nils-herrmann/clean_scirepeval huggingface dataset:
Fermented Foods: Fermented Vegetables and Other Products

Many fermented traditional plant based products are manufactured through lactic acid fermentation around the world, at both industrial and household levels. The suitability of vegetables and fruits for the manufacturing of innovative functional products has opened new perspectives. The axis 'fermented foods human health' is easily conceivable. Fermentation of plant material, as an industrialized and life science driven technology, may lead to significant changes in health promoting properties of foods. Understanding the relationship between food, beneficial microorganism, and health is important to improve human well being.
Evaluating recommendation systems for a sparse boolean dataset

Recommendation systems is an area within machine learning that has become increasingly relevant with the expansion of the daily usage of technology. The most popular approaches when making a recommendation system are collaborative filtering and content based. Collaborative filtering also contains two major sub approaches memory based and model based. This thesis will explore both content based and collaborative filtering to use as a recommendation system on a sparse boolean dataset. For the content based filtering approach term frequency inverse document frequency algorithm was implemented. As a memory based approach K nearest neighbours method was conducted. For the model based approach two different algorithms were implemented, singular value decomposition and alter least square. To evaluate, a cross approach evaluator was used by looking at the recommendations as a search, a search that the users were not aware of. Key values such as the number of test users who could received a recommendation, time consumption, F1 score (precision and recall) and the dataset size were used to compare the methods and reach conclusions. The finding of the study was that collaborative filtering was the most accurate choice when it comes to sparse datasets. The implemented algorithm for the model based collaborative filtering that performed most accurate was Singular value decomposition without any regularization against overfitting. A further step of this thesis would be to evaluate the different methods in an online environment with active users, giving feedback in real time.
Economic development, urban underemployment, and income inequality

The evolution of income inequality during the course of economic development is investigated. The source of inequality is market luck in obtaining employment in the protected urban 'formal sector' versus employment in the unprotected urban 'informal sector. It is shown that with development, inequality tends to follow an 'inverted u. It rises when urbanization is low and consequent pressure on the land keeps rural incomes low, making agents willing to incur high risks of 'underemployment' in the urban informal sector. It eventually falls after urbanization and consequently rural incomes have increased sufficiently to allow agents to make better than even bets in the urban industrial sector.
Long Term Trends in Economic Inequality: Lessons from Colonial Botswana, 1921 74

This article contributes to the growing literature on colonial legacies influencing long term development. It focuses on Botswana, a case where the post independence diamond led economy has been considered an economic success story, despite its high levels of inequality. Here it is argued that this pathway of rapid resource driven growth combined with increasing socio economic inequality had already started during the time of the colonial cattle economy, and that this older case is equally relevant for understanding long term growth inequality trends in Botswana and other natural resource dependent economies. Six social tables, covering the period 1921 to 1974, are constructed using colonial archives, government statistics, and anthropological records. Based on the social tables, income inequality is estimated in the colonial and early post independence eras, capturing both the formal and informal sectors of the economy. The article demonstrates how the creation of a cattle export sector in the 1930s brought new opportunities to access export incomes, and how this led to a polarization in cattle holdings and increasing income inequalities. Further, with the expansion of colonial administration, government wages forged ahead, increasing income inequality and causing a growing income divide between public and private formal employment.
Influence of Morphology on the Mechanical Properties of Polymer Nanocomposites Filled with Uniform or Patchy Nanoparticles.
Venue: Langmuir the ACS journal of surfaces and colloids

In this work we perform molecular dynamics simulations, both on the coarse grained and the chemistry specific levels, to study the influence of morphology on the mechanical properties of polymer nanocomposites (PNCs) filled with uniform spherical nanoparticles (which means without chemical modification) and patchy spherical nanoparticles (with discrete, attractive interaction sites at prescribed locations on the particle surface) Through the coarse grained model, the nonlinear decrease of the elastic modulus (G' and the maximum of the viscous modulus (G' around the shear strain of 10% is clearly reproduced. By turning to the polybutadiene model, we examine the effect of the shear amplitude and the interaction strength among uniform NPs on the aggregation kinetics. Interestingly, the change of the G' as a function of the aggregation time exhibited a maximum value at intermediate time attributed to the formation of a polymer bridged filler network in the case of strong interaction between NPs. By imposing a dynamic periodic shear, we probe the change of the G' as a function of the strain amplitude while varying the interaction strength between uniform NPs and its weight fraction. A continuous filler network is developed at a moderate shear amplitude, which is critically related to the interaction strength between NPs and the weight fraction of the fillers. In addition, we study the self assembly of the patchy NPs, which form the typical chain like and sheet like structures. For the first time, the effect of these self assembled structures on the viscoelastic and stress strain behavior of PNCs is compared. In general, in the coarse grained model we focus on the size effect of the rough NPs on the Payne effect, while some other parameters such as the dynamic shear flow, the interaction strength between NPs, the weight fraction, and the chemically heterogeneous surface of the NPs are explored for the chemistry specific model.
Online entertainment: A new wave of media globalization?

