nils-herrmann/clean_scirepeval huggingface dataset:
Lake heatwaves under climate change
Venue: Nature
Year: 2021

Lake ecosystems, and the organisms that live within them, are vulnerable to temperature change 1 5 including the increased occurrence of thermal extremes 6 However, very little is known about lake heatwaves periods of extreme warm lake surface water temperature and how they may change under global warming. Here we use satellite observations and a numerical model to investigate changes in lake heatwaves for hundreds of lakes worldwide from 1901 to 2099. We show that lake heatwaves will become hotter and longer by the end of the twenty first century. For the high greenhouse gas emission scenario (Representative Concentration Pathway (RCP) 8.5) the average intensity of lake heatwaves, defined relative to the historical period (1970 to 1999) will increase from 3.7 0.1 to 5.4 0.8 degrees Celsius and their average duration will increase dramatically from 7.7 0.4 to 95.5 35.3 days. In the low greenhouse gas emission RCP 2.6 scenario, heatwave intensity and duration will increase to 4.0 0.2 degrees Celsius and 27.0 7.6 days, respectively. Surface heatwaves are longer lasting but less intense in deeper lakes (up to 60 metres deep) than in shallower lakes during both historic and future periods. As lakes warm during the twenty first century 7 8 their heatwaves will begin to extend across multiple seasons, with some lakes reaching a permanent heatwave state. Lake heatwaves are likely to exacerbate the adverse effects of long term warming in lakes and exert widespread influence on their physical structure and chemical properties. Lake heatwaves could alter species composition by pushing aquatic species and ecosystems to the limits of their resilience. This in turn could threaten lake biodiversity 9 and the key ecological and economic benefits that lakes provide to society. Modelling and remote sensing show that by the end of the twenty first century, lake heatwaves will be several degrees Celsius warmer and some will be months longer, with potentially major adverse consequences for lake ecosystems.
Sequential line search for efficient visual design optimization by crowds
Venue: ACM Trans. Graph.
Year: 2017

Parameter tweaking is a common task in various design scenarios. For example, in color enhancement of photographs, designers tweak multiple parameters such as "brightness" and "contrast" to obtain the best visual impression. Adjusting one parameter is easy; however, if there are multiple correlated parameters, the task becomes much more complex, requiring many trials and a large cognitive load. To address this problem, we present a novel extension of Bayesian optimization techniques, where the system decomposes the entire parameter tweaking task into a sequence of one dimensional line search queries that are easy for human to perform by manipulating a single slider. In addition, we present a novel concept called crowd powered visual design optimizer, which queries crowd workers, and provide a working implementation of this concept. Our single slider manipulation microtask design for crowdsourcing accelerates the convergence of the optimization relative to existing comparison based microtask designs. We applied our framework to two different design domains: photo color enhancement and material BRDF design, and thereby showed its applicability to various design domains.
Non normalizable functions: A new method to generate metamorphic malware
Venue: 2011 MILCOM 2011 Military Communications Conference
Year: 2011

To successfully identify the metamorphic viruses oriented from the same base, anti virus software has adopted the code normalization technique to transform the variations to a more uniform signature representation. Current code normalization technique focuses on the simplification of the arithmetical or logical operators. In this paper, we introduce a new technique of generating metamorphic viruses by embedding complicated manipulation functions that cannot be normalized into the malicious executables. Using encryption/decryption functions as an example, we present this evasion strategy that malware writers could employ in the future. We demonstrate the strategy's effectiveness in evading detection by current anti virus technologies. We also discuss the potential mitigation mechanisms.
Online dictionary learning for sparse coding
Venue: ICML '09
Year: 2009

Sparse coding that is, modelling data vectors as sparse linear combinations of basis elements is widely used in machine learning, neuroscience, signal processing, and statistics. This paper focuses on learning the basis set, also called dictionary, to adapt it to specific data, an approach that has recently proven to be very effective for signal reconstruction and classification in the audio and image processing domains. This paper proposes a new online optimization algorithm for dictionary learning, based on stochastic approximations, which scales up gracefully to large datasets with millions of training samples. A proof of convergence is presented, along with experiments with natural images demonstrating that it leads to faster performance and better dictionaries than classical batch algorithms for both small and large datasets.
Turbo Aggregate: Breaking the Quadratic Aggregation Barrier in Secure Federated Learning
Venue: IEEE Journal on Selected Areas in Information Theory
Year: 2021

