nils-herrmann/clean_scirepeval huggingface dataset:
Bilateral Relations between Germany and Saudi Arabia: Military Political Dimension
Year: 2019

Germany is an example of power, which is consistently trying to increase its role in global politics, including more active part in the solution of a wide range of military political questions. At the same time Germany is facing the growing number of challenges for its own security, coming mostly from unstable Asian and African states. This makes Germany pay more attention on the Middle East in searching of new and strengthening traditional links with the regional partners. In this regard the article covers the dynamics, problems and perspectives of the bilateral interactions between Germany and Saudi Arabia in political military sphere during the 2010s. Traditionally Saudi Arabia was one of the key partners of the 'collective West' in the Middle East and has had rather good relations with Germany. The key research method used in the article is the event analysis. The research paper profoundly investigates the relations between Germany and Saudi Arabia during the first half of the 2010s. The article stresses the mutual interest in expanding and deepening cooperation in the context of the "Arab awakening" including the solution of the Syrian problem. The key focus is paid to the growing discrepancies in positions of two parts regarding the Yemen conflict resolution in the context of confrontation between Saudi Arabia and Iran. The article also describes the dynamics of negotiations between Germany and Saudi Arabia on the highest and high levels in the middle 2010s. The paper points out the growing recession periods in German Saudi relations in 2016 2017 (taken into account the execution of Shiite preachers in KSA; Qatar diplomatic crises and the assassination of J. Khashoggi) After the signature and implementation of the Iranian 'nuclear deal' Germany has been increasingly inclined towards the tactics of "balancing" between Iran and Saudi Arabia. And in this regard has emphasized the unacceptability of a direct military conflict between them. After Trump's administration withdrawal from Iranian nuclear deal the article stresses the tougher German pressure on Saudi Arabia both in militarytechnical cooperation and political spheres in order to assure the withdrawal of Saudi Arabian military forces from Yemen. In the conclusion the author specifies the politicization of the bilateral military technical cooperation and the sharp increase of the influence of Iranian factor over the German Saudi relations. Three scenarios of future development of the confrontation between two states are proposed. Depending on each of them, the prospects for the development of German Saudi relations are defined.
Building Information Modeling and Integrated Project Delivery: What is the future?
Year: 2011

The current state of practice in Building Information Modeling (BIM) has made significant progress over the last decade in integrating the design and construction processes. Current contractual relationships such as Integrated Project Delivery (IPD) arrangements are also making inroads into a more integrated process of combining design and instruction. However, both developments are still in a state of infancy. This paper explores best practices through a current analysis of the state of practice in integrating design and construction through BIM and new contractual arrangements as well as the current limitations to functional integration. The referred limitation comprises an analysis of how aspects such as sustainable/green construction and conservation design can be better integrated into BIM, including lean construction to maximize value reduce waste. This paper explores this process, chiefly addressing issues of liability, particularly as such models gain greater usage by the Owner during the operational and maintenance phases of a facility. It concludes with possible avenues that the construction industry needs to explore in the greater strategic integration of design and construction.
Effect of herbal feed additives on performance parameters, intestinal microbiota, intestinal morphology and meat lipid oxidation of broiler chickens
Venue: British poultry science
Year: 2018

