nils-herrmann/clean_scirepeval huggingface dataset:
Machine-to-Machine Communications in Ultra-Dense Networks—A Survey

To achieve 1000-fold capacity increase in 5G wireless communications, ultradense network (UDN) is believed to be one of the key enabling technologies. Most of the previous research activities on UDNs were based very much on human-to-human communications. However, to provide ubiquitous Internet of Things services, machine-to-machine (M2M) communications will play a critical role in 5G systems. As the number of machine-oriented connections increases, it is expected that supporting M2M communications is an essential requirement in all future UDNs. In this paper, we aim to bridge the gaps between M2M communications and UDNs, which were commonly considered as two separate issues in the literature. The paper begins with a brief introduction on M2M communications and UDNs, and then will discuss the issues on the roles of M2M communications in future UDNs. We will identify different ways to implement M2M communications in the UDNs from the perspectives of layered architecture, including physical, media access control, network, and application layers. Other two important issues, i.e., security and network virtualization, will also be addressed. Before the end of this paper, we will give a summary on identified research topics for future studies.
Photodocumentation in rhinoplasty surgery

High-quality documentary photo series have a special place in rhinoplasty. The exact photographic reproduction of the nasal contours is an essential part of surgical planning, documentation and follow-up of one’s own work. Good photographs can only be achieved using suitable technology and with a good knowledge of photography. Standard operating procedures are also necessary. The photographic equipment should consist of a digital single-lens reflex camera, studio flash equipment and a suitable room for photography with a suitable backdrop. The high standards required cannot be achieved with simple photographic equipment. The most important part of the equipment is the optics. Fixed focal length lenses with a focal length of about 105 mm are especially suited to this type of work. Nowadays, even a surgeon without any photographic training is in a position to produce a complete series of clinical images. With digital technology, any of us can take good photographs. The correct exposure, the right depth of focus for the key areas of the nose and the right camera angle are the decisive factors in a good image series. Up to six standard images are recommended in the literature for the proper documentation of nasal surgery. The most important are frontal, three quarters and profile views. In special cases, close-up images may also be necessary. Preparing a professional image series is labour-intensive and very expensive. Large hospitals no longer employ professional photographers. Despite this, we must strive to maintain a high standard of photodocumenation for publications and to ensure that cases can be compared at congresses.
ASAP: A Transistor Sizing Tool for Speed Area and Power Optimization of Static CMOS Circuits

This paper introduces an automated transistor sizing tool (ASAP) that incorporates accurate gatelevel functio~nal models and can be used for delay, area, and power optimization of CMOS combinational logic circuits in a VLSI design environment. ASAP considers the performailce improvement of VLSI CMOS circuits by optimally sizing the transistors on the first N critical paths. The global picture of the circuit is considered by taking into account the effects that the transi.stor size changes of one path have on the others. The optimization technique in our sizing tool is based on simulated annealing and couples accurate delay modeling with power and area optimization. The combinatorial minimization of the objective function relies on analytical models that can accurately evaluate the delay, the power and the area of a gate. ASAP has been implemented in C on an Apollo 400 workstation with encouraging results.
The adolescent hymen.

The genital examination is not a routine part of health maintenance assessment in prepubertal and pubertal girls. However, evaluation of minors for suspected sexual abuse has been addressed extensively in the last two decades. In spite of this, normal anatomic variations and developmental changes are not fully investigated. This paper reviews current knowledge about the hymen, with a focus on puberty and adolescence. More is known about the external genitals of prepubertal children than of adolescent girls. No longitudinal studies have been performed among girls older than age 3. Tanner staging does not include detailed genital development. A variety of terms have been used to describe the configuration and/or distortion of the hymen: attenuation, clefts, tears and transections, bumps and notches. No studies have been published on the normal variations of the width of the hymenal rim, although an attenuated and/or narrow rim is categorized as consistent with penetrative sexual abuse according to an international consensus statement. Critiques of the literature on the hymen have been published by experts on forensic medicine, emphasizing the fact that the normal hymenal appearance in adolescents still is not well documented. Few studies on hymenal configuration in nonabused adolescent girls have been performed, including girls with and without experience of consensual vaginal intercourse and use of tampons. Longitudinal investigations are required for a better knowledge of female genital development during puberty, with a special focus on vulvar and hymenal anatomy.
A novel stealth Vivaldi antenna

A novel stealth Vivaldi antenna is proposed in this paper that covers the entire X-band from 8 to 12 GHz. Based on the difference of the current distribution on the metal patch when the antenna radiates or scatters, the shape of the patch is modified so that the electromagnetic scattering is significantly decreased in a wide angle range within the entire operating band. Maximally 14dBsm radar cross section (RCS) reduction is achieved with satisfactory radiation performance maintained.
Evaluation of palatal donor site haemostasis and wound healing after free gingival graft surgery.