This article considers the phenomena of global online screen entertainment platforms in the context of enduring debates in communication and media studies concerning media globalization. While the relatively frictionless globality of such phenomena demands attention, we stress the differences between such platforms and the system of national broadcasting, film, and DVD release and licensing by windowing and territory. The latter, established forms of global media, enter territories with IP controlled content, whereas platforms such as YouTube exhibit facilitation rather than content control and much greater content, creator, service firm, and language and cultural diversity than traditional global media hegemons. The article introduces the Special Section and argues that we are witnessing the rise of a proto media industry that represents nontraditional media ownership, disruptive platforms, and unique content innovation that challenges our prior conceptions of media globalization, including national regulatory regimes.
Experimental result for SAR GMTI using monostatic pursuit mode of TerraSAR X and TanDEM X on Staring Spotlight images

TerraSAR X and TanDEM X is able to fly in monostatic pursuit mode, a formation with the satellites in identic orbit displaced in along track of a distance corresponding to 10 s delay. Such formation gives e.g. the ability to detect very slow targets or targets moving only between measurements. This can be performed using Change Detection (CD) and/or the Detection of Moving Targets by Focusing (DMTF) technique. A combination of DMTF and CD is promising. To investigate the applicability of the methods for moving target detection, an experiment was performed with TerraSAR X and TanDEM X in monostatic pursuit mode and several deployed targets.
Characterization of programmed cell death 1 ligand (PD L1) expression in circulating tumor cells (CTCs) of lung cancer

conclusively showed catheter position in the centre of SPN (26 cases) NIR spectroscopy probe based forceps were placed at the same place in order to gather tissue information. Mean measurement time was less than one minute after establishing ideal position. Results of spectroscopy measurements from NIR spectroscopy were obtained as differences between spectral characteristics of normal tissue (same side, different lobe) to SPN tissue.  The results are expressed as sensitivity of NIR spectroscopy towards EBUS navigated biopsies. Statistical analysis of the results showed very high sensitivity for NIR spectroscopy in confirmation of SPN tissue. From 26 EBUS positive visualisations of SPN there were 26 correct discriminations of SPN tissue, leading to 23 conclusive histological findings.  Every confirmatory method brings different information about tissue. EBUS describes volume of the SPN and gives valuable information about the position of catheter in the SPN. NIR spectroscopy brings information about biochemical/ optical characteristics of the tissues. Prototype of intelligent NIR based forceps showed good discriminative ability in the diagnosis of SPN.
Synthesis and applications of metal organic framework quantum dot (QD@MOF) composites

The combination of the high surface areas, microporosity and tuneable compositions of metal organic frameworks (MOFs) with the desirable photo physical behaviour of semiconductor nanoparticles or quantum dots (QDs) allows the preparation of composite materials with enhanced properties for applications in photocatalysis, energy, gas storage and sensing. These QD@MOF composites are an emergent class of materials and in this review we discuss current strategies for their synthesis, consider the semiconductor behaviour of MOFs themselves and present the applications of the various materials reported this far grouped by the nature of the QD component.
Sentiment Analysis of Twitter Data using NLTK in Python

In today's world, Social Networking website like Twitter, Facebook, Tumbler, etc. plays a very significant role. Twitter is a micro blogging platform which provides a tremendous amount of data which can be used for various applications of Sentiment Analysis like predictions, reviews, elections, marketing, etc. Sentiment Analysis is a process of extracting information from large amount of data, and classifies them into different classes called sentiments. Python is simple yet powerful, high level, interpreted and dynamic programming language, which is well known for its functionality of processing natural language data by using NLTK (Natural Language Toolkit) NLTK is a library of python, which provides a base for building programs and classification of data. NLTK also provide graphical demonstration for representing various results or trends and it also provide sample data to train and test various classifiers respectively. The goal of this thesis is to classify twitter data into sentiments (positive or negative) by using different supervised machine learning classifiers on data collected for different Indian political parties and to show which political party is performing best for public. We also concluded which classifier gives more accuracy during classification.
Deep vs. shallow networks An approximation theory perspective
Venue: ArXiv