This feeding trial investigated the effects of herbal feed additives on performance of broiler chickens, jejunal and caecal microbiota, jejunal morphology, meat chemical composition and oxidative stability during refrigerated storage. 2. In a 42 days trial, 320 one day old broiler chickens were randomly allocated to 4 groups with 4 replicate pens each containing 20 chicks. The control group was fed maize soybean based diets. The diets of the other three groups were supplemented with herbal feed additives: HRB1 with StresomixTM (0.5 g/kg feed) HRB2 with AyuceeTM (1.0 g/kg feed) HRB3 with Salcochek ProTM (1.0 g/kg feed) The GC/MS analysis of the feed additives showed that the major components of HRB1 were b caryophyllene (14.4% and menthol (9.8% HRB2 were n hexadecanoic acid (14.22% and b caryophyllene (14.4% and HRB3 were menthol (69.6% and clavicol methyl ether (13.9% 3. Intestinal samples were taken at 42 day to determine bacterial populations (total aerobe counts, Lactobacilli, and Escherichia coli) and perform gut morphology analysis. Meat samples were analysed for chemical composition and oxidative stability under storage. 4. The HRB1 group had improved (P 0.05) body weight gain and tended to have improved (0.05 P 0.10) feed conversion ratio, compared to the control group. Jejunum lactic acid bacteria counts were increased (P 0.001) in groups HRB1 and HRB3, compared to the control group, whereas caecal lactic acid bacteria counts tended to increase (0.05 P 0.10) in group HRB1, compared to the control group. Breast meat fat content tended to be lower (0.05 P 0.10) in group HRB1. Meat oxidative stability was improved (P 0.001) and jejunum villus height, crypt depth and goblet cells numbers were increased (P 0.001) in all three herbal supplemented groups, compared to the control. 5. In conclusion, herbal feed additives may be able to improve both growth performance and antioxidant activity of broiler chickens, based on their phenolic compound content.
The Proposed Development of Prototype with Secret Messages Model in Whatsapp Chat
Year: 2018

Development of prototype at data security through secret messages is needed for disguising the messages sent in smartphone chatting application, WhatsApp (WA) Chat. We propose a model to disguise a plaintext message which is first encrypted by cryptosystem to change the plaintext message to ciphertext. Plaintext or plainimage entering the smartphone system is changed into encrypted text; receiver then can read the message by using similar key with the sender. The weakness of this proposal is the message random system is not planted directly in the chatting application; therefore message removing process from cryptosystem to WA application is still needed. The strength of using this model is the messages sent will not be easily re encrypted by hacker and can be used at client computing section.
Perceived Risk, Product Returns, and Optimal Resource Allocation: Evidence from a Field Experiment
Year: 2015

Relatively few retailers include metrics such as product returns in their customer selection and optimal resource allocation algorithms when measuring and maximizing customer value. Even when they do include this metric, increases in product return behavior are usually considered merely an economic cost that must be managed by decreasing the marketing resource allocations toward the customers making the returns. However, recent research has suggested that satisfactory product return experiences can actually benefit firms by lowering the customer's perceived risk of current and future purchases. To better understand the role of this perceived risk in the firm customer exchange process, the authors conduct a large scale customer selection and optimal resource allocation field experiment with 26,000 customers from an online retailer over six months. They find that the firm is able to increase both its short and long term profits when accounting for the perceived risk related to product returns in addition to managing product return costs. Furthermore, the authors find that by including this risk, rather than simply implementing traditional customer lifetime value based models generically, the firm can target more profitable customers.
Qualitative, quantitative screening and antifungal study of Pittosporum floribundum Wight Arn.
Year: 2019

Pittosporum floribundum is an ethnomedicinal plant which has a numerous number of medicinal claims and it hasn't been explored thoroughly. Various parts of plant used medicinally such as used in skin disorder, leprosy, etc.  To explore different qualitative, quantitative and antifungal aspect of Pittosporum floribundum.  Different test were carried out to determine qualitative as well as quantitative parameter such as for the presence of protein, glycosides, alkaloids, carbohydrates, terpenoids, etc.  The three extracts were taken for examination such as water, methanolic and hydroalcoholic. The study was carried out on Pittosporum bark and leaves and for every sample three extract were prepared. And every extract shows different results. Also, study reveals Pittosporum floribundum shows antifungal activity.  The Pittosporum floribundum plant extracts could be used as an antifungal after comprehensive in vitro biological studies.
The Influence of Government Size, Audit Opinion and Incumbent on Audit Delay in the Provincial Government in Indonesia
Year: 2019

