nils-herrmann/clean_scirepeval huggingface dataset:
A New Way for Antihelixplasty in Prominent Ear Surgery: Modified Postauricular Fascial Flap.

Otoplasty procedures aim to reduce the concha-mastoid angle and recreate the antihelical fold. Here, we explained the modified postauricular fascial flap, described as a new way for recreating the antihelical fold, and reported the results of patients on whom this flap was used.



The defined technique was used on 24 patients (10 females and 14 males; age, 6-27 years; mean, 16.7 years) between June 2009 and July 2012, a total of 48 procedures in total (bilateral). Follow-up ranged from 1 to 3 years (mean, 1.5 years). At the preoperative and postoperative time points (1 and 12 months after surgery), all patients were measured for upper and middle helix-head distance and were photographed. The records were analyzed statistically using t test and analysis of variance.



The procedure resulted in ears that were natural in appearance without any significant visible evidence of surgery. The operations resulted in no complications except 1 patient who developed a small skin ulcer on the left ear because of band pressure. When we compared the preoperative and postoperative upper and middle helix-head distance, there was a high significance statistically.



To introduce modified postauricular fascial flap, we used a simple and safe procedure to recreate an antihelical fold. This procedure led to several benefits, including a natural-in-appearance antihelical fold, prevention of suture extrusion and granuloma, as well as minimized risk for recurrence due to neochondrogenesis. This method may be used as a standard procedure for treating prominent ears surgically.
[Diagnosis and treatment of endodermal sinus tumor of the vagina].

To describe the clinical characteristics and the role of chemotherapy in endodermal sinus tumor of the vagina.



Two patients with endodermal sinus tumor of the vagina were presented focusing on the clinical manifestations and outcome of the chemotherapy.



Patient's age was quite young, 2 and 3 years old respectively. Vaginal bleeding and a polypoid and fragile tumor of the vagina were main clinical features. Elevated serum alpha-FP was found before chemotherapy and dropped dramatically to normal if the tumor was sensitive to chemotherapy. Diagnosis was made by pathology and alpha-FP immunohistochemical staining. Both two patient was well responded to cisplatin vincristine bleomycin (PVB) and cisplatin etoposide bleomycin (PEB) chemotherapy. Clinical and pathological complete remission was obtained after 2-3 courses of chemotherapy without radical surgery and radiotherapy.



Endodermal sinus tumor of vagina in infant was very sensitive to the chemotherapy. Serum alpha-FP was very useful in diagnosis and monitoring of the disease.
Potential Test of Papaya Leaf and Seed Extract (Carica Papaya) as Larvicides against Anopheles Mosquito Larvae Mortality. Sp in Jayapura, Papua Indonesia

Anopheles mosquitoes, sp is the main vector of malaria disease that is widespread in many parts of the world including in Papua Province. There are four speciesof Anopheles mosquitoes, sp, in Papua namely: An.farauti, An.koliensis, An. subpictus, and An.punctulatus. Larviciding synthetic cause resistance. This study aims to analyze the potential of papaya leaf and seeds extracts (Carica papaya) as larvicides against the mosquitoes Anopheles sp. The experiment was conducted at the Laboratory of Health Research and Development in Jayapura Papua province. The method used is an experimental post only control group design. Sampling was done randomly on the larvae of Anopheles sp of breeding places in Kampung Kehiran Jayapura Sentani District, 1,500 larvae. Analysis of data using statistical analysis to test the log probit mortality regression dosage, Kruskall Wallis and Mann Whitney. The results showed that papaya leaf extract effective in killing larvae of Anopheles sp, value Lethal Concentration (LC50) were 422.311 ppm, 1399.577 ppm LC90, Lethal Time (LT50) 13.579 hours, LT90 23.478 hours. Papaya seed extract is effective in killing mosquito larvae Anopheles sp, with 21.983 ppm LC50, LC90 ppm 137.862, 13.269 hours LT50, LT90 26.885 hours. Papaya seed extract is more effective in killing larvae of Anopheles sp. The mixture of papaya leaf extract and seeds are effective in killing mosquito larvae Anopheles sp, indicated by the percentage of larval mortality, the observation hours to 12, the highest larval mortality in comparison 0,05:0,1 extract, 52%, ratio 0.1 : 0.1 by 48 %, on a 24 hour observation, larval mortality in both groups reached 100 %.
Clinical encounters with internet pornography.

