nils-herrmann/clean_scirepeval huggingface dataset:
Facebook and the cultivation of ethnic diversity perceptions and attitudes
Venue: Internet Res.
Year: 2020

The purpose of this paper is to apply cultivation theory to social network sites by investigating how Facebook uses cultivates users' ethnic diversity perceptions and attitudes.,The authors' investigations include an online and offline survey study with 476 Facebook users and a follow up experiment with 75 individuals.,The authors provide empirical support that Facebook use cultivates ethnic diversity perceptions and ethnic diversity related attitudes. They show that Facebook use relates to perceptions of ethnic minorities that resemble the world on Facebook that is characterized by high ethnic diversity. The authors further demonstrate that the cultivation of ethnic diversity related attitudes is mediated by diversity perceptions related to users' close social environment.,Future research should consider culturally and educationally diverse samples as well as longitudinal research designs to address external validity and causality issues.,Algorithms determining the content users are exposed should be thoughtfully curated to avoid attitudinal and ideological polarization.,Facebook can play an important role in positively shaping intergroup relations, thereby countering negative outgroup attitudes, social anxieties and radical right wing parties.,The authors' studies extend the scope of cultivation research by identifying a new media vehicle as a source of cultivation influences and shed light on the cultivation based process of attitude change on social network sites.
Wound Healing Potential of Ipomoea carnea Jacq. An Un Explored Herb Used in Indian Traditional System of Medicine
Year: 2017

Wounds can be major causes of physical disabilities and may lead to losses of many productive man hours  Wounds are essentially the disruption of functional continuity of cells and tissues at the site of injury, and can be caused by insults to the tissue sites by physical, chemical, microbiological or immunological process  Humans and all animals have in situ capabilities of healing wounds in their body parts through continuous tissue repair and tissue regeneration  However, such capabilities are impaired by age, stress situation, obesity, sex, life style, conditions of health and immunity status, severity and types of wounds, patient's medication status, disastrous nature of the assault environment around the site of the wounds and potentials of serious microbial infection
Facile one step method realizing scalable production of g C3N4 nanosheets and study of their photocatalytic H2 evolution activity
Year: 2014

Graphene like g C3N4 nanosheets show great potential application in varied fields owing to their unique electronic and optical properties. However, most of the developed methods for preparing g C3N4 nanosheets still suffer from low yield and time consuming shortcomings, which considerably hamper their further study and application. Herein, a facile dicyandiamide blowing method with NH4Cl as the gas template for the synergic achievement of large quantity and high quality graphene like g C3N4 nanosheets has been reported. The g C3N4 nanosheets prepared by this one step method possess enhanced specific area surface, improved electron transport ability and increased lifetime of photoexcited charge carriers, revealing enhanced photocatalytic H2 activities than that of bulk g C3N4. Our work represents a significant progress for the scalable fabrication of high quality 2D g C3N4 and provides a new pathway for the scalable production of other 2D nanomaterials.
Low Dose Ionizing Radiation Modulates the Expression of Proangiogenic Genes in Critical Limb Ischemia Patients: Preliminary Results
Year: 2019

The use of artificial intelligence (AI) in health care is based on machine learning algorithms and software to replace human cognition in the analysis of medical data. We aimed to provide a systematic review on the use of AI in peripheral vascular diseases (PVDs)  A systematic review was conducted through the PubMed database. Search terms were focused to identify studies reporting artificial intelligence OR algorithm OR natural language processing OR machine learning OR neural networks AND peripheral vascular disease NOT robotics.  A total of 25 articles from 1956 to 2019 were included. These represented empirical work from qualitative, quantitative, and mixedmethods approaches, with mainly AI software use in PVD. The studies examined the application of AI software in the identification of risk factors and screening (2 studies) diagnosis (13 studies) management (2 studies) and assessment of the complications and severity of PVD (7 studies) There was also a study comparing three different models in the diagnosis of PVD. Of the 25 articles, the AI software had shown positive results in their respective domains in 24 articles. Risk factors for PVD were identified and were used by the AI software to screen for asymptomatic PVD in the general population, and the positive predictive value for the AI was twice that of the Inter Society Consensus screening criteria, the current universal screening score. The AI software was able to compile and to interpret the results to generate a diagnosis of PVD with high specificity and sensitivity according to the consistently high diagnostic accuracy findings from 12 of the articles on PVD diagnosis. The AI was also able to generate a management algorithm with multiple treatment routes based on the patient's profile.  Currently, AI is helpful to aid in the journey of PVD patients from screening to management. However, more research and development are required before it can be widely applied to assist physicians in the management of patients with PVD.
Epidemiological Survey on Schistosomiasis and Intestinal Helminthiasis among Village Residents of the Rural River Basin Area in White Nile State, Sudan
Venue: The Korean journal of parasitology
Year: 2019