Financial statements that were not provided on time may cause those report loses their capacity to influence decisions. This study aims to examine the effects of government size, audit opinion, incumbent on audit delay in Indonesia. This study used 165 financial reports from 33 provincial government in Indonesia from 2012 to 2016. Research data was obtained from the financial audit agency and directorate general of financial balance. The dependent variable of this research is audit delay. While the independent variables include the size of government, audit opinon, dan incumbent. Multiple regression analysis was used to test the hypothesis. The test results show that audit opinion has a significant effect on audit delay. But size of government and incumbent does not have a significant effect on audit delay.
Inside Out: From Basic Emotions Theory to the Behavioral Ecology View
Year: 2019

Basic emotions theory (BET) is the most popular and deeply rooted psychological theory of both emotion and the facial behavior held to express it. We review its Western foundations and the key developments in its evolution, focusing on its parsing of facial expressions into two kinds: biological, categorical, iconic, universal "facial expressions of emotion," versus modified, culturally diverse versions of those iconic expressions due to intermediation by learned "display rules." We suggest that this dichotomy and its many corollaries are oversimplified, and that many of BET's recent modifications are inconsistent in ways that may render it impossible to test and immune to falsification. In contrast, we suggest that the behavioral ecology view of facial displays, as an externalist and functionalist approach, resolves the quandaries and contradictions embedded in BET's precepts and extensions.
Omidubicel Versus Standard Myeloablative Umbilical Cord Blood Transplantation: Results of a Phase III Randomized Study.
Venue: Blood
Year: 2021

Omidubicel is an ex vivo expanded hematopoietic progenitor cell, and non expanded myeloid and lymphoid cell product derived from a single umbilical cord blood unit. We report results of a phase III trial to evaluate the efficacy of omidubicel compared to standard umbilical cord blood transplantation (UCBT) Between January 2017 and January 2020, 125 patients aged 13 65 with hematologic malignancies were randomized to omidubicel versus standard UCBT. Patients received myeloablative conditioning and graft versus host disease (GvHD) prophylaxis with a calcineurin inhibitor and mycophenolate mofetil. The primary endpoint was time to neutrophil engraftment. The treatment arms were well balanced and racially diverse. Median time to neutrophil engraftment was 12 days (95% CI 10 14 days) and 22 days (95% CI 19 25 days) (p<0.001) for the omidubicel and control arms, respectively. The cumulative incidence of neutrophil engraftment was 96% and 89% for patients receiving omidubicel and control transplants, respectively. The omidubicel arm had faster platelet recovery (55% vs. 35% recovery by 42 days, p=0.028) a lower incidence of first grade 2/3 bacterial or invasive fungal infections (37% vs. 57% p=0.027) and spent more time out of hospital during the first 100 days following transplant (median 61 vs. 48 days, p=0.005) than controls. Differences in GvHD and survival between the two arms were not statistically significant. Transplantation with omidubicel results in faster hematopoietic recovery and reduced early transplant related complications as compared to standard UCBT. The results suggest that omidubicel may be considered as a new standard of care for adult patients eligible for UCBT.
Studi Aspek Afektif pada Kompetensi Inti dan Kompetensi Dasar Mata Pelajaran Aqidah Akhlak
Year: 2020

