nils-herrmann/clean_scirepeval huggingface dataset:
IMMU 10. USE OF A SINGLE PEPTIDE CHECKPOINT INHIBITOR FOR TREATMENT OF CENTRAL NERVOUS SYSTEM TUMORS
Venue: Neuro Oncology
Year: 2021

Cancer immunotherapy has revolutionized clinical management of malignancies by generating long term, durable control of tumors. Unfortunately, these therapies often cause serious immune related adverse events. In addition, only a small percentage of solid tumors respond to these therapies and there is little efficacy in CNS tumors. Our research is focused on the CD200 immune checkpoint, which modulates the immune system through the inhibitory receptor (CD200R1) and activation receptors (CD200AR) We demonstrated that targeting the CD200AR with a checkpoint peptide ligand (CD200AR L) activates the immune system and renders it impervious to the inhibitory effects of CD200. In a pre clinical canine spontaneous high grade glioma trial, CD200AR L, with autologous tumor lysate vaccination, resulted in a 20% two year progression free survival; no toxicities or adverse effects were observed. We suggest this result was due to the ability of the CD200AR L to modulate multiple immune checkpoints. During the characterization of the CD200AR L, we discovered signaling molecules are shared by the CD200 and PD 1/PD L1 checkpoint pathways, suggesting these immune checkpoints are connected. Our preliminary studies demonstrated that the inhibitory CD200R1 and PD 1 mediate immune checkpoint signaling activities through the SHIP1/2. Moreover, CD200AR L overpowers the suppressive effects of CD200 and PD L1, which are both shed by tumors, by downregulating the inhibitory CD200R1 and PD 1 on both antigen presenting cells (APC) and T cells. In addition, CD200AR L downregulates PD 1 on APCs and inhibits the upregulation of PD L1 and CTLA4. These studies led to the discovery that the novel peptide modulates the CD200, PD 1/PD L1 and CTLA 4 pathways, providing the basis for the translatable development of a CD200 directed peptide for clinical use against multiple tumors including gliomas. These studies led to FDA approval of this peptide for the first in human phase I single center, open label, dose escalation clinical trial (NCT04642937) in adult and pediatric trial for children with recurrent malignant brain tumors.
Silver Surfers and New Media: Experiences, Thoughts and Observations of Elder People about Internet
Year: 2018

The effects of internet over media had changed either content production of mass media or audience way of using media. The breaking point created by internet has caused to call Radio, television and newspaper as "traditional media" while creating new media.The passive audience of traditional media had gained an active role by spread of Internet. New audience or user had gain content producer role for new media. There are considerable effects of Social Network Sites on content producing. Social network sites which are simulating social networks existing in public life, had give a new dimension to interpersonal communication with the help of asynchronous, independent from place and continuously opened communication channel. Another word, the interpersonal communication carried to public sphere had become a content of mass communication. When the technology had kept in step with this new situation, audience had increased rapidly. This development had caused wider the age range. Different genders are using new media and especially social network sites for many reasons such as to communicate, to get information, to get news and research. Different generations can show different adaptation levels to new media. It is a reality that people met Internet in early age or people who born in this new era are easily and completely adopted the new technology. The other side of this reality is elder people who had grown up with traditional media cannot easily adopt new media and its technology. That's why digital nomads and digital migrants discrimination is made. Researches are show that numbers of digital migrants are increasing. These increases show itself especially on to have new technology. This study aims to appear the observations, experience and thoughts of elder people (55 and up) about Internet and using technology. To reach this aim deep interview method are used on 6 women and 6 men who own new media technologies.
Austerity policing, emotional labour and the boundaries of police work: an ethnography of a police force control room in England
Year: 2018

