Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of two principal approaches to objective image quality assessment

Nowadays, it is evident that we must consider human perceptual properties to visualize information clearly and efficiently. We may utilize computational models of human visual systems to consider human perception well. Image quality assessment is a challenging task that is traditionally approached by such computational models. Recently, a new assessment methodology based on structural similarity has been proposed. We select two representative models of each group, the visible differences predictor and the structural similarity index, for evaluation. We begin with the description of these two approaches and models. We then depict the subjective tests that we have conducted to obtain mean opinion scores. Inputs to these tests included uniformly compressed images and images compressed non-uniformly with regions of interest. Then, we discuss the performance of the two models, and the similarities and differences between the two models. We end with a summary of the important advantages of each approach.
A contribution to the characterization of the interference power in cognitive radio networks

In future cognitive radio networks, radio devices will observe by sensing to detect non-occupied bandwidth and interferences. The result of this observation process will then be used by the cognitive manager to adapt the transmitter to its environment, at all layers. The quality of the observation process is thus of primary importance. In this paper, we are interested in the statistical characterization of the power sensed by a radio node in the presence of multiple interferers when path-loss, shadowing and fast fading effects are taken into consideration. In this context, we develop a method that provides a very good approximation of the probability density function of this interference power, for a given localization of the interferers. In comparison with classical approaches that in general take into account path-loss and Rayleigh fading only, the proposed characterization also includes shadowing effects. Moreover, in addition to providing a better comprehension of the interference phenomenon when all propagation effects are included, the proposed model facilitates simulations compared to the classical Monte Carlo approach.
Impact of Breast Cancer Resistance Protein Expression on the In Vitro Efficacy of Anticancer Drugs in Pancreatic Cancer Cell Lines

Breast cancer resistance protein (BCRP) overexpression confers multidrug resistance to cancer cells, and the efficacy of anticancer drugs has been reported to be significantly affected by BCRP in cell lines transfected with BCRP or selected with drugs. It is unclear whether the in vitro efficacy of anticancer drugs is affected by endogenous BCRP, although cancer cell line panels consisting of defined tumor cell lines with endogenous BCRP have been used to screen for anticancer drugs in the pharmaceutical industry. We assessed the impact of BCRP expression on efficacy of anticancer drugs using pancreatic cancer cell lines expressing varying levels of endogenous BCRP. Pancreatic cancer cell lines were selected from the Cancer Cell Line Encyclopedia (CCLE). The EC50 of 7-ethyl-10-hydroxycamptothecin (SN-38), topotecan, and mitoxantrone decreased in the presence of a BCRP inhibitor in PANC-1 and AsPC-1 cells, which exhibit high BCRP expression. However, no significant alterations in EC50 were observed in HPAF-II, SW 1990, and MIA PaCa-2, which show moderate or low BCRP expression. The shift of EC50 of anticancer drugs with and without a BCRP inhibitor increased with an increase of BCRP mRNA expression levels; however, the shift was obvious only in cells highly expressing BCRP. Thus, the in vitro efficacy of anticancer drugs on cell proliferation may be minimally affected by BCRP in most pancreatic cancer cell lines, considering that 72% of pancreatic cancer cell lines in CCLE show moderate or low BCRP expression. The effect of BCRP should be carefully evaluated in pancreatic cell lines that highly express BCRP.
Attribute-Based Encryption for a Subclass of Circuits with Bounded Depth from Lattices

In this work, we present two Key-Policy Attribute-Based Encryption (ABE) schemes for some subclass of circuits based on the Learning with Error (LWE) assumption. Our constructions are selectively secure in the standard model. More specifically, our first construction supports a subclass of circuits with polynomially bounded depth. We call this subclass the OR-restricted circuits which means that for any input x, if f(x) = 0 then for all the OR gates in f , at least one of its incoming wires will evaluate to 0. The second one is a Key-Policy ABE scheme for shallow circuits whose depth is bounded by O(log log λ), where λ is the security parameter.
Meal Detection in Patients With Type 1 Diabetes: A New Module for the Multivariable Adaptive Artificial Pancreas Control System