Evaluating effectiveness of a medicinal plant extract (MPE) in achieving haemostasis and early wound healing at free gingival graft (FGG) donor site in a randomized controlled fashion.



Forty patients requiring FGG at lower anterior area were randomly assigned into two groups. FGG was performed to all patients and following graft procurement; wet gauze (WG) was applied alone (control: WG group) or with MPE (test: MPE + WG group) for haemostasis. Donor site working time, bleeding (BLE), colour match (CM), pain, epithelization (EP) and sensation loss (SL) were evaluated.



Thirty-three participants completed a 6-month period study. In the test group, primary BLE was shorter (p < 0.001) and fewer individuals showed secondary BLE during 3 days (p < 0.001). During the 6 days, pain scores were higher in WG patients (p < 0.05). Later on, no inter-group difference was observed. EP was relatively faster (p < 0.001) and CM was slightly better (p < 0.05) in MPE + WG group.



MPE provided faster and continuous haemostasis that made a positive contribution to the early soft tissue healing to some extent but due to limitations; further trials are needed to demonstrate the efficiency of this material.
Postoperative Multimodal Analgesia Pain Management With Nonopioid Analgesics and Techniques: A Review.

Amid the current opioid epidemic in the United States, the enhanced recovery after surgery pathway (ERAS) has emerged as one of the best strategies to improve the value and quality of surgical care and has been increasingly adopted for a broad range of complex surgical procedures. The goal of this article was to outline important components of opioid-sparing analgesic regimens.



Regional analgesia, acetaminophen, nonsteroidal anti-inflammatory agents, gabapentinoids, tramadol, lidocaine, and/or the N-methyl-d-aspartate class of glutamate receptor antagonists have been shown to be effective adjuncts to narcotic analgesia. Nonsteroidal anti-inflammatory agents are not associated with an increase in postoperative bleeding. A meta-analysis of 27 randomized clinical trials found no difference in postoperative bleeding between the groups taking ketorolac tromethamine (33 of 1304 patients [2.5%]) and the control groups (21 of 1010 [2.1%]) (odds ratio [OR], 1.1; 95% CI, 0.61-2.06; P = .72). After adoption of the multimodal analgesia approach for a colorectal ERAS pathway, most patients used less opioids while in the hospital and many did not need opioids after hospital discharge, although approximately 50% of patients received some opioid during their stay.



Multimodal analgesia is readily available and the evidence is strong to support its efficacy. Surgeons should use this effective approach for patients both using and not using the ERAS pathway to reduce opioid consumption.
Stacked Autoencoders for Outlier Detection in Over-the-Horizon Radar Signals

Detection of outliers in radar signals is a considerable challenge in maritime surveillance applications. High-Frequency Surface-Wave (HFSW) radars have attracted significant interest as potential tools for long-range target identification and outlier detection at over-the-horizon (OTH) distances. However, a number of disadvantages, such as their low spatial resolution and presence of clutter, have a negative impact on their accuracy. In this paper, we explore the applicability of deep learning techniques for detecting deviations from the norm in behavioral patterns of vessels (outliers) as they are tracked from an OTH radar. The proposed methodology exploits the nonlinear mapping capabilities of deep stacked autoencoders in combination with density-based clustering. A comparative experimental evaluation of the approach shows promising results in terms of the proposed methodology's performance.
A Learning-Based Approach to the Detection of SQL Attacks

Web-based systems are often a composition of infrastructure components, such as web servers and databases, and of applicationspecific code, such as HTML-embedded scripts and server-side applications. While the infrastructure components are usually developed by experienced programmers with solid security skills, the application-specific code is often developed under strict time constraints by programmers with little security training. As a result, vulnerable web-applications are deployed and made available to the Internet at large, creating easilyexploitable entry points for the compromise of entire networks. Web-based applications often rely on back-end database servers to manage application-specific persistent state. The data is usually extracted by performing queries that are assembled using input provided by the users of the applications. If user input is not sanitized correctly, it is possible to mount a variety of attacks that leverage web-based applications to compromise the security of back-end databases. Unfortunately, it is not always possible to identify these attacks using signature-based intrusion detection systems, because of the ad hoc nature of many web-based applications. Signatures are rarely written for this class of applications due to the substantial investment of time and expertise this would require. We have developed an anomaly-based system that learns the profiles of the normal database access performed by web-based applications using a number of different models. These models allow for the detection of unknown attacks with reduced false positives and limited overhead. In addition, our solution represents an improvement with respect to previous approaches because it reduces the possibility of executing SQL-based mimicry attacks.
Brain neural synchronization and functional coupling in Alzheimer's disease as revealed by resting state EEG rhythms.