There have been some reports on schistosomiasis of school children in Sudan's Nile River basin area; however, information about the infection status of Schistosoma species and intestinal helminths among village residents of this area is very limited. Urine and stool samples were collected from the 1,138 residents of the Al Hidaib and Khour Ajwal villages of White Nile State, Sudan in 2014. The prevalence of overall schistosomiasis and intestinal helminthiasis was 36.3% and 7.7% respectively. Egg positive rates were 35.6% for Schistosoma haematobium, 2.6% for S. mansoni, and 1.4% were mixed. The prevalence of schistosomiasis was significantly higher in men (45.6% than in women (32.0% in Khou Ajwal villagers (39.4% than in Al Hidaib villagers (19.2% and for age groups =15 years old (51.5% than for age groups >15 years old (13.2% The average number of eggs per 10 ml urine (EP10) of S. haematobium infections was 18.9, with 22.2 eggs in men vs 17.0 in women and 20.4 in Khou Ajwal villagers vs 8.1 in Al Hidaib villagers. In addition to S. mansoni eggs, 4 different species of intestinal helminths were found in the stool, including Hymenolepis nana (6.6% and H. diminuta (1.0% Collectively, urinary schistosomiasis is still prevalent among village residents in Sudan's White Nile River basin and was especially high in men, children =15 years, and in the village without a clean water system. H. nana was the most frequently detected intestinal helminths in the 2 villages.
Polar steroid derivatives from the Vietnamese starfish Astropecten polyacanthus
Venue: Natural product research
Year: 2018

Five polar steroid derivatives, including one new glycosylated polyhydroxysteroid namely polyacanthoside A (1) were isolated from the water soluble materials from the MeOH extract of the Vietnamese starfish Astropecten polyacanthus using various chromatographic separations. The structure elucidation was confirmed by spectroscopic experiments such as HR ESI MS, 1D and 2D NMR. Among the isolated compounds, (20R,24S) 3b,6a,8,15b,24 pentahydroxy 5a cholestane (3) showed significant cytotoxic effect against five human cancer cell lines as HepG2, KB, LNCaP, MCF7 and SK Mel2 with the IC50 values from 18.03 2.63 to 21.59 3.23 mM.
BMN: Boundary Matching Network for Temporal Action Proposal Generation
Venue: 2019 IEEE/CVF International Conference on Computer Vision (ICCV)
Year: 2019

Temporal action proposal generation is an challenging and promising task which aims to locate temporal regions in real world videos where action or event may occur. Current bottom up proposal generation methods can generate proposals with precise boundary, but cannot efficiently generate adequately reliable confidence scores for retrieving proposals. To address these difficulties, we introduce the Boundary Matching (BM) mechanism to evaluate confidence scores of densely distributed proposals, which denote a proposal as a matching pair of starting and ending boundaries and combine all densely distributed BM pairs into the BM confidence map. Based on BM mechanism, we propose an effective, efficient and end to end proposal generation method, named Boundary Matching Network (BMN) which generates proposals with precise temporal boundaries as well as reliable confidence scores simultaneously. The two branches of BMN are jointly trained in an unified framework. We conduct experiments on two challenging datasets: THUMOS 14 and ActivityNet 1.3, where BMN shows significant performance improvement with remarkable efficiency and generalizability. Further, combining with existing action classifier, BMN can achieve state of the art temporal action detection performance.
Solving the Set Covering Problem with a Binary Black Hole Inspired Algorithm
Venue: ICCSA
Year: 2016

There are multiple problems in several industries that can be solved with combinatorial optimization. In this sense, the Set Covering Problem is one of the most representative of them, being used in various branches of engineering and science, allowing find a set of solutions that meet the needs identified in the restrictions that have the lowest possible cost. This paper presents an algorithm inspired by binary black holes (BBH) to resolve known instances of SPC from the OR Library. Also, it reproduces the behavior of black holes, using various operators to bring good solutions.
Citation Analysis of LIS Dissertations for Collection Development
Year: 2017

This book is designed to analyze bibliographic references cited by Library and Information Science postgraduate students in their dissertation for determining patron driven collection development. This book covers the concept, importance, development and methods for citation analysis. An overview of citation metrics and criticism of citation analysis has also been discussed in this book. The results showed that Journals are the most cited bibliographic format of the total citation.among the students. It was found that the dispersion of journal titles did not satisfy the verbal formulation of Bradford's Law of Scattering. The findings revealed the extensive use of collaborative author is popular among the masters students of LIS. Most of the information resources heavily cited by students are foreign. The study recommends that efforts should be made towards acquiring all titles that were extensively cited by students that were not available in the university library.
Predicting change in management accounting systems: a contingent approach
Year: 2017

