Miracle-dz/UniFAR-FTUs huggingface dataset:
EOQ model for controllable deterioration rate and time dependent demand and Inventory holding cost

In this paper, we have developed a deterministic inventory model for deteriorating items in which demand rate and holding cost are quadratic and linear function of time. During deterioration period, deterioration rate can be controlled using preservation technology (PT). An exponential distribution is used to represent the distribution of time to deterioration. The derived model is illustrated by a numerical example.
Case Study Applying Agile Service-Oriented Modeling and Architecture Approach for Better Business-Services Alignment

Service modeling and design is one of the challenging tasks in shaping system services in a way that enables Service Business alignment in Service Oriented Architecture systems. Most of the modeling approaches focus on modeling services from the business perspective. Thus, the role of the analyst in shaping the services becomes a separate activity from development that will provide the final shape of the service to be implemented. This causes a gap between service analysis, design, and implementation that increases the chances for improper business service design and implementation alignment. Another problem related to organizing the architecture work of SOA systems is fitting into agile methodologies. This paper introduces a case study providing a practical agile approach that engages service designers with analysts, testers and product owners for full-service alignment among all development players.
Stressful Life Events and Schizophrenia

Empirical research concerning the relationship between life event stressors and schizophrenia is critically reviewed. In accordance with the view that patients suffering from schizophrenia are vulnerable to stress, there is evidence of a relationship between stressors and variation in severity of symptoms over time. There is less indication that schizophrenic patients have had higher levels of stressors than the general population or than patients suffering from other psychiatric disorders. These findings are consistent with vulnerability-stress models of the development of schizophrenia.
How to Assess and Rank User-Generated Content on Web

User-generated content (UGC) on the Web, especially on social media platforms, facilitates the association of additional information with digital resources and online social topics and it can provide valuable supplementary content. However, UGC varies in quality and, consequently, raises the challenge of how to maximize its utility for a variety of end-users, in particular in the age of misinformation. This study aims to provide researchers and Web data curators with answers to the following questions: (1) What are the existing approaches and methods for assessing and ranking UGC (2) What features and metrics have been used successfully to assess and predict UGC value across a range of application domains This survey is composed of a systematic review of approaches for assessing and ranking UGC: results obtained by identifying and comparing methodologies within the context of short text-based UGC on the Web. This survey categorizes existing assessment and ranking approaches into four framework types and discusses the main contributions and considerations of each type. Furthermore, it suggests a need for further experimentation and encourages the development of new approaches for the assessment and ranking.
MotionTree: A Tree-Based In-Bed Body Motion Classification System Using Load-Cells

The basic necessity of sleep in our life is critically important to ensure our wellbeing. Sufficient sleep of good quality is highly desired in order to have enough energy to live. One of the main factors to measure sleep quality is the amount of body motion during sleep. In our earlier work, we have developed a load cell based system that can detect in-bed body movements and classify them into two broad classes: large or small movements. In this paper, we set out to achieve much finer body motion classification. Towards this goal, we define 9 classes of movements, and design a machine learning algorithm using Support Vector Machine (SVM) and Random Forest techniques to classify a movement into one of these 9 classes. In this way, we can find out which body parts are involved in every movement. For every movement, we have extracted 24 features and used them in our model. This movement classification system was evaluated on data collected from 40 subjects who performed 35 predefined movements in each experiment. The accuracy of our model is not exactly the same for all classes of movements. On average it classified correctly 90% of movements. This model can be used conveniently for long-term home monitoring.
An Examination of a Multitiered System of Language Support for Culturally and Linguistically Diverse Preschoolers: Implications for Early and Accurate Identification

Abstract. A disproportionate percentage of culturally and linguistically diverse students have difficulties with language-related skills that affect their academic success. Early and intensive language instruction may greatly improve these students' language skills, yet there is not sufficient research available to assist educators and school psychologists in distinguishing between language disabilities and language differences. Because of this, culturally and linguistically diverse children often receive special education services several years later than other children. The purpose of the study was to investigate the effect of a multitiered intervention on the narrative language skills of seven culturally diverse preschool students. We also examined the preventive impact the narrative language intervention had on special education referrals. Results of the multiple baseline design across participants revealed that a positive trend emerged in retells and personal stories from baseline to intervention for all seven participants. At follow-up, scores remained consistently above baseline. The intervention had a preventive impact for six preschoolers, and only one preschooler was referred for a psychoeducational evaluation. These findings support the use of narrative intervention to prevent erroneous referrals of culturally and linguistically diverse students.
Minorités sexuelles, Internet et santé

