applications (apps) can be very useful software on smartphones for all aspects of people’s lives. Chronic diseases, such as diabetes, can be made manageable with the support of mobile apps. Applications on smartphones can also help people with diabetes to control their fitness and health. A systematic review of free apps in the English language for smartphones in three of the most popular mobile app stores: Google Play (Android), App Store (iOS) and Windows Phone Store, was performed from November to December 2015. The review of freely available mobile apps for self-management of diabetes was conducted based on the criteria for promoting diabetes self-management as defined by Goyal and Cafazzo (monitoring blood glucose level and medication, nutrition, physical exercise and body weight). The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) was followed. Three independent experts in the field of healthcare-related mobile apps were included in the assessment for eligibility and testing phase. We tested and evaluated 65 apps (21 from Google Play Store, 31 from App Store and 13 from Windows Phone Store). Fifty-six of these apps did not meet even minimal requirements or did not work properly. While a wide selection of mobile applications is available for self-management of diabetes, current results show that there are only nine (5 from Google Play Store, 3 from App Store and 1 from Windows Phone Store) out of 65 reviewed mobile apps that can be versatile and useful for successful self-management of diabetes based on selection criteria. The levels of inclusion of features based on selection criteria in selected mobile apps can be very different. The results of the study can be used as a basis to prvide app developers with certain recommendations. There is a need for mobile apps for self-management of diabetes with more features in order to increase the number of long-term users and thus influence better self-management of the disease.
A Programming Language and System for Heterogeneous Cloud of Things

Cloud of Things (CoT) is a computing model that combines the widely popular cloud computing with Internet of Things (IoT). One of the major problems with CoT is the latency of accessing distant cloud resources from the devices, where the data is captured. To address this problem, paradigms such as fog computing and Cloudlets have been proposed to interpose another layer of computing between the clouds and devices. Such a three-layered cloud-fog-device computing architecture is touted as the most suitable approach for deploying many next generation ubiquitous computing applications. Programming applications to run on such a platform is quite challenging because disconnections between the different layers are bound to happen in a large-scale CoT system, where the devices can be mobile. This paper presents a programming language and system for a three-layered CoT system. We illustrate how our language and system addresses some of the key challenges in the three-layered CoT. A proof-of-concept prototype compiler and runtime have been implemented and several example applications are developed using it.
Structural Health Monitoring Using Wireless Sensor Networks: A Comprehensive Survey

Structural health monitoring (SHM) using wireless sensor networks (WSNs) has gained research interest due to its ability to reduce the costs associated with the installation and maintenance of SHM systems. SHM systems have been used to monitor critical infrastructure such as bridges, high-rise buildings, and stadiums and has the potential to improve structure lifespan and improve public safety. The high data collection rate of WSNs for SHM pose unique network design challenges. This paper presents a comprehensive survey of SHM using WSNs outlining the algorithms used in damage detection and localization, outlining network design challenges, and future research directions. Solutions to network design problems such as scalability, time synchronization, sensor placement, and data processing are compared and discussed. This survey also provides an overview of testbeds and real-world deployments of WSNs for SH.
PyDraw: a GUI drawing generator based on Tkinter and its design concept

The emergence of GUI is a great progress in the history of computer science and software design. GUI makes human computer interaction more simple and interesting. Python, as a popular programming language in recent years, has not been realized in GUI design. Tkinter has the advantage of native support for Python, but there are too few visual GUI generators supporting Tkinter. This article presents a GUI generator based on Tkinter framework, PyDraw. The design principle of PyDraw and the powerful design concept behind it are introduced in detail. With PyDraw's GUI design philosophy, it can easily design a visual GUI rendering generator for any GUI framework with canvas functionality or programming language with screen display control. This article is committed to conveying PyDraw's GUI free design concept. Through experiments, we have proved the practicability and efficiency of PyDrawd. In order to better convey the design concept of PyDraw, let more enthusiasts join PyDraw update and evolution, we have the source code of PyDraw. At the end of the article, we summarize our experience and express our vision for future GUI design. We believe that the future GUI will play an important role in graphical software programming, the future of less code or even no code programming software design methods must become a focus and hot, free, like drawing GUI will be worth pursuing.
Biological Control of Mosquito Vectors: Past, Present, and Future