The paper briefly reviews several recent results on hierarchical architectures for learning from examples, that may formally explain the conditions under which Deep Convolutional Neural Networks perform much better in function approximation problems than shallow, one hidden layer architectures. The paper announces new results for a non smooth activation function the ReLU function used in present day neural networks, as well as for the Gaussian networks. We propose a new definition of relative dimension to encapsulate different notions of sparsity of a function class that can possibly be exploited by deep networks but not by shallow ones to drastically reduce the complexity required for approximation and learning.
Ecosystem based adaptation in cities: An analysis of European urban climate adaptation plans

Ecosystem based adaptation (EbA) measures have been increasingly promoted in the literature, as well as in policies and practices, for their environmental and socio economic co benefits. The recent scientific literature has shown a growing interest to assess climate adaptation plans at the urban level, in recognition of the important role played by urban areas in addressing climate change challenges. However, little information is available on the combination of these two issues, i.e. the actual inclusion of EbA measures in climate adaptation plans at the urban level. This paper addresses this gap by developing a framework to analyze the treatment of EbA in urban level climate planning, and apply it to a sample of climate adaptation plans in Europe. The framework consists of a classification of EbA measures, and a scoring system to evaluate how well they are reflected in different components of the plans. The results suggest that there is in general good awareness in plans of EbA measures, and of their potential role in addressing climate change challenges. However, their treatment in climate adaptation plans at the urban level often lacks sufficient baseline information, as well as convincing implementation actions. The paper concludes by offering recommendations to improve future practice, in terms of enhancing the baseline information to improve the proposal and design of EbA measures, improving the treatment of co benefits associated to EbA measures, and strengthening coordination with other planning tools. Possible future development of this works include the integration of the proposed EbA classification, and the analysis of a larger sample of territorial plans.
Intracellularly Acid Switchable Multifunctional Micelles for Combinational Photo/Chemotherapy of the Drug Resistant Tumor.
Venue: ACS nano

The intrinsic or acquired drug resistance is the main challenge for cancer chemotherapy today. So far, many nanosized drug delivery systems (NDDS) have been exploited to combat cancer drug resistance. However, the therapy efficacy of current NDDS is severely impaired by the limited tumor penetration of the nanoparticles due to the existence of physiological and pathological barriers in the solid tumor. In this study, we report on the design and fabrication of intracellularly acid switchable multifunctional micelles for combinational photo and chemotherapy of the drug resistant tumor. The micelles were composed of a pH responsive diblock copolymer, a photosensitizer, and a polymeric prodrug of doxorubicin. The micelle displayed silenced fluorescence and photoactivity during the blood circulation and switched to an active state in weakly acid conditions (i.e. pH 6.2) in the endocytic vesicles to dramatically induce a 7.5 fold increase of the fluorescence signal for fluorescence imaging. Upon near infrared (NIR) laser irradiation, the micelle induced notable reactive oxygen species generation to trigger cytosol release of the chemotherapeutics and perform photodynamic therapy (PDT) Moreover, the micelle efficiently converted the NIR light to local heat for enhancing tumor penetration of the anticancer drug, tumor specific photothermal therapy, and photoacoustic (PA) imaging. Furthermore, the micelles could generate amplified magnetic resonance (MR) signal in an acidic microenvironment to perform MR imaging. Collectively, this study presents a robust nanoplatform for multimodal imaging and combinational therapy of the drug resistant tumor, which might provide an insight for developing polymer based NDDS for cancer therapy.
Photo Forensics

Photographs have been doctored since photography was invented. Dictators have erased people from photographs and from history. Politicians have manipulated photos for short term political gain. Altering photographs in the predigital era required time consuming darkroom work. Today, powerful and low cost digital technology makes it relatively easy to alter digital images, and the resulting fakes are difficult to detect. The field of photo forensics pioneered in Hany Farid's lab at Dartmouth College restores some trust to photography. In this book, Farid describes techniques that can be used to authenticate photos. He provides the intuition and background as well as the mathematical and algorithmic details needed to understand, implement, and utilize a variety of photo forensic techniques. Farid traces the entire imaging pipeline. He begins with the physics and geometry of the interaction of light with the physical world, proceeds through the way light passes through a camera lens, the conversion of light to pixel values in the electronic sensor, the packaging of the pixel values into a digital image file, and the pixel level artifacts introduced by photo editing software. Modeling the path of light during image creation reveals physical, geometric, and statistical regularities that are disrupted during the creation of a fake. Various forensic techniques exploit these irregularities to detect traces of tampering. A chapter of case studies examines the authenticity of viral video and famously questionable photographs including "Golden Eagle Snatches Kid" and the Lee Harvey Oswald backyard photo.
Graphene based Recyclable Photo Absorbers for High Efficiency Seawater Desalination.
Venue: ACS applied materials interfaces