LES NOUVELLES TECHNOLOGIES DE communication, et notamment Internet, ont transforme a la fois les strategies relationnelles et la transmission et le partage des informations dans toutes les spheres de la vie, incluant le domaine de la sante. Pour les minorites sexuelles qui sont confrontees a de multiples formes de discrimination et de marginalisation, Internet est devenu un puissant moyen de s’organiser, d’informer et d’intervenir dans le champ de la sante. Les associations et organismes communautaires ciblant ces populations proposent aujourd’hui un
In-Place Printing of Carbon Nanotube Transistors at Low Temperature

Interest in flexible, stretchable, and wearable electronics has motivated the development of additive printing to fabricate customizable devices and systems directly onto virtually any surface. However, progress has been limited by the relatively high temperatures (>200 °C) required to sinter metallic inks and time-consuming process steps, many of which require removal of the substrate from the printer for coating, washing, or sintering. In this work, we addressed these challenges and demonstrate carbon nanotube thin-film transistors (CNT-TFTs) that are fabricated by aerosol jet printing with the substrate never leaving the printer. The full in-place printing approach, from first step to last, used a maximum process temperature of only 80 °C on the printer platen. Silver nanowire (Ag NW) ink was found to be most viable for low-temperature, in-place sintering while still yielding good electrical interfaces to the CNT thin-film channels. These aerosol-jet printed Ag NW films were conductive immediately afte.
A Note On Strongly Edge-Disjoint Arborescences Kristóf Bérczi

In [1], Colussi, Conforti and Zambelli conjectured that in a rooted k-edgeconnected digraph there exist k strongly edge-disjoint arborescences, and also gave a proof for k = 2. In this paper, we give a generalization of the case k = 2 and show that the conjecture does not hold for k ≥ 3.
The effect of EconomasE® as a vitamin E replacer on performance, meat quality and organ weights of broiler birds.

This study was conducted to investigate the effect of supplementing EconomasE ® ( EcoE) as a vitamin E replacer on performance and meat quality of broilers. A total of 300 one-d-old male broilers were randomly assigned into 6 treatments. Each treatment comprised 5 replicates of 10 broilers each. Broilers were allocated to 1 of 6 diets and were fed for 42 d in a complete randomized design (CRD). The dietary treatments included four concentrations of EconomasE ® (150 g, 200 g, 250 g and 300 g /ton) and a 100 IU vitamin E/kg level. The control group was fed with basal diet only. During 42-d growth period, all test diets increased the weight gain of broilers compared to the control (p ® fed birds (p ® has the same or better effects on performance, meat quality and organ weights of broilers compared with dietary supplementation of 100 IU vitamin E/kg.
Evaluation of the fused silica thermal conductivity by comparing infrared thermometry measurements with two-dimensional simulations

A self-consistent approach is proposed to determine the temperature dependent thermal conductivity k(T) of fused silica, for a range of temperatures up to material evaporation using a CO2 laser irradiation. Calculation of the temperature of silica using a two-dimensional axi-symmetric code was linked step by step as the laser power was increased with experimental measurements using infrared thermography. We show that previously reported k(T) does not reproduce the temporal profile as well as our adaptive fit which shows that k(T) evolves with slope discontinuities at the annealing temperature and the softening temperature.
Characterization of an 18F-Growth Hormone Secretagogue Probe for Positron Emission Tomography Imaging of the Growth Hormone Secretagogue Receptor