This study investigated the frequency and location of changes in management accounting and control systems in a sample of Canadian manufacturing companies. Using regression and path analysis the study attempted to understand how five environmental variables influenced change in the management accounting and control systems through the organizational structure. The findings indicate that changes in management accounting were best predicted by organization capacity to learn. Such changes mostly occur in systems that support planning and control followed by those that support decision making. The intensity of competition was found to affect management accounting change through the organizational structure. Organizations that placed a high emphasis on differentiation strategies reported significant changes in their management accounting and control systems.
The Neuroprotective and Biomarker Potential of PACAP in Human Traumatic Brain Injury
Venue: International journal of molecular sciences
Year: 2020

Traumatic brain injury remains a growing public health concern and represents the greatest contributor to death and disability globally among all trauma related injuries. There are limited clinical data regarding biomarkers in the diagnosis and outcome prediction of TBI. The lack of real effective treatment for recovery calls for research of TBI to be shifted into the area of prevention, treatment of secondary brain injury and neurorehabilitation. The neuropeptide pituitary adenylate cyclase activating polypeptide (PACAP) has been reported to act as a hormone, a neuromodulator, a neurotransmitter and a trophic factor, and has been implicated in a variety of developmental and regenerative processes. The importance of PACAP in neuronal regeneration lies in the upregulation of endogenous PACAP and its receptors and the protective effect of exogenous PACAP after different central nervous system injury. The aim of this minireview is to summarize both the therapeutic and biomarker potential of the neuropeptide PACAP, as a novel possible target molecule presently being investigated in several human conditions including TBI, and with encouraging results in animal models of TBI.
La cofradia de las aranas. Mitos y ritos hermeticos de las maestras textileras mapuches
Year: 2017

Analizamos material mitico central en la ideologia de las maestras textileras y los ritos de iniciacion al que son sometidas las aspirantes a maestras tejedoras mapuches. Tales mitos refieren a narrativas mitologicas fundacionales en relatos guardados por tejedoras consagradas, que explican las categoria basales sobre las que se construye su ideologia, ya que, el mito establece el marco contextual y practico tanto de los pasos performativos del ritual como del sistema categorial esencial que toda tejedora novata debe dominar. Las practicas de la iniciacion textil se recubren de una densa estetica basada en el diseno de la tela de las aranas y de las mujeres; en texturas, colores, iconos y pliegues, cargados con significados de los mitos y ritos en una visualidad integral.
Analyzing Knowledge Transfer in Deep Q Networks for Autonomously Handling Multiple Intersections
Venue: ArXiv
Year: 2017

We analyze how the knowledge to autonomously handle one type of intersection, represented as a Deep Q Network, translates to other types of intersections (tasks) We view intersection handling as a deep reinforcement learning problem, which approximates the state action Q function as a deep neural network. Using a traffic simulator, we show that directly copying a network trained for one type of intersection to another type of intersection decreases the success rate. We also show that when a network that is pre trained on Task A and then is fine tuned on a Task B, the resulting network not only performs better on the Task B than an network exclusively trained on Task A, but also retained knowledge on the Task A. Finally, we examine a lifelong learning setting, where we train a single network on five different types of intersections sequentially and show that the resulting network exhibited catastrophic forgetting of knowledge on previous tasks. This result suggests a need for a long term memory component to preserve knowledge.
Costs of hospitalized ventilator dependent children: Differences between a ventilator ward and intensive care unit
Venue: Pediatric pulmonology
Year: 2011

Hospitalizing clinically stable patients in critical care settings results in unnecessary healthcare costs and thwarts timely patient throughput. Some pediatric hospitals care for their stable ventilator dependent children outside of pediatric intensive care units (PICUs) To date, no analysis of the costs of these pediatric ventilator units compared to PICUs has been performed. We conducted a retrospective comparison of PICU and ventilator ward costs of hospitalizations for 103 admissions in which ventilator dependent children served as their own matched controls between 2004 and 2007. For included admissions, patients were hospitalized in both units during the same admission and spent more than 1 day in their initial unit. Comparisons of costs were made using the last full PICU day and first full ward day. For the study period, the mean PICU cost of hospitalization per day was $3,565 (standard deviation [SD] 716.50) The mean ward cost was $2,052 (SD 617) The mean PICU cost was significantly larger than the mean ward cost (paired t test, P 0.0001) Ventilator ward total and variable costs were significantly less than those in the PICU, and such units represent a potential cost saving measure for hospitals that care for ventilator dependent children. Pediatr Pulmonol.
Event Driven Random Back Propagation: Enabling Neuromorphic Deep Learning Machines
Venue: Front. Neurosci.
Year: 2017

An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of network wide information stored with high precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event driven random BP (eRBP) rule that uses an error modulated synaptic plasticity for learning deep representations. Using a two compartment Leaky Integrate Fire (I&F) neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning.
Generalized hyperstability of a Drygas functional equation on a restricted domain using Brzdek's fixed point theorem
Year: 2017