Federated learning is a distributed framework for training machine learning models over the data residing at mobile devices, while protecting the privacy of individual users. A major bottleneck in scaling federated learning to a large number of users is the overhead of secure model aggregation across many users. In particular, the overhead of the state of the art protocols for secure model aggregation grows quadratically with the number of users. In this article, we propose the first secure aggregation framework, named Turbo Aggregate, that in a network with <inline formula> <tex math notation="LaTeX"$N$ /tex math>/inline formula> users achieves a secure aggregation overhead of <inline formula> <tex math notation="LaTeX"$O(N\log {N} /tex math>/inline formula> as opposed to <inline formula> <tex math notation="LaTeX"$O(N^{2} /tex math>/inline formula> while tolerating up to a user dropout rate of 50% Turbo Aggregate employs a multi group circular strategy for efficient model aggregation, and leverages additive secret sharing and novel coding techniques for injecting aggregation redundancy in order to handle user dropouts while guaranteeing user privacy. We experimentally demonstrate that Turbo Aggregate achieves a total running time that grows almost linear in the number of users, and provides up to <inline formula> <tex math notation="LaTeX"$40\times /tex math>/inline formula> speedup over the state of the art protocols with up to <inline formula> <tex math notation="LaTeX"$N=200$ /tex math>/inline formula> users. Our experiments also demonstrate the impact of model size and bandwidth on the performance of Turbo Aggregate.
Beamforming design of decode and forward cooperation for improving wireless physical layer security
Venue: 2013 15th International Conference on Advanced Communications Technology (ICACT)
Year: 2013

Physical layer based security aims at ensuring the reliability of communication and preventing eavesdropping by taking advantage of the physical layer's characteristics rather than the data encryption in upper layer. Cooperation is a way to achieve this goal with many benefits for wireless communication. In particular, the cooperation scheme called decode and forward (DF) is discussed in this paper and our objective is to design the beamforming weight of each cooperating node which is one antenna equipped for maximum achievable secrecy rate. Considering that individual power constraint is more reasonable than total power constraint and to set noise power levels at the destination and the eavesdropper different is more practical than the same, we get the whole optimization problem which is unconvex. With the help of perfect global channel state information (CSI) the problem is solved through a way where convex optimization and one dimensional search are combined together. And strict proofs are presented for this method. Then zero forcing (ZF) based simplification and extension to cope with multi antenna case are discussed. Numerical results show that the proposed design can significantly improve the security performance of wireless systems.
RF Injection of THz QCL Combs at 80 K Emitting over 700 GHz Spectral Bandwidth
Year: 2020

We report about RF injection locking of an homogeneous THz quantum cascade laser operating at 3 THz central frequency. The extremely diagonal nature of the optical transition, combined with low loss copper based double metal waveguides, allow CW operation up to 105 K and CW power in excess of 5.6 mW measured at 80 K. Terahertz emission spanning up to 600 GHz, together with a narrow beatnote, indicate comb operation at 80 K, and strong RF injection clearly modifies the laser spectrum up to 700 GHz spectral bandwidth making these devices ideal candidates for an on chip dual comb spectrometer.
Red blood cells in retinal vascular disorders.
Venue: Blood cells, molecules diseases
Year: 2016

Microvascular circulation plays a vital role in regulating physiological functions, such as vascular resistance, and maintaining organ health. Pathologies such as hypertension, diabetes, or hematologic diseases affect the microcirculation posing a significant risk to human health. The retinal vasculature provides a unique window for non invasive visualisation of the human circulation in vivo and retinal vascular image analysis has been established to predict the development of both clinical and subclinical cardiovascular, metabolic, renal and retinal disease in epidemiologic studies. Blood viscosity which was otherwise thought to play a negligible role in determining blood flow based on Poiseuille's law up to the 1970s has now been shown to play an equally if not a more important role in controlling microcirculation and quantifying blood flow. Understanding the hemodynamics/rheology of the microcirculation and its changes in diseased states remains a challenging task; this is due to the particulate nature of blood, the mechanical properties of the cells (such as deformability and aggregability) and the complex architecture of the microvasculature. In our review, we have tried to postulate a possible role of red blood cell (RBC) biomechanical properties and laid down future framework for research related to hemorrheological aspects of blood in patients with retinal vascular disorders.
Trefoil factor(s) and CA19.9: A promising panel for early detection of pancreatic cancer
Venue: EBioMedicine
Year: 2019