Alzheimer's disease (AD) is the most common type of neurodegenerative disorder, typically causing dementia along aging. AD is mainly characterized by a pathological extracellular accumulation of amyloid-beta peptides that affects excitatory and inhibitory synaptic transmission, inducing aberrant patterns in neuronal circuits. Growing evidence shows that AD targets cortical neuronal networks related to cognitive functions including episodic memory and visuospatial attention. This is partially reflected by the abnormal mechanisms of cortical neural synchronization and coupling that generate resting state electroencephalographic (EEG) rhythms. The cortical neural synchronization is typically indexed by EEG power density. The EEG coupling between electrode pairs probes functional (inter-relatedness of EEG signals) and effective (casual effect from one over the other electrode) connectivity. The former is typically indexed by synchronization likelihood (linear and nonlinear) or spectral coherence (linear), the latter by granger causality or information theory indexes. Here we reviewed literature concerning EEG studies in condition of resting state in AD and mild cognitive impairment (MCI) subjects as a window on abnormalities of the cortical neural synchronization and functional and effective connectivity. Results showed abnormalities of the EEG power density at specific frequency bands (<12Hz) in the MCI and AD populations, associated with an altered functional and effective EEG connectivity among long range cortical networks (i.e. fronto-parietal and fronto-temporal). These results suggest that resting state EEG rhythms reflect the abnormal cortical neural synchronization and coupling in the brain of prodromal and overt AD subjects, possibly reflecting dysfunctional neuroplasticity of the neural transmission in long range cortical networks.
Compliance of blood sampling procedures with the CLSI H3-A6 guidelines: An observational study by the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) working group for the preanalytical phase (WG-PRE).

An observational study was conducted in 12 European countries by the European Federation of Clinical Chemistry and Laboratory Medicine Working Group for the Preanalytical Phase (EFLM WG-PRE) to assess the level of compliance with the CLSI H3-A6 guidelines.



A structured checklist including 29 items was created to assess the compliance of European phlebotomy procedures with the CLSI H3-A6 guideline. A risk occurrence chart of individual phlebotomy steps was created from the observed error frequency and severity of harm of each guideline key issue. The severity of errors occurring during phlebotomy was graded using the risk occurrence chart.



Twelve European countries participated with a median of 33 (18-36) audits per country, and a total of 336 audits. The median error rate for the total phlebotomy procedure was 26.9 % (10.6-43.8), indicating a low overall compliance with the recommended CLSI guideline. Patient identification and test tube labelling were identified as the key guideline issues with the highest combination of probability and potential risk of harm. Administrative staff did not adhere to patient identification procedures during phlebotomy, whereas physicians did not adhere to test tube labelling policy.



The level of compliance of phlebotomy procedures with the CLSI H3-A6 guidelines in 12 European countries was found to be unacceptably low. The most critical steps in need of immediate attention in the investigated countries are patient identification and tube labelling.
A Study on Change Detection Methods

In the real word, the environment is often dynamic instead of stable. Usually the underlying data of a problem changes with time, which enhances the difficulties when learning a model from data. In this paper, different methods capable to detect changes from high-speed time changing data streams are compared. These methods are appropriated to be embedded inside learning models, allowing the adaptation to a non-stationary problem. The experimental evaluation considers different types of concept drift and data streams with different properties. Assessing measures such as: false alarm rates, number of samples until a change is detected and miss detections rates, a comparison between the algorithms’ capability of consistent detection is given. The choice on the best detection algorithm relies on a trade-off between the rate of false alarms and miss detections and the delay time until detection.
Design and Validation of a Reconfigurable Single Varactor-Tuned Reflectarray

An aperture-coupled reflectarray element giving a full phase tuning range with a single varactor diode is proposed in this paper for pattern reconfigurability applications. The full phase agility is achieved by a proper optimization of the phase tuning line, thus providing an alternate inductive/capacitive effect able to avoid the use of two varactor diodes, usually adopted in similar existing configurations. The proposed active element structure is adopted to design a demonstrative reflectarray prototype of 3 × 15 radiators. Furthermore, an own synthesis procedure is applied to obtain the proper biasing voltages giving the prescribed H-plane field. Test examples of beam-scanning, multibeam, and shaped-beam patterns are discussed to demonstrate the effectiveness of the approach.
A Pretrained DenseNet Encoder for Brain Tumor Segmentation