Mosquitoes represent the major arthropod vectors of human disease worldwide transmitting malaria, lymphatic ﬁlariasis, and arboviruses such as dengue virus and Zika virus. Unfortunately, no treatment (in the form of vaccines or drugs) is available for most of these diseases andvectorcontrolisstillthemainformofprevention. Thelimitationsoftraditionalinsecticide-based strategies, particularly the development of insecticide resistance, have resulted in signiﬁcant efforts to develop alternative eco-friendly methods. Biocontrol strategies aim to be sustainable and target a range of different mosquito species to reduce the current reliance on insecticide-based mosquito control. In thisreview, weoutline non-insecticide basedstrategiesthat havebeenimplemented orare currently being tested. We also highlight the use of mosquito behavioural knowledge that can be exploited for control strategies.
Dynamic Data Flow Testing of Object Oriented Systems

Data flow testing has recently attracted new interest in the context of testing object oriented systems, since data flow information is well suited to capture relations among the object states, and can thus provide useful information for testing method interactions. Unfortunately, classic data flow testing, which is based on static analysis of the source code, fails to identify many important data flow relations due to the dynamic nature of object oriented systems. In this paper, we propose a new technique to generate test cases for object oriented software. The technique exploits useful inter-procedural data flow information extracted dynamically from execution traces for object oriented systems. The technique is designed to enhance an initial test suite with test cases that exercise complex state based method interactions. The experimental results indicate that dynamic data flow testing can indeed generate test cases that exercise relevant behaviors otherwise missed by both the original test suite and by test suites that satisfy classic data flow criteria.
The treasure beneath convolutional layers: Cross-convolutional-layer pooling for image classification

A number of recent studies have shown that a Deep Convolutional Neural Network (DCNN) pretrained on a large dataset can be adopted as a universal image descriptor, and that doing so leads to impressive performance at a range of image classification tasks. Most of these studies, if not all, adopt activations of the fully-connected layer of a DCNN as the image or region representation and it is believed that convolutional layer activations are less discriminative. This paper, however, advocates that if used appropriately, convolutional layer activations constitute a powerful image representation. This is achieved by adopting a new technique proposed in this paper called cross-convolutional-layer pooling. More specifically, it extracts subarrays of feature maps of one convolutional layer as local features, and pools the extracted features with the guidance of the feature maps of the successive convolutional layer. Compared with existing methods that apply DCNNs in the similar local feature setting, the proposed method avoids the input image style mismatching issue which is usually encountered when applying fully connected layer activations to describe local regions. Also, the proposed method is easier to implement since it is codebook free and does not have any tuning parameters. By applying our method to four popular visual classification tasks, it is demonstrated that the proposed method can achieve comparable or in some cases significantly better performance than existing fully-connected layer based image representations.
Assembly of flexible CoMoO4@NiMoO4·xH2O and Fe2O3 electrodes for solid-state asymmetric supercapacitors

In this work, CoMoO4@NiMoO4·xH2O core-shell heterostructure electrode is directly grown on carbon fabric (CF) via a feasible hydrothermal procedure with CoMoO4 nanowires (NWs) as the core and NiMoO4 nanosheets (NSs) as the shell. This core-shell heterostructure could provide fast ion and electron transfer, a large number of active sites, and good strain accommodation. As a result, the CoMoO4@NiMoO4·xH2O electrode yields high-capacitance performance with a high specific capacitance of 1582 F g-1, good cycling stability with the capacitance retention of 97.1% after 3000 cycles and good rate capability. The electrode also shows excellent mechanical flexibility. Also, a flexible Fe2O3 nanorods/CF electrode with enhanced electrochemical performance was prepared. A solid-state asymmetric supercapacitor device is successfully fabricated by using flexible CoMoO4@NiMoO4·xH2O as the positive electrode and Fe2O3 as the negative electrode. The asymmetric supercapacitor with a maximum voltage of 1.6 V demonstrates high specific energy (41.8 Wh kg-1 at 700 W kg-1), high power density (12000 W kg-1 at 26.7 Wh kg-1), and excellent cycle ability with the capacitance retention of 89.3% after 5000 cycles (at the current density of 3A g-1).
Seasonal dynamics of phloem and xylem formation in silver fir and Norway spruce as affected by drought