Mohammad Nuh (Menteri Pendidikan periode 2009 2014) mengatakan bahwa kurikulum 2013 menitikberatkan pada pengembangan aspek sikap (afektif) peserta didik. Untuk membuktikan kebenaran, ketepatan dan keabsahan titik berat tersebut, maka harus dilakukan analisis dengan teori afektif dalam pendidikan yang dikembangkan oleh Krathwohl. Tujuan penelitian ini adalah untuk menganalisa wujud dan bukti aspek afektif yang terdapat pada Kompetensi Inti dan Kompetensi Dasar pada mata pelajaran Akidah Akhlak Madrasah Ibtidaiyah dari kelas I sampai kelas VI. Penelitian ini masuk pada penelitian pustaka yang bersifat deskriptif analitik yang disajikan berbentuk uraian temuan dengan menggunakan teori pendidikan afeksi, kemudian dilanjutkan dengan penarikan sebuah kesimpulan. Hasil penelitian menunjukan bahwa di dalam bunyi bunyi Kompetensi Inti dan Kompetensi Dasar terdapat wujud aspek afektif dengan berbagai tingkatan. Dari yang paling dasar sampai tingkat yang paling tinggi receiving, responding, valuing, organization, dan characterization
Bacteria Use Collective Behavior to Generate Diverse Combat Strategies
Venue: Current Biology
Year: 2018

Animals have evolved a wide diversity of aggressive behavior often based upon the careful monitoring of other individuals. Bacteria are also capable of aggression, with many species using toxins to kill or inhibit their competitors. Like animals, bacteria also have systems to monitor others during antagonistic encounters, but how this translates into behavior remains poorly understood. Here, we use colonies of Escherichia coli carrying colicin encoding plasmids as a model for studying antagonistic behavior. We show that in the absence of threat, dispersed cells with low reproductive value produce colicin toxins spontaneously, generating efficient pre emptive attacks. Cells can also respond conditionally to toxins released by clonemates via autoinduction or other genotypes via competition sensing. The strength of both pre emptive and responsive attacks varies widely between strains. We demonstrate that this variability occurs easily through mutation by rationally engineering strains to recapitulate the diversity in naturally occurring strategies. Finally, we discover that strains that can detect both competitors and clonemates are capable of massive coordinated attacks on competing colonies. This collective behavior protects established colonies from competitors, mirroring the evolution of alarm calling in the animal world.
Federated Deep Learning Architecture for Personalized Healthcare
Venue: MIE
Year: 2021

Using deep learning to advance personalized healthcare requires data about patients to be collected and aggregated from disparate sources that often span institutions and geographies. Researchers regularly come face to face with legitimate security and privacy policies that constrain access to these data. In this work, we present a vision for privacy preserving federated neural network architectures that permit data to remain at a custodian's institution while enabling the data to be discovered and used in neural network modeling. Using a diabetes dataset, we demonstrate that accuracy and processing efficiencies using federated deep learning architectures are equivalent to the models built on centralized datasets.
Deep features and One class classification with unsupervised data for weed detection in UAV images
Venue: 2019 Ninth International Conference on Image Processing Theory, Tools and Applications (IPTA)
Year: 2019

With the raise of the world population, increasing agricultural productivity has become a necessity for farmers. One way to reduce the cost of chemicals and environmental impact is to allocate the right doses of herbicide to the right place and at the right time (precision agriculture) Nowadays, automatic weeds detection is one of the most challenging problem for precision agriculture. However, weeds and crop are hard to discriminate because of their strong similarities. One of the approaches used for weed detection is machine learning. The main common point between machine learning algorithms is the need of training data. In this article we propose to use deep features and one class classification on unsupervised data for weed detection in UAV images. The results show that one class classification can be comparable to the literature and also to a deep learning model trained with supervised training data labeling. Results obtained on all test datasets can be up to 90% depending on the data used for the training.
Hope, self efficacy, optimism, and academic achievement: Distinguishing constructs and levels of specificity in predicting college grade point average
Year: 2015

Research shows that Snyder's (1994) goal directed hope construct predicts college GPA. However, studies have documented relatively weak relationships between these variables, possibly because hope was measured regarding goals generally not academic specific goals. Additionally, most studies have not compared variance accounted for in GPA by hope relative to other expectancy constructs. In a cross sectional sample of 89 college students, we administer the Hope Scale, Domain Specific Hope Scale (academic subscale) General Self Efficacy Scale, Academic Self Efficacy Scale, Life Orientation Test Revised (optimism) among others. We test a path analytic model where academic specific expectancies (e.g. academic hope, academic self efficacy) have direct paths to GPA, and generalized expectancies (e.g. general hope, general self efficacy) have paths to these academic specific variables.  Optimism and general self efficacy did not predict academic specific expectancy variables nor GPA.
Lifelong Machine Learning and root cause analysis for large scale cancer patient data
Venue: Journal of Big Data
Year: 2019