A novel meal-detection algorithm is developed based on continuous glucose measurements. Bergman's minimal model is modified and used in an unscented Kalman filter for state estimations. The estimated rate of appearance of glucose is used for meal detection. Data from nine subjects are used to assess the performance of the algorithm. The results indicate that the proposed algorithm works successfully with high accuracy. The average change in glucose levels between the meals and the detection points is 16(±9.42) [mg/dl] for 61 successfully detected meals and snacks. The algorithm is developed as a new module of an integrated multivariable adaptive artificial pancreas control system. Meal detection with the proposed method is used to administer insulin boluses and prevent most of postprandial hyperglycemia without any manual meal announcements. A novel meal bolus calculation method is proposed and tested with the UVA/Padova simulator. The results indicate significant reduction in hyperglycemia.
AI and Agents: State of the Art

This article is a reflection on agent-based AI. My contention is that AI research should focus on interactive, autonomous systems, that is, agents. Emergent technologies demand so. We see how recent developments in (multi-) agent-oriented research have taken us closer to the original AI goal, namely, to build intelligent systems of general competence. Agents are not the panacea though. I point out several areas such as design description, implementation, reusability, and security that must be developed before agents are universally accepted as the AI of the future.
CLSR: Cognitive Link State Routing for CR-based Tactical Ad Hoc Networks

The Cognitive Radio (CR) paradigm in tactical ad hoc networks is an important element of future military communications for network-centric warfare. This paper presents a novel Cognitive Link State Routing protocol for CR-based tactical ad hoc networks. The proposed scheme provides prompt and reliable routes for Primary User (PU) activity through procedures that incorporate two main functions: PU-aware power adaptation and channel switching. For the PU-aware power adaptation, closer multipoint relay nodes are selected to prevent network partition and ensure successful PU communication. The PU-aware channel switching is proactively conducted using control messages to switch to a new available channel based on a common channel list. Our simulation study based on the ns-3 simulator demonstrates that the proposed routing scheme delivers significantly improved performance in terms of average end-to-end delay, jitter, and packet delivery ratio.
Contextual recommendations using intention mining on process traces: Doctoral consortium paper

Nowadays, digital traces are omnipresent in Information System (IS). Companies track IS interactions to retrieve and compile information about actors. Researchers of various streams, within IT and beyond, focused on recording actor interactions with systems and the technical possibilities to identify record and store these interactions. Tracing functionality has appeared in almost all common computer applications. This PhD project will focus on the establishment of a trace-based system and propose recommendations to actors regarding to their context. The objective of this thesis is to study process traces to propose recommendations to the actors by identifying a set of generic processes adaptable to the current actors' context. Thus, any actor, expert or novice, will be able to use this knowledge that gives contextual clues to identify the potential steps he could perform.
Anti-Human Rhinoviral Activity of Polybromocatechol Compounds Isolated from the Rhodophyta, Neorhodomela aculeata

An extract of the red alga, Neorhodomela aculeata, exhibited antiviral activity against human rhinoviruses. Bioassay-guided purification was performed to yield six compounds, which were subsequently identified as lanosol (1) and five polybromocatechols (2–6) by spectroscopic methods, including 1D and 2D NMR and mass spectrometric analyses. Structurally, all of these compounds, except compound 5, contain one or two 2,3-dibromo-4,5-dihydroxyphenyl moieties. In a biological activity assay, compound 1 was found to possess antiviral activity with a 50% inhibitory concentration (IC50) of 2.50 μg/mL against HRV2. Compound 3 showed anti-HRV2 activity, with an IC50 of 7.11 μg/mL, and anti-HRV3 activity, with an IC50 of 4.69 μg/mL, without demonstrable cytotoxicity at a concentration of 20 μg/mL. Collectively, the results suggest that compounds 1 and 3 are candidates for novel therapeutics against two different groups of human rhinovirus.
Supervised Vector Angle Embedding Learning for Face Recognition