The dynamics of phloem growth ring formation in silver fir (Abies alba Mill.) and Norway spruce (Picea abies Karst.) at different sites in Slovenia during the droughty growing season of 2003 was studied. We also determined the timing of cambial activity, xylem and phloem formation, and counted the number of cells in the completed phloem and xylem growth rings. Light microscopy of cross-sections revealed that cambial activity started on the phloem and xylem side simultaneously at all three plots. However, prior to this, 1–2 layers of phloem derivatives near the cambium were differentiated without previous divisions. The structure of the early phloem was similar in silver fir and Norway spruce. Differences in the number of late phloem cells were found among sites. Phloem growth rings were the widest in Norway spruce growing at the lowland site. In all investigated trees, the cambium produced 5–12 times more xylem cells than phloem ones. In addition, the variability in the number of cells in the 2003 growth ring around the stem circumference of the same tree and among different trees was higher on the xylem side than on the phloem side. Phloem formation is presumably less dependent on environmental factors but is more internally driven than xylem formation.
Cutaneous metastases from internal malignancies: a clinicopathologic and immunohistochemical review.

Skin metastases occur in 0.6%-10.4% of all patients with cancer and represent 2% of all skin tumors. Skin metastases from visceral malignancies are important for dermatologists and dermatopathologists because of their variable clinical appearance and presentation, frequent delay and failure in their diagnosis, relative proportion of different internal malignancies metastasizing to the skin, and impact on morbidity, prognosis, and treatment. Another factor to take into account is that cutaneous metastasis may be the first sign of clinically silent visceral cancer. The relative frequencies of metastatic skin disease tend to correlate with the frequency of the different types of primary cancer in each sex. Thus, women with skin metastases have the following distribution in decreasing order of frequency of primary malignancies: breast, ovary, oral cavity, lung, and large intestine. In men, the distribution is as follows: lung, large intestine, oral cavity, kidney, breast, esophagus, pancreas, stomach, and liver. A wide morphologic spectrum of clinical appearances has been described in cutaneous metastases. This variable clinical morphology included nodules, papules, plaques, tumors, and ulcers. From a histopathologic point of view, there are 4 main morphologic patterns of cutaneous metastases involving the dermis, namely, nodular, infiltrative, diffuse, and intravascular. Generally, cutaneous metastases herald a poor prognosis. The average survival time of patients with skin metastases is a few months. In this article, we review the clinicopathologic and immunohistochemical characteristics of cutaneous metastases from internal malignancies, classify the most common cutaneous metastases, and identify studies that may assist in diagnosing the origin of a cutaneous metastasis.
Cyber Perfidy

Perfidy is the impersonation of civilians during armed conflict. It is generally outlawed by the laws of war such as the Geneva Conventions as its practice makes wars more dangerous for civilians. Cyber perfidy can be defined as malicious software or hardware masquerading as ordinary civilian software or hardware. We argue that it is also banned by the laws of war in cases where such cyber infrastructure is essential to normal civilian activity. This includes tampering with critical parts of operating systems and security software. We discuss possible targets of cyber perfidy, possible objections to the notion, and possible steps towards international agreements about it. This paper appeared in the Routledge Handbook of War and Ethics as chapter 29, ed. N. Evans, 2013.
Application of metabolomics to plant genotype discrimination using statistics and machine learning

Metabolomics is a post genomic technology which seeks to provide a comprehensive profile of all the metabolites present in a biological sample. This complements the mRNA profiles provided by microarrays, and the protein profiles provided by proteomics. To test the power of metabolome analysis we selected the problem of discrimating between related genotypes of Arabidopsis. Specifically, the problem tackled was to discrimate between two background genotypes (Col0 and C24) and, more significantly, the offspring produced by the crossbreeding of these two lines, the progeny (whose genotypes would differ only in their maternally inherited mitichondia and chloroplasts).