This article discusses the changing role of policing in an era of austerity from the perspective of frontline civilian police staff (call handlers and dispatchers) in a force control room (FCR) It draws on a symbolic interactionist framework and the concept of emotional labour (Hochschild 1979; 1983[2012] in order to explore the emotional responses and strategies engaged in by staff when responding to 101 non emergency calls and 999 emergency calls. The clash of public and police expectations, and the emotional labour expended when managing this clash, provide a valuable insight into the frontline staff perspective on the changing role of the police under austerity. Data is drawn from ethnographic fieldwork in the control room of a police force in England.
Uji Predasi Tungau Predator (Neoseulus longspnosus) Terhadap Tungau Hama (Tetranychus sp. Yang Berasosiasi Pada Ekosistem Tanaman Kentang (Solanum tuberosum. Linn)
Year: 2018

ABSTRAK Penelitian ini bertujuan untuk mengetahui pengaruh kepadatan mangsa terhadap kemampuan mempredasi dari tungau Predator Neoseiuluslongispinosus terhadap Tungau Hama Tetranychus sp. yang berasosiasi pada ekosistem tanamankentang (Solanum tuberosum Linn. Penelitian ini telah dilaksanakan dari bulan Junisampai Agustus 2018 pada lahan budidaya kentangDesa Beririjarak,Kecamatan Wanasaba, Kabupaten Lombok Timur dan Laboratorum Proteksi Tanaman Fakultas Pertanian Universitas Mataram. Metode yang digunakan dalam penelitian ini adalah metode eksperimental RAL dengan pengambilan sampel di lapangan dan dilakukan pengujian di laboratorium. Hasil pengujian kemampuanmemangsa menunjukkan bahwapenambahan kepadatan mangsa tidak berpengaruh terhadap pemangsaan predatorNeoseoulusLongispinosus. ABSTRACK This study aims to determine the effect of prey on the prediction ability of Neoseiulus longispinosus mites against Tetranychus sp. which is associated with the plant ecosystem of potatoes (Solanum tuberosum Linn. This research has been carried out from June to August 2018 in the field of cultivation of the Beririjarak Village, Wanasaba District, East Lombok Regency and the Village Protection Laboratory of the Faculty of Agriculture, Mataram. The method used in this study is the experimental RAL method with sampling in the field and testing in the laboratory. The results of the ability show that the amount of density is not the same as the predator Neoseoulus Longispinosus.
(De)Randomized Smoothing for Certifiable Defense against Patch Attacks
Venue: NeurIPS
Year: 2020

Patch adversarial attacks on images, in which the attacker can distort pixels within a region of bounded size, are an important threat model since they provide a quantitative model for physical adversarial attacks. In this paper, we introduce a certifiable defense against patch attacks that guarantees for a given image and patch attack size, no patch adversarial examples exist. Our method is related to the broad class of randomized smoothing robustness schemes which provide high confidence probabilistic robustness certificates. By exploiting the fact that patch attacks are more constrained than general sparse attacks, we derive meaningfully large robustness certificates. Additionally, the algorithm we propose is de randomized, providing deterministic certificates. To the best of our knowledge, there exists only one prior method for certifiable defense against patch attacks, which relies on interval bound propagation. While this sole existing method performs well on MNIST, it has several limitations: it requires computationally expensive training, does not scale to ImageNet, and performs poorly on CIFAR 10. In contrast, our proposed method effectively addresses all of these issues: our classifier can be trained quickly, achieves high clean and certified robust accuracy on CIFAR 10, and provides certificates at the ImageNet scale. For example, for a 5*5 patch attack on CIFAR 10, our method achieves up to around 57.8% certified accuracy (with a classifier around 83.9% clean accuracy) compared to at most 30.3% certified accuracy for the existing method (with a classifier with around 47.8% clean accuracy) effectively establishing a new state of the art. Code is available at this https URL.
Medical tourism: Sea, sun, sand and surgery
Year: 2006