Pornography, if understood to involve the depiction of sexual activity, organs, and experiences, is perhaps as old as human civilization itself. Historically linked to various technological innovations, pornography viewing in the Internet age has reached epic proportions, with large numbers of individuals taking advantage of ease of access, affordability, and presumed anonymity to explore sexual material online. Within the mental health professions substantial research exists on the effects of viewing general pornography; however, the distinctive effects of the marriage of pornography and cyberspace is only beginning to be examined. In addition to reviewing some historical and statistical material about pornography and the relevant psychiatric and psychoanalytic literature, four detailed clinical vignettes are presented to illustrate the types of problems related to Internet pornography use that are being presented to practicing psychotherapists.
Summarization Approach for Unstructured Customer Reviews in the field of E-commerce A Comparative Analysis

Due to the large amounts of text data being generated and organizations increased rapidly with the availability of Big Data platforms, there is no enough time to read and understand each document and make decisions based on document contents. Hence, there is a great demand for summarizing text documents to provide a representative substitute for the original documents. Text summarization is the task of reducing a text document with help of a computer program in order to create a summary that keeps the most important points of the original document. It is not easy task for people to manually summarize large documents of text data. There are two methods to summarize a text data 1) extractive summarization and 2) abstractive summarization. An extractive summarization method selects important sentence, content etc. from the original text data and combined them into shorter form. An abstractive summarization method understand the original text data and re-telling it in fewer words to generate summary. Popularity and growth of E-commerce has led to the creation of several websites that market and sell products as well as allow customer to post reviews and that reviews about a product grows rapidly. The number of reviews can be more than hundreds or thousands for a particular product. So it is difficult for a potential customer to take decision about products by reading all reviews manually and if he reads only a few of those reviews, then he may get a biased and confused view about the product. Product reviews are written by persons is not in structured form, natural language text; the process of summarizing them is one challenge and has a great commercial importance. With a feature-based summary, a current customer can easily see what other customer feels about product and can take decision. For a maker of a product, it is possible to combine summaries from multiple web sources to produce a single report for each product. In this paper, we present a survey and Comparative Analysis of Text Summarization Approach for Unstructured Customer Reviews in the field of E-commerce.  Text Mining, Text summarization, Product Review, Information Retrieval, E-commerce, opinion analysis.
Speech Recognition with Dynamic Time Warping using MATLAB

— Speech recognition has found its application on various aspects of our daily lives from automatic phone answering service to dictating text and issuing voice commands to computers. In this paper, we present the historical background and technological advances in speech recognition technology over the past few decades. More importantly, we present the steps involved in the design of a speaker-independent speech recognition system. We focus mainly on the pre-processing stage that extracts salient features of a speech signal and a technique called Dynamic Time Warping commonly used to compare the feature vectors of speech signals. These techniques are applied for recognition of isolated as well as connected words spoken. We conduct experiments on MATLAB to verify these techniques. Finally, we design a simple 'Voice-to-Text' converter application using MATLAB.
Suicide risk assessment and risk formulation part I: a focus on suicide ideation in assessing suicide risk.

The main procedure used by clinicians to determine whether an individual may be at risk of suicidal behaviors is the suicide risk assessment (SRA). The purpose of the SRA is to identify risk and protective factors that then provide the data for the formulation of suicide risk. The suicide risk formulation (SRF) assigns a level of suicide risk that ideally leads to triage and treatment deemed appropriate for that level of risk. Some of the problems with the SRA are explored here, with an emphasis on addressing the over reliance on communicated suicide ideation, and recommendations are made for improvements. Part II of this article (Berman & Silverman, 2013, also appears in this issue of STLB) examines the process of an SRF and, similarly, makes recommendations to improve clinical practice toward the desired end of saving lives.
Integrating the Supply Chain

The Scope of the Supply Chain The role of manufacturing industry is to create wealth by adding value and selling products. Common to all manufacturing companies is the need to control the flow of material from suppliers, through the value adding processes and distribution channels, to customers. The supply chain, as shown in Figure 1, is the connected series of activities which is concerned with planning, coordinating and controlling material, parts and finished goods from suppliers to the customer. It is concerned with two distinct flows through the organisation: material and information. The scope of the supply chain begins with the source of supply and ends at the point of consumption. It extends much further than simply a concern with the physical movement of material and is just as much concerned with supplier management, purchasing, materials management, manufacturing management, facilities planning, customer service and information flow as with transport and physical distribution.
Geosocial Media Data as Predictors in a GWR Application to Forecast Crime Hotspots (Short Paper)

In this paper we forecast hotspots of street crime in Portland, Oregon. Our approach uses geosocial media posts, which define the predictors in geographically weighted regression (GWR) models. We use two predictors that are both derived from Twitter data. The first one is the population at risk of being victim of street crime. The second one is the crime related tweets. These two predictors were used in GWR to create models that depict future street crime hotspots. The predicted hotspots enclosed more than 23% of the future street crimes in 1% of the study area and also outperformed the prediction efficiency of a baseline approach. Future work will focus on optimizing the prediction parameters and testing the applicability of this approach to other mobile crime types.
Novelty and Conventionality in International Research Collaboration