Motivated by the notion of Ulam stability, we investigate the generalized hyperstability results for the Drygas functional equation \begin{aligned} f(x+y)+f(x y)=2f(x)+f(y)+f( y) \end{aligned}$f(x+y)+f(x y)=2f(x)+f(y)+f( y),on a restricted domain. The method is based on a quite recent fixed point theorem (cf. [6, Theorem 1] in some functions spaces. We derive from them some characterizations of inner product spaces. Our results are improvements and generalizations of the main results of Piszczek and Szczawinska [29]
Nursing observation on vascular complications of the puncture site after the full cerebral digital subtraction angiography via femoral artery
Year: 2012

To investigate the nursing observation on vascular complications of the puncture site after full cerebral digital subtraction angiography(DSA) via femoral artery.Method:295 patients with postoperative complications were analyzed. cases were with sub dermal ecchymosis,5 cases with regional bleeding,5 cases with subcutaneous hematoma and 1 case with pseudoaneurysm.Serious complications can be reduced or even prevented by closer observation,timely treatment and efficient health education among patients after full cerebral DSA.
Hierarchical Feature Selection for Random Projection
Venue: IEEE Transactions on Neural Networks and Learning Systems
Year: 2019

Random projection is a popular machine learning algorithm, which can be implemented by neural networks and trained in a very efficient manner. However, the number of features should be large enough when applied to a rather large scale data set, which results in slow speed in testing procedure and more storage space under some circumstances. Furthermore, some of the features are redundant and even noisy since they are randomly generated, so the performance may be affected by these features. To remedy these problems, an effective feature selection method is introduced to select useful features hierarchically. Specifically, a novel criterion is proposed to select useful neurons for neural networks, which establishes a new way for network architecture design. The testing time and accuracy of the proposed method are improved compared with traditional methods and some variations on both classification and regression tasks. Extensive experiments confirm the effectiveness of the proposed method.
Hur foretag kan implementera customer relationship management
Year: 2015

En okad kundmedvetenhet och den okande globala konkurrensen har gjort att det blivit allt viktigare for foretag att bemota och varda sina kundrelationer. Detta har gjort att fler foretag valjer att arbeta med Customer Relationship Management (CRM) CRM ar ett verktyg som blir alltmer vanligt da det hanterar och vardar kundrelationer och kan ge en betydande konkurrensfordel for foretag. Tidigare studier havdar att CRM kommer att ha en betydande roll i framtiden for lakemedelsindustrin pa grund av dess komplexitet och industrins harda konkurrens. Trots CRM:s okade betydelse och att foretag runt om i varlden inversterar stora summor pengar pa CRM har resultaten av implementeringen ofta visat sig misslyckade eller overksamma. Denna studie syftar till att utforska implementeringsprocessen av CRM i foretag for att forsta vad som kan paverka implementering. Detta for att bidra i utvecklingen av ett ramverk for implementeringen av CRM i foretag. Studien bygger pa en induktiv ansats och for att besvara uppsatsens forskningsfragor har en litteraturstudie genomforts tillsammans med en fallstudie av lakemedelsforetaget Swedish Oprhan Biovitrum (Sobi) Fallstudien har genomforts med intervjuer fran medarbetare pa Sobi som berattar om deras implementering. Studiens resultat visar att sju aspekter ar viktiga for foretag som implementerar CRM: kundorientering, strategi, organisation, ledning, medarbetare, teknologi och kommuikation. Dessa aspekter kan paverka en implementerings framgang, men de kan ocksa leda till problem om de hanteras pa fel satt. Vissa aspekter kan ha olika betydelse beroende pa foretag och de kan paverka olika beroende pa de unika forutsattningar som rader i foretaget.
A Reinforcement Learning Method for a Hybrid Flow Shop Scheduling Problem
Venue: Algorithms
Year: 2019

The scheduling problems in mass production, manufacturing, assembly, synthesis, and transportation, as well as internet services, can partly be attributed to a hybrid flow shop scheduling problem (HFSP) To solve the problem, a reinforcement learning (RL) method for HFSP is studied for the first time in this paper. HFSP is described and attributed to the Markov Decision Processes (MDP) for which the special states, actions, and reward function are designed. On this basis, the MDP framework is established. The Boltzmann exploration policy is adopted to trade off the exploration and exploitation during choosing action in RL. Compared with the first come first serve strategy that is frequently adopted when coding in most of the traditional intelligent algorithms, the rule in the RL method is first come first choice, which is more conducive to achieving the global optimal solution. For validation, the RL method is utilized for scheduling in a metal processing workshop of an automobile engine factory. Then, the method is applied to the sortie scheduling of carrier aircraft in continuous dispatch. The results demonstrate that the machining and support scheduling obtained by this RL method are reasonable in result quality, real time performance and complexity, indicating that this RL method is practical for HFSP.