Based on constructing neighborhood graphs, a method called supervised vector angle embedding (SVAE)was presented for face recognition. A graph including both positive edges and negative edges was constructed. It put a positive edge on two samples in the same class and a negative edge on two different class samples within k nearest neighbor each other. The measure in SVAE was the angle between two vectors instead of modulus in traditional methods. It does not require the estimation of the parameter in heat weight function, and can reduce the influence of luminance on face recognition. When test sample was embedded into low-dimensional space with preserving neighborhood vector angle, a classification called angle nearest neighbor was used for face recognition. Experiments on Yale and UMIST databases demonstrated the proposed approach was superior to other methods in terms of recognition accuracy.
Untrimmed Video Classification for Activity Detection: submission to ActivityNet Challenge

Current state-of-the-art human activity recognition is focused on the classification of temporally trimmed videos in which only one action occurs per frame. We propose a simple, yet effective, method for the temporal detection of activities in temporally untrimmed videos with the help of untrimmed classification. Firstly, our model predicts the top k labels for each untrimmed video by analysing global video-level features. Secondly, frame-level binary classification is combined with dynamic programming to generate the temporally trimmed activity proposals. Finally, each proposal is assigned a label based on the global label, and scored with the score of the temporal activity proposal and the global score. Ultimately, we show that untrimmed video classification models can be used as stepping stone for temporal detection.
Estimation of energy intake to feed subjects at energy balance as verified with doubly labelled water: a study in the elderly.

A study was intended to estimate energy intake (EI) for a nutrition intervention study. Subjects were 17 elderly men (age: 72 +/- 5 years) and 11 elderly women (age: 67 +/- 4 years). Two methods were used to measure EI: a 4-day dietary record (DR group; n = 12) or a dietary questionnaire (DQ group; n = 16). Subjects were fed for 3 weeks according to this intake during an intervention period, and energy expenditure (EE) was measured with doubly labelled water to verify the resulting figure for EI. Body weight and body composition were measured at the beginning of the second week and at the end of the third week, and metabolizable energy (ME) was calculated as gross energy intake (GEI) minus energy in faeces and urine. GEI, ME and EE did not differ between the DR and DQ groups (mean +/- SD for GEI: 10.09 +/- 1.21 and 9.29 +/- 1.36; ME: 9.09 +/- 1.28 and 8.34 +/- 1.31; EE: 10.13 +/- 1.57 and 9.25 +/- 0.35 MJ/d). In both groups ME was significantly lower than EE (DR group P < 0.05; DQ group P < 0.01). Body weight decreased significantly during the intervention period (mean +/- SD for DR group: -0.64 +/- 0.50 kg, P < 0.001; DQ group: -0.86 +/- 0.90 kg, P < 0.01). The change in body weight was significantly correlated with energy balance (ME - EE; P < 0.05). As shown from the results of the body composition measurements, body weight loss was a decrease of fat mass. (ABSTRACT TRUNCATED AT 250 WORDS)
Data Indexing and Querying in DHT Peer-to-Peer Networks

Peer-to-peer DHT systems, such as Chord [8], CAN [5], Pastry [6], or Tapestry [11], make it simple to discover specific data when their complete identifiers—or keys—are known in advance. In practice, however, users looking up resources stored in peer-to-peer systems often have only partial information for identifying these resources and tend to submit broad queries. In this paper, we describe techniques for indexing data stored in peer-to-peer networks, and discovering the resources that match a given user query. Our system creates multiple indexes, organized hierarchically, which permit users to access data in many different ways. Indexes are distributed across the nodes of the network and contain key-to-key (or query-to-query) mappings. Given a broad query, a user can look up the more specific queries that match the original query; the DHT can be recursively queried until the user finds the desired data items. The data itself is stored on only one (or few) of the nodes. Our indexing techniques have several interesting properties, such as good scalability, loose coupling between data and indexes, decentralized architecture, and reasonably-small space requirements. Look-up times depend on the “precision” of the initial query: broad queries incur higher lookup times than specific queries. Note that we do not aim at answering complex database-like queries, but rather at providing practical techniques for searching data using more advanced tools than exact or simple keyword lookups.
Expression Analysis of PIN Genes in Root Tips and Nodules of Medicago truncatula