Medical tourism, where patients travel overseas for operations, has grown rapidly in the past decade, especially for cosmetic surgery. High costs and long waiting lists at home, new technology and skills in destination countries alongside reduced transport costs and Internet marketing have all played a role. Several Asian countries are dominant, but most countries have sought to enter the market. Conventional tourism has been a by product of this growth, despite its tourist packaging, and overall benefits to the travel industry have been considerable. The rise of medical tourism emphasises the privatisation of health care, the growing dependence on technology, uneven access to health resources and the accelerated globalisation of both health care and tourism.
A Game Theoretic Approach for Dynamic Information Flow Tracking to Detect Multistage Advanced Persistent Threats
Venue: IEEE Transactions on Automatic Control
Year: 2020

Advanced persistent threats (APTs) infiltrate cyber systems and compromise specifically targeted data and/or resources through a sequence of stealthy attacks consisting of multiple stages. Dynamic information flow tracking has been proposed to detect APTs. In this article, we develop a dynamic information flow tracking game for resource efficient detection of APTs via multistage dynamic games. The game evolves on an information flow graph, whose nodes are processes and objects (e.g. file, network endpoints) in the system and the edges capture the interaction between different processes and objects. Each stage of the game has prespecified targets that are characterized by a set of nodes of the graph. The goal of the APT is to evade detection and reach a target node of each stage. The goal of the defender is to maximize the detection probability while minimizing performance overhead on the system. The resource costs of the players are different and the information structure is asymmetric, resulting in a nonzero sum imperfect information game. We first calculate the best responses of the players and then compute Nash equilibrium for single stage attacks. We then provide a polynomial time algorithm to compute a correlated equilibrium for the multistage attack case. Finally, we simulate our model and algorithm on real world nation state attack data obtained from the Refinable Attack INvestigation (RAIN) system.
[Relationship between alcohol, drug use and traffic accidents related to nightlife among a Spanish youth sample in three autonomous communities in 2007]
Venue: Revista espanola de salud publica
Year: 2008

The phenomenon known as binge drinking and other drug abuse frequently occurs among young people in nightlife related areas. This study analyzes the risk behaviours and the accident rate related to alcohol and other drugs among a sample of young people involved in nightlife.  A total of 440 young people from 3 Spanish Autonomous Communities took part. The sample size was estimated by means of Respondent Driven Sampling. The statistical analyses mined frequencies and measurements of the relationship of driving risk related behaviour in relation to the accident rate, number of cases of drunkenness, frequency of accidents during the past month, influence of gender and age, as well as the predictiveness of these variables as regards the accident rate.  A total of 50.2% of these young people had gotten into a vehicle with a driver who was drunk and/or under the influence of drugs, 23.2% has driven when drunk and 23.5% under the influence of drugs. The greater the degree of involvement in nightlife, the higher the frequency of drunkenness chi(2) (9)=112.24; p< .000 the greater the number of cases of drunkenness, the higher the frequency of these behaviors: getting into a vehicle with drivers who are drunk or under the influence of drugs c(2)=36,442, (3) p<0.001 drunken driving chi(2) =23,748, (3) p<0.001 and driving while under the influence of drugs chi(2)=23,816 (3) p<0.001 The regression analysis highlighted drunken driving (odds ratio=5.4) as the risk behaviour most related to traffic accidents.  There is a high incidence of risk behaviours while driving vehicles. Drunkenness, drug use and involvement in nightlife increase the frequency of these behaviours. Drunken driving was the best accident predictor.
Multi scale hierarchical neural network models that bridge from single neurons in the primate primary visual cortex to object recognition behavior
Year: 2021