Trefoil factors (TFF1, TFF2, and TFF3) are small secretory molecules that recently have gained significant attention in multiple studies as an integral component of pancreatic cancer (PC) subtype specific gene signature. Here, we comprehensively investigated the diagnostic potential of all the member of trefoil family, i.e. TFF1, TFF2, and TFF3 in combination with CA19.9 for detection of PC.  Trefoil factors (TFFs) gene expression was analyzed in publicly available cancer genome datasets, followed by assessment of their expression in genetically engineered spontaneous mouse model (GEM) of PC (KrasG12D; Pdx1 Cre (KC) and in human tissue microarray consisting of normal pancreas adjacent to tumor (NAT) precursor lesions (PanIN) and various pathological grades of PC by immunohistochemistry (IHC) Serum TFFs and CA19.9 levels were evaluated via ELISA in comprehensive sample set (n 362) comprised of independent training and validation sets each containing benign controls (BC) chronic pancreatitis (CP) and various stages of PC. Univariate and multivariate logistic regression and receiver operating characteristic curves (ROC) were used to examine their diagnostic potential both alone and in combination with CA19.9.  The publicly available datasets and expression analysis revealed significant increased expression of TFF1, TFF2, and TFF3 in human PanINs and PC tissues. Assessment of KC mouse model also suggested upregulated expression of TFFs in PanIN lesions and early stage of PC. In serum analyses studies, TFF1 and TFF2 were significantly elevated in early stages of PC in comparison to benign and CP control group while significant elevation in TFF3 levels were observed in CP group with no further elevation in its level in early stage PC group. In receiver operating curve (ROC) analyses, combination of TFFs with CA19.9 emerged as promising panel for discriminating early stage of PC (EPC) from BC (AUCTFF1+TFF2+TFF3+CA19.9 0.93) as well as CP (AUCTFF1+TFF2+TFF3+CA19.9 0.93) Notably, at 90% specificity (desired for blood based biomarker panel) TFFs combination improved CA19.9 sensitivity by 10% and 25% to differentiate EPC from BC and CP respectively. In an independent blinded validation set, the combination of TFFs and CA19.9 (AUCTFF1+TFF2+TFF3+CA19.9 0.82) also improved the overall efficacy of CA19.9 (AUCCA19.9 0.66) to differentiate EPC from CP proving unique biomarker capabilities of TFFs to distinguish early stage of this deadly lethal disease.  In silico, tissue and serum analyses validated significantly increased level of all TFFs in precursor lesions and early stages of PC. The combination of TFFs enhanced sensitivity and specificity of CA19.9 to discriminate early stage of PC from benign control and chronic pancreatitis groups.
Evaluation of the Prognostic Stage in the 8th Edition of the American Joint Committee on Cancer in Patients with Breast Cancer and Internal Mammary Lymph Node Metastasis
Venue: AntiCancer Research
Year: 2018

This study evaluated the prognostic value of the 8th edition of American Joint Committee on Cancer (AJCC) cancer staging system for patients with internal mammary lymph node (IMN) metastases.  Of the patients with breast cancer who were treated between 2009 and 2013, 66 were diagnosed as cN3b. We restaged the patients and analyzed the prognostic value of the prognostically staged groups.  With a median follow up of 53.9 months, the 5 year overall survival rates of patients with IIIA, IIIB, and IIIC stages were 100% 95% and 50% (p=0.001) while the progression free survival rates were 100% 83% and 50% (p=0.005)  Despite the small number of patients, the prognostic stage provided accurate information for IMN metastasized breast cancer, which will lead to more accurate prognosis predictions and optimal treatment selection.
Effect of Canopy Microclimate, Season and Region on Sauvignon blanc Grape Composition and Wine Quality
Year: 2017

The effect of canopy microclimate on the grape aroma composition and wine quality of Sauvignon blanc was investigated in three climatically different regions, i.e. in the Stellenbosch (1996 and 1997 season) Robertson and Elgin regions (1997 and 1998 season) A canopy shade treatment altering microclimate in a natural way, was applied to Sauvignon blanc vineyards in the three regions. Control vines were not manipulated. The concentrations of aroma compounds in the grapes, namely monoterpenes, Cu norisoprenoids and 2 methoxy 3 isobutylpyrazine, were determined weekly during the respective ripening periods. Solar radiation above and within the canopies as well as temperature within the canopies were also measured continually during the ripening periods. The highest canopy solar radiation, temperature, and monoterpene and C13 norisoprenoid concentrations were found for the control treatments, followed by the shaded treatments. An opposite tendency was found for 2 methoxy 3 isobutylpyrazine, which is one of the most important components responsible for the typical green pepper/asparagus aroma of Sauvignon blanc. There appears to be a relationship between chemical and microclimatic data in each region and over seasons. Marked temperature and aroma component concentration differences were observed among the three regions during the cool 1997 season, which manifested in wine aroma parameters such as fruitiness and vegetative/asparagus/green pepper nuances. Two definite wine styles emerged, namely the green pepper/asparagus "cool climate" style and the "warm climate" fruity/tropical style. However, differences in 2 methoxy 3 isobutylpyrazine and C13 norisoprenoid levels and wine characteristics between regions were not as pronounced during the warm 1998 season. The data contribute to establishing guidelines for canopy manipulation for obtaining a specific wine character and quality. The choice lies with the viticulturist and winemaker to strive for and obtain, within limits, the style that they prefer.
Deep neural network ensemble for pneumonia localization from a large scale chest x ray database
Venue: Comput. Electr. Eng.
Year: 2019