Polar auxin transport is dependent on the family of PIN-formed proteins (PINs), which are membrane transporters of anionic indole-3-acetic acid (IAA−). It is assumed that polar auxin transport may be essential in the development and meristematic activity maintenance of Medicago truncatula (M. truncatula) root nodules. However, little is known about the involvement of specific PIN proteins in M. truncatula nodulation. Using real-time quantitative PCR, we analyzed the expression patterns of all previously identified MtPIN genes and compared them between root nodules and root tips of M. truncatula. Our results demonstrated significant differences in the expression level of all 11 genes (MtPIN1–MtPIN11) between examined organs. Interestingly, MtPIN9 was the only PIN gene with higher expression level in root nodules compared to root tips. This result is the first indication of PIN9 transporter potential involvement in M. truncatula nodulation. Moreover, relatively high expression level in root nodules was attributed to MtPINs encoding orthologs of Arabidopsis thaliana PIN5 subclade. PIN proteins from this subclade have been found to localize in the endoplasmic reticulum, which may indicate that the development and meristematic activity maintenance of M. truncatula root nodules is associated with intracellular homeostasis of auxins level and their metabolism in the endoplasmic reticulum.
Assessing the Potential of a Low-Cost 3-D Sensor in Shallow-Water Bathymetry

Highly detailed 3-D geoinformation about bathymetry is crucial to understand a wide range of processes and conditions in the geosciences. Recently, low-cost sensors such as Microsoft’s structured-light 3-D camera Kinect for Xbox 360 have been deployed to complement established sources of 3-D bathymetric data like light detection and ranging or sound navigation and ranging. In this letter, we assess the Kinect’s applicability to capture the bathymetry of shallow waters. Therefore, the maximum capturing range through water, accuracy, and precision of Kinect measurements are examined. Additionally, we test a recording setup which allows for the mitigation of waves and which features advantages in terms of refraction correction on a scene containing submerged gravels. As a result, water depths of 30 cm (outdoors) and 40 cm (indoors) can be penetrated. The accomplished accuracy [mean standard deviation (SD) 7 mm] and precision values (mean SD 3.1 mm) are similar to the ones achieved by terrestrial laser scanning bathymetry. Derived gravel sizes highly correspond to the manual reference measurements. Overall, the findings show the Kinect’s applicability in researching shallow natural water bodies.
Neighbourhood Ethnic Composition and Employment Effects on Immigrant Incomes

Currently, in many Western countries there are concerns that clustering of ethnic minorities in certain parts of cities will negatively affect integration processes. However, scholarly theory and evidence on this point is mixed. We use Swedish data and conduct a panel analysis quantifying the degree to which the ethnic composition of the neighbourhood affects the subsequent labour income of individuals for the 1991 to 2006 period. We employ a fixed effects model to reduce the potential bias arising from unmeasured individual characteristics leading to neighbourhood selection. We also control for a range of individual demographic and socioeconomic attributes. Based on gender-stratified analyses of eight immigrant categories (N = 110,000) in three Swedish metropolitan areas, we find that male immigrants (females less so) gain if they reside in neighbourhoods with higher shares of co-ethnics and (under most circumstances) other immigrants, though the impact depends on neighbourhood level of employment and trajectory of ethnic share. This, we argue, should not be seen as an argument for ethnic residential segregation, but it tells us that the high degree of exclusion from the labour market experienced by many immigrants in Sweden is not directly caused by the level of immigrant residential segregation.
Characterization of Drosophila Saposin-related mutants as a model for lysosomal sphingolipid storage diseases