Primate visual object recognition relies on the representations in cortical areas at the top of the ventral stream that are computed by a complex, hierarchical network of neural populations. While recent work has created reasonably accurate image computable hierarchical neural network models of those neural stages, those models do not yet bridge between the properties of individual neurons and the overall emergent behavior of the ventral stream. One reason we cannot yet do this is that individual artificial neurons in multi stage models have not been shown to be functionally similar to individual biological neurons. Here, we took an important first step by building and evaluating hundreds of hierarchical neural network models in how well their artificial single neurons approximate macaque primary visual cortical (V1) neurons. We found that single neurons in certain models are surprisingly similar to their biological counterparts and that the distributions of single neuron properties, such as those related to orientation and spatial frequency tuning, approximately match those in macaque V1. Critically, we observed that hierarchical models with V1 stages that better match macaque V1 at the single neuron level are also more aligned with human object recognition behavior. Finally, we show that an optimized classical neuroscientific model of V1 is more functionally similar to primate V1 than all of the tested multi stage models, suggesting room for further model improvements with tangible payoffs in closer alignment to human behavior. These results provide the first multi stage, multi scale models that allow our field to ask precisely how the specific properties of individual V1 neurons relate to recognition behavior. Highlights Image computable hierarchical neural network models can be naturally extended to create hierarchical "brain models" that allow direct comparison with biological neural networks at multiple scales from single neurons, to population of neurons, to behavior. Single neurons in some of these hierarchical brain models are functionally similar to single neurons in macaque primate visual cortex (V1) Some hierarchical brain models have processing stages in which the entire distribution of artificial neuron properties closely matches the biological distributions of those same properties in macaque V1 Hierarchical brain models whose V1 processing stages better match the macaque V1 stage also tend to be more aligned with human object recognition behavior at their output stage
The Effect of Network Characteristics on Online Identity Management Practices
Venue: J. Comput. Inf. Syst.
Year: 2017

As online social networking permeates all aspects of personal and professional lives, users of social networking sites (SNSs) are more motivated than ever to manage their online identities to project a favorable impression of themselves to online audiences. This research builds on the boundary management perspective to gain a better understanding of online identity management practices by examining the relationship between characteristics of the online social network, including cognitive homogeneity and social tie variety and the use of identity management practices such as segmentation and self enhancement. The proposed research model is tested using survey data. The findings suggest cognitive homogeneity is positively related to the use of both identity management practices, segmentation and self enhancement, whereas social tie variety is positively related to segmentation, but not self enhancement practices. We conclude with implications of the study results for research and practice, as well as a discussion of directions for future research.
Neural Symbolic Learning and Reasoning (Dagstuhl Seminar 14381)
Venue: Dagstuhl Reports
Year: 2014

This report documents the program and the outcomes of Dagstuhl Seminar 14381 "Neural Symbolic Learning and Reasoning" which was held from September 14th to 19th, 2014. This seminar brought together specialist in machine learning, knowledge representation and reasoning, computer vision and image understanding, natural language processing, and cognitive science. The aim of the seminar was to explore the interface among several fields that contribute to the effective integration of cognitive abilities such as learning, reasoning, vision and language understanding in intelligent and cognitive computational systems. The seminar consisted of contributed and invited talks, breakout and joint group discussion sessions.
Proprietes antibacteriennes des extraits des plantes medicinales comme conservateur naturel dans les aliments et de l'aquaculture O5
Year: 2013

L'antibioresistance est aujourd'hui un probleme de sante publique mondial. Le transfert a l'homme des bacteries resistantes ou de leurs genes de resistance via la chaine alimentaire et l'environnement constitue une des voies de propagation majeure de l'antibioresistance. Ainsi les aliments d'origine animale ou vegetale contamines par des bacteries pathogenes ou opportunistes resistantes aux antibiotiques (Escherichia coli, Campylobacter spp. Salmonella spp. Staphylococcus aureus etc) constituent un risque sanitaire important. En consequence, il est preconise de promouvoir l'utilisation raisonnee des antibiotiques dans les elevages et de developper des alternatives permettant de reduire leur pression de selection. A cet egard, les extraits de plantes sont generalement consideres comme une source riche en composes antimicrobiens qui ont ete largement etudies, et sur lesquels sont basees les medecines traditionnelles. Les interactions (synergie, antagonisme) entre differents extraits de plantes sont des facteurs importants a considerer dans la selection des composes actifs car ils determinent l'efficacite des traitements a base de plantes. Des exemples seront donnes a partir de nos recherches appliquees a l'aquaculture, sachant que ce secteur a connu une importante intensification au Vietnam, avec les problemes inherents a l'usage abusif des antibiotiques (residus, resistance) (Resume d'auteur)
Multiplex immunoassay for in vitro characterization of acellular pertussis antigens in combination vaccines.
Venue: Vaccine
Year: 2016