Pneumonia is a bacterial, viral, or fungal infection of one or both sides of the lungs that causes lung alveoli to fill up with fluid or pus, which is usually diagnosed with chest x rays. This work investigates opportunities for applying machine learning solutions for automated detection and localization of pneumonia on chest x ray images. We propose an ensemble of two convolutional neural networks, namely RetinaNet and Mask R CNN for pneumonia detection and localization. We validated our solution on a recently released dataset of 26,684 images from Kaggle Pneumonia Detection Challenge and were score among the top 3% of submitted solutions. With 0.793 recall, we developed a reliable solution for automated pneumonia diagnosis and validated it on the largest clinical database publicity available to date. Some of the challenging cases were additionally examined by a team of physicians, who helped us to interpret the obtained results and confirm their practical applicability.
Numerical study on the thermal buckling analysis of CNT reinforced composite plates with different shapes based on the higher order shear deformation theory
Year: 2019

In the present study, based on the higher order shear deformation plate theory, the unified numerical formulation is developed in variational framework to investigate the thermal buckling of different shapes of functionally graded carbon nanotube reinforced composite (FG CNTRC) plates. Since the thermal environment has considerable effects on the material properties of carbon nanotubes (CNTs) the temperature dependent (TD) thermo mechanical material properties are taken into account. In order to present the governing equations, the quadratic form of the energy functional of the plate structure is derived and its discretized counterparts are presented employing the variational differential quadrature (VDQ) approach. The discretized equations of motion are finally obtained based on Hamilton's principle. In order to convenient application of differential quadrature numerical operators in irregular physical domain, the mapping procedure is considered in accordance to the conventional finite element formulation. Some comparison and convergence studies are performed to show validity and efficiency of the proposed approach. A wide range of numerical results are also reported to analyze the thermal buckling behavior of different shaped FG CNTRC plates.
Target Driven Nanozyme Growth in TiO2 Nanochannels for Improving Selectivity in Electrochemical Biosensing.
Venue: Analytical chemistry
Year: 2020

Nanozymes have been used in colorimetric and electrochemical sensing because of their low cost and high stability. However, the wide applications of nanozymes in sensing devices are largely limited due to their poor selectivity. In this study, unlike traditional methods using prepared nanozymes for target detection, we designed a target driven nanozyme growth strategy in TiO2 na nochannels to detect analytes. Using telomerase as an example, the established recognition event was used to expand the photocata lytic activity of TiO2 to visible light region, thus triggering Prussian blue nanoparticle (PBNP) growth in visible light. Benefiting from the peroxidase (POD) like activity of PBNPs, the uncharged 3,5,3',5' tetramethylbenzidine (TMB) is oxidized to positively charged oxTMB, which induces significant ionic transport changes in nanochannels, and thus in turn provides information about telomerase activity. Such a nanozyme triggered sensing system exhibited excellent performance in telomerase detection in urine specimens from patients with bladder cancer. This innovative target driven signal generation strategy might provide a new method for applying nanozymes in developing sensitive, rapid, and accurate biological sensing systems.
Credibility in Online Social Networks: A Survey
Venue: IEEE Access
Year: 2019

The importance of information credibility in society cannot be underestimated given that it is at the heart of all decision making. Generally, more information is better; however, knowing the value of this information is essential for the decision making processes. Information credibility defines a measure of the fitness of the information for consumption. It can also be defined in terms of reliability, which denotes the probability that a data source will appear credible to the users. A challenge in this topic is that there is a great deal of literature that has developed different credibility dimensions. In addition, information science dealing with online social networks has grown in complexity, attracting interest from researchers in information science, psychology, human computer interaction, communication studies, and management studies, all of whom have studied the topic from different perspectives. This work will attempt to provide an overall review of the credibility assessment literature over the period 2006 2017 as applied to the context of the microblogging platform, Twitter. The known interpretations of credibility will be examined, particularly as they relate to the Twitter environment. In addition, we investigate levels of credibility assessment features. We then discuss recent works, addressing a new taxonomy of credibility analysis and assessment techniques. At last, a cross referencing of literature is performed while suggesting new topics for future studies of credibility assessment in a social media context.