ABSTRACT Sphingolipidoses are inherited diseases belonging to the class of lysosomal storage diseases (LSDs), which are characterized by the accumulation of indigestible material in the lysosome caused by specific defects in the lysosomal degradation machinery. While some LSDs can be efficiently treated by enzyme replacement therapy (ERT), this is not possible if the nervous system is affected due to the presence of the blood-brain barrier. Sphingolipidoses in particular often present as severe, untreatable forms of LSDs with massive sphingolipid and membrane accumulation in lysosomes, neurodegeneration and very short life expectancy. The digestion of intralumenal membranes within lysosomes is facilitated by lysosomal sphingolipid activator proteins (saposins), which are cleaved from a prosaposin precursor. Prosaposin mutations cause some of the severest forms of sphingolipidoses, and are associated with perinatal lethality in mice, hampering studies on disease progression. We identify the Drosophila prosaposin orthologue Saposin-related (Sap-r) as a key regulator of lysosomal lipid homeostasis in the fly. Its mutation leads to a typical spingolipidosis phenotype with an enlarged endolysosomal compartment and sphingolipid accumulation as shown by mass spectrometry and thin layer chromatography. Sap-r mutants show reduced viability with ∼50% survival to adulthood, allowing us to study progressive neurodegeneration and analyze their lipid profile in young and aged flies. Additionally, we observe a defect in sterol homeostasis with local sterol depletion at the plasma membrane. Furthermore, we find that autophagy is increased, resulting in the accumulation of mitochondria in lysosomes, concomitant with increased oxidative stress. Together, we establish Drosophila Sap-r mutants as a lysosomal storage disease model suitable for studying the age-dependent progression of lysosomal dysfunction associated with lipid accumulation and the resulting pathological signaling events. Summary: Detailed analysis of lipid accumulation, lysosomal dysfunction and neurodegeneration in a Drosophila sphingolipidosis model, suitable for studying the resulting pathological signaling events.
An Agent Based Inter-organizational Collaboration Framework: OperA+

Inter-organizational collaboration often occurs in complex, dynamic and unpredictable environments. Regulating structures should be represented explicitly and independently from the acting components at different levels of abstraction in order for stakeholders to be able to analyze the overall setup and decide on their participation. This paper proposes a framework for describing collaboration relationships in inter-organizational partnerships. The framework is based on the OperA model for multi-agent organizations and provides a specification dimension which describes what to do from the designer's perspective based on the concept of organization, role and role dependency, and an enactment dimension which represents the agents and their role enacting relationships to describe who does what from an implementation perspective. The adoption of composite roles and composite agents facilitates a modeling of nested organizations, which offers a suitable way to manage/regulate inter-organizational interactions.
Dynamic authenticated index structures for outsourced databases

In outsourced database (ODB)systems the database owner publishes its data through a number of remote servers, with the goal of enabling clients at the edge of the network to access and query the data more efficiently. As servers might be untrusted or can be compromised, query authentication becomes an essential component of ODB systems. Existing solutions for this problem concentrate mostly on static scenarios and are based on idealistic properties for certain cryptographic primitives. In this work, first we define a variety of essential and practical cost metrics associated with ODB systems. Then, we analytically evaluate a number of different approaches, in search for a solution that best leverages all metrics. Most importantly, we look at solutions that can handle dynamic scenarios, where owners periodically update the data residing at the servers. Finally, we discuss query freshness, a new dimension in data authentication that has not been explored before. A comprehensive experimental evaluation of the proposed and existing approaches is used to validate the analytical models and verify our claims. Our findings exhibit that the proposed solutions improve performance substantially over existing approaches, both for static and dynamic environments.