Vaccines characterization is required to ensure physical, chemical, and biological integrity of antigens and adjuvants. Current analytical methods mostly require complete antigen desorption from aluminum based adjuvants and are not always suitable to distinguish individual antigens in multivalent formulations. Here, Luminex technology is proposed to improve the analytics of vaccine characterization. As proof of concept, TdaP (tetanus, diphtheria and acellular pertussis) combination, adjuvanted with aluminum hydroxide, was chosen as model formulation to quantify and determine the level of adsorption of acellular pertussis (aP) antigens onto adjuvant surface at the same time. The assay used specific antibodies bound to magnetic microspheres presenting unique digital signatures for each pertussis antigen, allowing the simultaneous recognition of respective antigens in the whole vaccine, avoiding laborious procedures for adjuvant separation. Accurate and reproducible quantification of aP antigens in TdaP vaccine has been achieved in the range 0.78 50 ng/mL, providing simultaneously information on antigen identity, quantity, and degree of adsorption to aluminum hydroxide. The current study could further be considered as a model to set up in vitro potency assays thus supporting the replacement of animal tests accordingly to the 3Rs concept.
An Ensemble Approach for Credit Card Fraud Detection
Year: 2012

The most important moral issue in the credit card trade is fraud involvement. The main aspires are, primarily, to recognize the different types of credit card fraud, and, secondly, to evaluate unconventional techniques that have been used in fraud detection. The sub aim is to present, compare and examine recently published discovering in credit card fraud detection. Credit card fraud detection has developed a number of techniques via bunch of investigate interest and, with special importance on, data mining and distributed data mining have been recommended. In our existing research we proceeded with the semi hidden markov model (SHMM) where we got efficient result in credit card fraud detection. That is also having a larger class of practical problems that can be properly modeled in the setting of SHMM. Also major constraint is found, conversely, in mutually HMM and SHMM, i.e. it is generally imagined that there survives at least one observation connected with every state that the hidden Markov chain takes on. To improve the efficiency of SHMM in our proposed research we are combining the multiple observation of SHMM called Multiple Semi Hidden Markov Model (MSHMM) through this we can improve the detection accuracy better than the SHMM. Our suggested methods of combining multiple learned fraud detectors under a "cost model" are common and obviously useful; our experimental results make obvious that we can significantly reduce loss due to fraud through distributed data mining of fraud models.
Demand response potential of district heating and ventilation in an educational office building
Year: 2019

This study examines the influence of demand response control strategies on thermal conditions, indoor air CO2 concentration, and heating energy cost and consumption in an educational office building heated by a district heating system in a cold climate. The real time pricing based demand response is applied for space heating, heating of ventilation, and adjustment of airflow rates. The ventilation analysis covers both constant and variable air volumes systems. The applied demand response algorithms regulate room air temperature set points for space heating, temperature set point for supply air, and CO2 set point adjusted with the variable air volume ventilation system. The accepted room air temperature range was 20 24.5 degC and CO2 concentration within 800 1200 ppm. This study was conducted with the validated dynamic building simulation tool IDA ICE. The results illustrate that the maximum yearly savings by demand response of space heating and ventilation with the constant air volume ventilation system are around 3 and 6% for the heating energy consumption and heating energy cost, respectively. For the variable air volume system, the heating energy consumption, heating energy cost, electricity consumption, and electricity cost saved by demand response control can be up to 8, 11, 9, and 2% respectively.