IntroductionThis paper presents a lifelong learning framework which constantly adapts with changing data patterns over time through incremental learning approach. In many big data systems, iterative re training high dimensional data from scratch is computationally infeasible since constant data stream ingestion on top of a historical data pool increases the training time exponentially. Therefore, the need arises on how to retain past learning and fast update the model incrementally based on the new data. Also, the current machine learning approaches do the model prediction without providing a comprehensive root cause analysis. To resolve these limitations, our framework lays foundations on an ensemble process between stream data with historical batch data for an incremental lifelong learning (LML) model.Case descriptionA cancer patient's pathological tests like blood, DNA, urine or tissue analysis provide a unique signature based on the DNA combinations. Our analysis allows personalized and targeted medications and achieves a therapeutic response. Model is evaluated through data from The National Cancer Institute's Genomic Data Commons unified data repository. The aim is to prescribe personalized medicine based on the thousands of genotype and phenotype parameters for each patient.Discussion and evaluationThe model uses a dimension reduction method to reduce training time at an online sliding window setting. We identify the Gleason score as a determining factor for cancer possibility and substantiate our claim through Lilliefors and Kolmogorov Smirnov test. We present clustering and Random Decision Forest results. The model's prediction accuracy is compared with standard machine learning algorithms for numeric and categorical fields.ConclusionWe propose an ensemble framework of stream and batch data for incremental lifelong learning. The framework successively applies first streaming clustering technique and then Random Decision Forest Regressor/Classifier to isolate anomalous patient data and provides reasoning through root cause analysis by feature correlations with an aim to improve the overall survival rate. While the stream clustering technique creates groups of patient profiles, RDF further drills down into each group for comparison and reasoning for useful actionable insights. The proposed MALA architecture retains the past learned knowledge and transfer to future learning and iteratively becomes more knowledgeable over time.
Cross media analysis and reasoning: advances and directions
Venue: Frontiers of Information Technology Electronic Engineering
Year: 2017

Cross media analysis and reasoning is an active research area in computer science, and a promising direction for artificial intelligence. However, to the best of our knowledge, no existing work has summarized the state of the art methods for cross media analysis and reasoning or presented advances, challenges, and future directions for the field. To address these issues, we provide an overview as follows: (1) theory and model for cross media uniform representation; (2) cross media correlation understanding and deep mining; (3) cross media knowledge graph construction and learning methodologies; (4) cross media knowledge evolution and reasoning; (5) cross media description and generation; (6) cross media intelligent engines; and (7) cross media intelligent applications. By presenting approaches, advances, and future directions in cross media analysis and reasoning, our goal is not only to draw more attention to the state of the art advances in the field, but also to provide technical insights by discussing the challenges and research directions in these areas.
Broad Discourse Context for Language Modeling
Year: 2017

Recurrent neural network language models (RNNLM) have become a key element for state of the art language modeling and are integral parts in a wide range of applications such as speech recognition or information retrieval systems. However, recent work has shown that the extent to which these models truly understand language remains unclear. In particular, the LAMBADA dataset consists of a collection of hard word prediction examples specifically designed to test language models' capabilities to keep track of information in the broader discourse. In this thesis we delve into the nature of LAMBADA and highlight the impact that rare words have on the overall results. We introduce our proposed model, the Softmax Mixture, and showcase through a series of experiments its ability to handle rare words when compared to vanilla RNNLMs. We further implement the Pointer Sentinel Mixture model and demonstrate that it achieves perplexities on par with the state ofthe art on LAMBADA while having superior adaptation capabilities.