Research produced through international collaboration is often more highly cited than other work, but is it also more novel? Using measures of conventionality and novelty developed by Uzzi et al. (2013) and replicated by Boyack and Klavans (2013), we test for novelty and conventionality in international research collaboration. Many studies have shown that international collaboration is more highly cited than national or sole-authored papers. Others have found that coauthored papers are more novel. Scholars have suggested that diverse groups have a greater chance of producing creative work. As such, we expected to find that international collaboration is also more novel. Using data from Web of Science and Scopus in 2005, we failed to show that international collaboration tends to produce more novel articles. In fact, international collaboration appeared to produce less novel and more conventional research. Transaction costs and the limits of global communication may be suppressing novelty, while an “audience effect” may be responsible for higher citation rates. Closer examination across the sciences, social sciences, and arts and humanities, as well as examination of six scientific specialties further illuminates the interplay of conventionality and novelty in work produced by international research teams.
Travel Speed Prediction with a Hierarchical Convolutional Neural Network and Long Short-Term Memory Model Framework

Advanced travel information and warning, if provided accurately, can help road users avoid traffic congestion through dynamic route planning and behavior change. It also enables traffic control centres mitigate the impact of congestion by activating Intelligent Transport System (ITS) proactively. Deep learning has become increasingly popular in recent years, following a surge of innovative GPU technology, high-resolution, big datasets and thriving machine learning algorithms. However, there are few examples exploiting this emerging technology to develop applications for traffic prediction. This is largely due to the difficulty in capturing random, seasonal, non-linear, and spatio-temporal correlated nature of traffic data. In this paper, we propose a data-driven modelling approach with a novel hierarchical D-CLSTM-t deep learning model for short-term traffic speed prediction, a framework combined with convolutional neural network (CNN) and long short-term memory (LSTM) models. A deep CNN model is employed to learn the spatio-temporal traffic patterns of the input graphs, which are then fed into a deep LSTM model for sequence learning. To capture traffic seasonal variations, time of the day and day of the week indicators are fused with trained features. The model is trained end-to-end to predict travel speed in 15 to 90 minutes in the future. We compare the model performance against other baseline models including CNN, LGBM, LSTM, and traditional speed-flow curves. Experiment results show that the D-CLSTM-t outperforms other models considerably. Model tests show that speed upstream also responds sensibly to a sudden accident occurring downstream. Our D-CLSTM-t model framework is also highly scalable for future extension such as for network-wide traffic prediction, which can also be improved by including additional features such as weather, long term seasonality and accident information.
Principal component analysis for clustering gene expression data

There is a great need to develop analytical methodology to analyze and to exploit the information contained in gene expression data. Because of the large number of genes and the complexity of biological networks, clustering is a useful exploratory technique for analysis of gene expression data. Other classical techniques, such as principal component analysis (PCA), have also been applied to analyze gene expression data. Using different data analysis techniques and different clustering algorithms to analyze the same data set can lead to very different conclusions. Our goal is to study the effectiveness of principal components (PCs) in capturing cluster structure. Specifically, using both real and synthetic gene expression data sets, we compared the quality of clusters obtained from the original data to the quality of clusters obtained after projecting onto subsets of the principal component axes.



Our empirical study showed that clustering with the PCs instead of the original variables does not necessarily improve, and often degrades, cluster quality. In particular, the first few PCs (which contain most of the variation in the data) do not necessarily capture most of the cluster structure. We also showed that clustering with PCs has different impact on different algorithms and different similarity metrics. Overall, we would not recommend PCA before clustering except in special circumstances.
Toxicity and Biodegradation Testing