Today's scientific advances in water desalination dramatically increase our ability to transform seawater into fresh water. As an important source of renewable energy, solar power holds great potential to drive the desalination of seawater. Previously, solar assisted evaporation systems usually relied on highly concentrated sunlight or were not suitable to treat seawater or wastewater, severely limiting the large scale application of solar evaporation technology. Thus, a new strategy is urgently required in order to overcome these problems. In this study, we developed a solar thermal evaporation system based on reduced graphene oxide (rGO) decorated with magnetic nanoparticles (MNPs) Because this material can absorb over 95% of sunlight, we achieved high evaporation efficiency up to 70% under only 1 kW m( 2) irradiation. Moreover, it could be separated from seawater under the action of magnetic force by decorated with MNPs. Thus, this system provides an advantage of recyclability, which can significantly reduce the material consumptions. Additionally, by using photoabsorbing bulk or layer materials, the deposition of solutes offen occurs in pores of materials during seawater desalination, leading to the decrease of efficiency. However, this problem can be easily solved by using MNPs, which suggests this system can be used in not only pure water system but also high salinity wastewater system. This study shows good prospects of graphene based materials for seawater desalination and high salinity wastewater treatment.
Encapsulating the delivery of affordable housing: An overview of Malaysian practice

Urban population increases much faster than other geographical areas and this brings huge challenges to Malaysian government especially those responsible for the provision of housing. Moreover, the rise of living cost and pressure towards the current economic situation had inevitably led to huge demands for affordable housing. Thus, affordability and inaccessibility of people in owning a house has become one of the major issues in Malaysia. These issues are not only faced by the low income group but mostly experienced by urban dwellers including the middle income group whom are not eligible to apply for low cost housing delivered by the government, yet cannot afford to buy a house. Hence, the Malaysian government had therefore established the Perumahan Rakyat 1 Malaysia (PR1MA) as the catalyst in providing adequate, quality and affordable houses. Furthermore, the Syarikat Perumahan Negara Berhad (SPNB) and the state governments also play their big role in providing affordable house at the state level. In trying to ensure smooth delivery of affordable housing, a systematic approach is required. This paper intends to examine the delivery of affordable housing in Malaysia. The objective was to assess the parties involved, and the various stages of the process. The methodology adopted for this study includes in depth interviews with affordable housing agencies. Investigation showed that the major problem relates to a mismatch in the delivery of affordable housing. Moreover, the political and economic aspects, as well as the organization situation had also influenced the inefficiency of affordable housing delivery system. Additionally, the significant of this paper is expected to formulate an improved strategy and guidance in delivery system, thus ensuring that the method of practice is applicable throughout the country.
The Determinant Of Carbon Emission Disclosures

Penelitian ini bertujuan untuk membuktikan pengaruh kinerja lingkungan, visibilitas organisasional, kondisi keuangan, dan mekanisme tata kelola terhadap pengungkapan emisi karbon di Indonesia. Pengungkapan emisi karbon diukur menggunakan checklist indeks Carbon Disclosure Project yang dikembangkan oleh Choi et al. (2013) Populasi dalam penelitian ini adalah perusahaan non keuangan yang terdaftar di Bursa Efek Indonesia tahun 2012 2014. Sampel dalam penelitian ini diambil menggunakan teknik purposive sampling. Terdapat 32 perusahaan setiap tahun. Metode analisis penelitian ini yaitu statistik deskriptif dan analisis regresi linear berganda. Hasil penelitian ini menunjukkan bahwa visibilitas organisasional, profitabilitas, kepemilikan manajerial, dan komite audit berpengaruh positif signifikan terhadap pengungkapan emisi karbon. Sementara itu, kinerja lingkungan, financial distress, kepemilikan institusional, dan proporsi komisaris independen tidak memiliki pengaruh yang signifikan terhadap pengungkapan emisi karbon. This study aimed to obtain empirical evidence about the influence of environmental performance, organizational visibility, financial condition, and corporate governance mechanism to extent of carbon emission disclosure in Indonesia. Carbon emission disclosure is measured by checklist Carbon Disclosure Project which developed by Choi et al. (2013) The population of this study was the company which listed in Indonesia Stock Exchange in 2012 2014. Sampel of this study was non financial company which listed in Indonesia Stock Exchange used purposive sampling method. There are 32 companies in every year. Analysis method which used in this study was descriptive statistic and multiple regression anaylsis. The result of this study showed that organizational visibility, profitability, managerial ownership and audit committee significantly influence to the extent of carbon emission disclosure. Meanwhile environmental performance, financial distress, institutional ownership and independence commissioner proportion had no significantly influence to the extent of emission disclosure.