A gas chromotography--mass spectrometry (GCMS) profiling protocol was used to identify 433 metabolites in the samples. The metabolomic profiles were compared using descriptive statistics which indicated that key primary metabolites vary more than other metabolites. We then applied neural networks to discriminate between the genotypes. This showed clearly that the two background lines can be discrimated between each other and their progeny, and indicated that the two progeny lines can also be discriminated. We applied Euclidean hierarchical and Principal Component Analysis (PCA) to help understand the basis of genotype discrimination. PCA indicated that malic acid and citrate are the two most important metabolites for discriminating between the background lines, and glucose and fructose are two most important metabolites for discriminating between the crosses. These results are consistant with genotype differences in mitochondia and chloroplasts.
PiDrone: An Autonomous Educational Drone Using Raspberry Pi and Python

A compelling robotics course begins with a compelling robot. We introduce a new low-cost aerial educational platform, the PiDrone, along with an associated college-level introductory robotics course. In a series of projects, students incrementally build, program, and test their own drones to create an autonomous aircraft capable of using a downward facing RGB camera and infrared distance sensor to visually localize and maintain position. The PiDrone runs Python and the Robotics Operating System (ROS) framework on an onboard Raspberry Pi, providing an accessible and inexpensive platform for introducing students to robotics. Students can use any web and SSH capable computer as a base station and programming platform. The projects and supplementary homeworks introduce PID control, state estimation, and high-level planning, giving students the opportunity to exercise their new skills in an exciting long-term project.
HybriDroid: Static analysis framework for Android hybrid applications

Mobile applications (apps) have long invaded the realm of desktop apps, and hybrid apps become a promising solution for supporting multiple mobile platforms. Providing both platform-specific functionalities via native code like native apps and user interactions via JavaScript code like web apps, hybrid apps help developers build multiple apps for different platforms without much duplicated efforts. However, most hybrid apps are developed in multiple programming languages with different semantics, which may be vulnerable to programmer errors. Moreover, because untrusted JavaScript code may access device-specific features via native code, hybrid apps may be vulnerable to various security attacks. Unfortunately, no existing tools can help hybrid app developers by detecting errors or security holes. In this paper, we present HybriDroid, the first static analysis framework for Android hybrid apps. We investigate the semantics of Android hybrid apps especially for the interoperation mechanism of Android Java and JavaScript. Then, we design and implement a static analysis framework that analyzes inter-communication between Android Java and JavaScript. As example analyses supported by HybriDroid, we implement a bug detector that identifies programmer errors due to the hybrid semantics, and a taint analyzer that finds information leaks cross language boundaries. Our empirical evaluation shows that the tools are practically usable in that they found previously uncovered bugs in real-world Android hybrid apps and possible information leaks via a widely-used advertising platform.
Exam performance and attitudes toward multitasking in six, multimedia-multitasking classroom environments

Although many colleges and universities have implemented laptop programs, the use of these technologies in the classroom doesn't guarantee increases in exam performance. Used improperly, these technologies can hinder the learning process. An experiment was conducted comparing how the use or non-use of technology affected exam performance between six different classroom environments. Consistent with predictions based on theories of multitasking and multimedia processing, participants performed worst on an exam when distracted with social media. Moreover, having had this experience, participants in five of the six conditions showed a decrease in perceptions of their abilities to efficiently multitask from pre-test to post-test. Results are discussed in terms of theory and recommendations are made for the integration of experiential learning sessions into orientation programs to help promote a healthy classroom learning environment.
Honeycyber: Automated signature generation for zero-day polymorphic worms

Signature-based intrusion detection systems (IDSs) can be evaded by polymorphic worms which vary their payloads in every infection attempt. In this paper, we propose Honeycyber, a system for automated signature generation for zero-day polymorphic worms. We have designed a novel double-Honeynet system, which is able to automatically detect new worms and isolate the attack traffic from innocuous traffic. We introduce unlimited Honeynet outbound connections, which allow us to capture different payloads in every infection of the same worm. The system is able to generate signatures to match most polymorphic worm instances with low false positives and low false negatives.