This article presents a convolutional neural network for the automatic segmentation of brain tumors in multimodal 3D MR images based on a U-net architecture. We evaluate the use of a densely connected convolutional network encoder (DenseNet) which was pretrained on the ImageNet data set. We detail two network architectures that can take into account multiple 3D images as inputs. This work aims to identify if a generic pretrained network can be used for very specific medical applications where the target data differ both in the number of spatial dimensions as well as in the number of inputs channels. Moreover in order to regularize this transfer learning task we only train the decoder part of the U-net architecture. We evaluate the effectiveness of the proposed approach on the BRATS 2018 segmentation challenge  where we obtained dice scores of 0.79, 0.90, 0.85 and 95% Hausdorff distance of 2.9mm, 3.95mm, and 6.48mm for enhanced tumor core, whole tumor and tumor core respectively on the validation set. This scores degrades to 0.77, 0.88, 0.78 and 95% Hausdorff distance of 3.6mm, 5.72mm, and 5.83mm on the testing set .
Route Designer: A Retrosynthetic Analysis Tool Utilizing Automated Retrosynthetic Rule Generation

Route Designer, version 1.0, is a new retrosynthetic analysis package that generates complete synthetic routes for target molecules starting from readily available starting materials. Rules describing retrosynthetic transformations are automatically generated from reaction databases, which ensure that the rules can be easily updated to reflect the latest reaction literature. These rules are used to carry out an exhaustive retrosynthetic analysis of the target molecule, in which heuristics are used to mitigate the combinatorial explosion. Proposed routes are prioritized by an empirical rating algorithm to present a diverse profile of the most promising solutions. The program runs on a server with a web-based user interface. An overview of the system is presented together with examples that illustrate Route Designer's utility.
Lower Limb Rehabilitation Robot in Sitting Position for Various Therapeutic Exercises

In this paper, a lower limb rehabilitation robot in sitting position is developed for patients with muscle weakness. The robot is a stationary based type which is able to perform various types of therapeutic exercises. For safe operation, the robot's joint is driven by two-stage cable transmission while the balance mechanism is used to reduce actuator size and transmission ratio. Control algorithms for passive, assistive and resistive exercises are designed to match characteristics of each therapeutic exercises and patients with different muscle strength. Preliminary experiments conducted with a healthy subject have demonstrated that the robot and the control algorithms are promising for lower limb rehabilitation task.
CONTEXT-AWARENESS IN MOBILE CLOUD COMPUTING: HEALTHCARE

Rapid changes in mobile cloud computing tremendously affect the telecommunication, education and healthcare industries and also business perspectives. Nowadays, advanced information and communication technology enhanced healthcare sector to improved medical services at reduced cost. However, issues related to security, privacy, quality of services and mobility and viability need to be solved before mobile cloud computing can be adopted in the healthcare industry. Mobile healthcare (mHealthcare) is one of the latest technologies in the healthcare industry which enable the industry players to collaborate each other’s especially in sharing the patience’s medical reports and histories. MHealthcare offer real-time monitoring and provide rapid diagnosis of health condition. User’s context such as location, identities and etc which are collected by active sensor is important element in MHealthcare. This paper conducts a study pertaining to mobile cloud healthcare, mobile healthcare and comparisons between the variety of applications and architecture developed/proposed by researchers.
Driverless Cars will Make Rails Obsolete

Driverless vehicles will be common on the road in a short time. They will have many impacts on the global transport market trends. One of the remarkable driverless vehicles impacts will be the laying aside of rail systems, because of several reasons, that is to say traffic congestions will be no more a justification for rail, rail will not be the best answer for disableds, air pollution of cars are more or less equal to air pollution of trains and the last but not least reason is that driverless cars are safer than trains.
Change-blindness as a result of ‘mudsplashes’

Change-blindness, occurs when large changes are missed under natural viewing conditions because they occur simultaneously with a brief visual disruption, perhaps caused by an eye movement,, a flicker, a blink, or a camera cut in a film sequence. We have found that this can occur even when the disruption does not cover or obscure the changes. When a few small, high-contrast shapes are briefly spattered over a picture, like mudsplashes on a car windscreen, large changes can be made simultaneously in the scene without being noticed. This phenomenon is potentially important in driving, surveillance or navigation, as dangerous events occurring in full view can go unnoticed if they coincide with even very small, apparently innocuous, disturbances. It is also important for understanding how the brain represents the world.
Overview of ESP8266 Wi-Fi module based Smart Irrigation System using IOT

This paper demonstrates the efficient use of Internet of Things for the traditional agriculture. It shows the use of Arduino and ESP8266 based monitored and controlled smart irrigation systems, which is also cost-effective and simple. It is beneficial for farmers to irrigate there land conveniently by the application of automatic irrigation system. This smart irrigation system has pH sensor, water flow sensor, temperature sensor and soil moisture sensor that measure respectively and based on these sensors arduino microcontroller drives the servo motor and pump. Arduino received the information and transmitted with ESP8266 Wi-Fi module wirelessly to the website through internet. This transmitted information is monitor and control by using IOT. This enables the remote control mechanism through a secure internet web connection to the user. A website has been prepared which present the actual time values and reference values of various factors needed by crops. Users can control water pumps and sprinklers through the website and keep an eye on the reference values which will help the farmer increase production with quality crops.