Nowadays, many different chemicals exerting negative effects on both human and animal health are widely present in the environment. Compounds that interfere in the action of endocrine system due to their structural similarities to the real hormones called endocrine disrupting chemicals have received much attention because they are suspected to affect reproduction, development, metabolism of living organisms and even induce cancer. Moreover, the endocrine-related disorders are often passed down to the next generations and alter their disease susceptibility. This group of substances includes both naturally occurring chemicals (e.g., phytoestrogen—coumestrol) and synthetic compounds used in industrial processes, agriculture, and household products (e.g., polychlorinated biphenyls, polybrominated biphenyls, polycyclic aromatic hydrocarbons, some pesticides, components of plastics such as bisphenols and phthalates). Among these compounds there are some groups of chemicals still widely used and therefore constituting an important source of health hazards. The most important man-made endocrine disrupting compounds belong to three groups which met with great interest in last years, i.e., phthalates, bisphenols (mainly bisphenol A), and alkylphenols (used mainly as ethoxylates). Decades of their production and usage led to considerable contamination of the environment. They are found in water, air, soil, both animal and plant food. Therefore, growing number of studies are devoted to their degradation, biodegradation, and removal from the environment. Present studies on the biodegradation of phthalates, bisphenols, and alkylphenol derivatives aim mainly at testing of selected bacterial strains of different lineage including some Bacillus sp., Gordonia sp., Pseudoxanthomonas sp., Sphingomonas sp., and Rhodococcus sp. bacteria as well as other bacterial strains. Tests with fungi like Aspergillus sp. and Polyporus sp. or fungal enzymes like laccases are also carried out. Ultimately, understanding metabolic pathways of diverse species and genes involved in the biodegradation may help in constructing bacterial or fungal strains through usage of genetic engineering for effective removal of selected endocrine disrupting compounds. On the other hand, studies on removal of these contaminants from the environment were also undertaken. Biodegradation in natural waters, including seawater and in soil and sediments was tested to gain information on possibility of their removal from contaminated areas.
Controller design for a bipedal walking robot using variable stiffness actuators

The bipedal spring-loaded inverted pendulum (SLIP) model captures characteristic properties of human locomotion, and it is therefore often used to study human-like walking. The extended variable spring-loaded inverted pendulum (V-SLIP) model provides a control input for gait stabilization and shows robust and energy-efficient walking patterns. This work presents a control strategy that maps the conceptual V-SLIP model on a realistic model of a bipedal robot. This walker implements the variable leg compliance by means of variable stiffness actuators in the knees. The proposed controller consists of multiple levels, each level controlling the robot at a different level of abstraction. This allows the controller to control a simple dynamic structure at the top level and control the specific degrees of freedom of the robot at a lower level. The proposed controller is validated by both numeric simulations and preliminary experimental tests.
Effect of Black Walnut ( Tetracarpidium conophorum ) Leaf Extract on the Reproductive Organ of Male Albino Rats

This study determined the effect of Tetracarpidium conophorum (black walnut) leaf extract on the male reproductive organs of albino rats. The effects of the leaf extracts were determined on the Epididymal sperm concentration, Testicular histology, and on testosterone concentration in the rat serum by a micro plate enzyme immunoassay (Testosterone assay). A total of sixteen (16) male albino wistar rats were divided into four (1, 2, 3 and 4) groups of four rats each. Group 1 served as the control and was fed with normal diet only, while groups 2, 3 and 4 were fed with 200, 400 and 600 mg/kg body weight (BW) of the extract for a period of two weeks. The Epididymal sperm concentration were not significantly affected (p>0.05) across the groups. The level of testosterone for the treatment groups 2 and 4 showed no significant difference (p>0.05) compared to the control while group 4 showed significant increase compared to that of the control (p<0.05). Pathologic changes were observed in testicular histology across the treatment groups. Robust seminiferous tubular lumen containing sperm cells and increased production of Leydig cells and Sertoli cells were observed across different treatment groups compared to that of the control.
Metric-space analysis of spike trains: theory, algorithms, and application

We present the mathematical basis of a new approach to the analysis of temporal coding. The foundation of the approach is the construction of several families of novel distances (metrics) between neuronal impulse trains. In contrast to most previous approaches to the analysis of temporal coding, the present approach does not attempt to embed impulse trains in a vector space, and does not assume a Euclidean notion of distance. Rather, the proposed metrics formalize physiologically based hypotheses for those aspects of the firing pattern that might be stimulus dependent, and make essential use of the point-process nature of neural discharges. We show that these families of metrics endow the space of impulse trains with related but inequivalent topological structures. We demonstrate how these metrics can be used to determine whether a set of observed responses has a stimulus-dependent temporal structure without a vector-space embedding. We show how multidimensional scaling can be used to assess the similarity of these metrics to Euclidean distances. For two of these families of metrics (one based on spike times and one based on spike intervals), we present highly efficient computational algorithms for calculating the distances. We illustrate these ideas by application to artificial data sets and to recordings from auditory and visual cortex.
Concatenated coded OFDM system over AWGN channel with H.264 source coding

This paper presents a robust concatenated coding scheme for OFDM with 64 QAM over AWGN channel. At the forward error correction unit, our proposed concatenated coding scheme employs standard form of BCH code as outer code and LDPC code as inner code. Varying from the code rates of BCH codes, we can find the minimum requirement of signal to noise ratio in the proposed concatenated coding scheme. In addition, our proposed scheme can yield better performance than that using BCH (7200, 7032) code in ETSI EN 302 775. Finally, we apply the H.264 source coding via our platform for demonstrations.