Cardiovascular disease affects 1.6 million Canadians, of whom one-third have heart failure (HF). HF is diagnosed by imaging investigations and detection of circulating biomarkers. Most of the current imaging strategies study morphologic and gross functional changes, but fall short of imaging molecular abnormalities associated with HF. Biomarkers offer molecular targets; however, clinical biomarkers circulate systemically and are not cardiac-specific. Thus, there is critical need for a biomarker that is endogenous to myocardial tissues. The growth hormone secretagogue receptor 1a (GHSR1a), which binds the hormone ghrelin, is expressed by cardiomyocytes and is elevated in HF patients. This study characterized the specificity of the novel tracer [1-Nal, Lys(4-[F]-FB)]G-7039 to target GHSR1a using Positron Emission Tomography (PET). In vitro analysis of probe specificity by cellular uptake determined that binding was independent of receptor expression, which was confirmed by in vivo PET imaging in GHSR1a-wildtype (wt) and -knockout (ghsr) mice. Ex vivo biodistribution comparing specificity and effects of nutritional state showed that [1-Nal, Lys(4-[F]-FB)]G-7039 did not distribute to the heart and uptake was independent of circulating ghrelin levels. Although [1-Nal, Lys(4-[F]-FB)]G-7039 demonstrated in vitro stability, negligible cardiac uptake and high uptake in the liver, intestines and kidneys within 1 h post-injection indicated rapid probe elimination through hepatobiliary and renal mechanisms, possibly explained by a highly lipophilic tracer. Analysis of cardiac GHSR1a expression and metabolic markers by fluorescence microscopy in fasted, fed, wt and ghsr mice suggests that there may be a ghrelin/GHSR1a system in the heart that is regulated independently of systemic ghrelin/GHSR1a, and that GHSR1a does not play a significant role in cardiac metabolism in healthy mice. In vitro stability and cellular uptake, ex vivo biodistribution and in vivo imaging conducted in this study present a step towards characterizing a suitable GHSR1a PET tracer that may be used to detect HF.
Intrusion-Tolerant Middleware: the MAFTIA approach

The pervasive interconnection of systems all over the world has given computer services a significant socio-economic value, which can be affected both by accidental faults and by malicious activity. It would be appealing to address both problems in a seamless manner, through a common approach to security and dependability. This is the proposal of ’intrusion tolerance’, where it is assumed that systems remain to some extent faulty and/or vulnerable and subject to attacks that can be successful, the idea being to ensure that the overall system nevertheless remains secure and operational. In this paper, we report some of the advances made in the European project MAFTIA, namely in what concerns a basis of concepts unifying security and dependability, and a modular and versatile architecture, featuring several intrusion-tolerant middleware building blocks. We describe new architectural constructs and algorithmic strategies, such as: the use of trusted components at several levels of abstraction; new randomization techniques; new replica control and access control algorithms. The paper concludes by exemplifying the construction of intrusion-tolerant applications on the MAFTIA middleware, through a transaction support service.
Flexible Aggregate Nearest Neighbor Queries in Road Networks

Aggregate nearest neighbor (ANN) query has been studied in both the Euclidean space and road networks. The flexible aggregate nearest neighbor (FANN) problem further generalizes ANN by introducing an extra flexibility. Given a set of data points P, a set of query points Q, and a user-defined flexibility parameter ϕ that ranges in (0, 1], an FA N N query returns the best candidate from P, which minimizes the aggregate (usually max or sum) distance to any ϕ |Q| objects in Q. In this paper, we focus on the problem in road networks (denoted as FANNR), and present a series of universal (i.e., suitable for both max and sum) algorithms to answer FANNR queries in road networks, including a Dijkstra-based algorithm enumerating P, a queue-based approach that processes data points from-near-to-far, and a framework that combines Incremental Euclidean Restriction (IER) and kNN. We also propose a specific exact solution to max-FANNR and a specific approximate solution to sum-FANNR which can return a near-optimal result with a guaranteed constant-factor approximation. These specific algorithms are easy to implement and can achieve excellent performance in some scenarios. Besides, we further extend the FANNR to k-FANNR, and successfully adapt most of the proposed algorithms to answer k-FANNR queries. We conduct a comprehensive experimental evaluation for the proposed algorithms on real road networks to demonstrate their superior efficiency and high quality.
Representation selection problem: Optimizing video delivery through caching

To cope with Internet video explosion, recent work proposes to deploy caches to absorb part of the traffic related to popular videos. Nonetheless, caching literature has mainly focused on network-centric metrics, while the quality of users' video streaming experience should be the key performance index to optimize. Additionally, the general assumption is that each user request can be satisfied by a single object, which does not hold when multiple representations at different quality levels are available for the same video. Our contribution in this paper is to extend the classic object placement problem (which object to cache and where) by further considering the representation selection problem (i.e., which quality representation to cache), employing two methodologies to tackle this challenge. First, we employ a Mixed Integer Linear Programming (MILP) formulation to obtain the centralized optimal solution, as well as bounds to natural policies that are readily obtained as additional constraints of the MILP. Second, from the structure of the optimal solution, we learn guidelines that assist the design of distributed caching strategies: namely, we devise a simple yet effective distributed strategy that incrementally improves the quality of cached objects. Via simulation over large scale scenarios comprising up to hundred nodes and hundred million objects, we show our proposal to be effective in balancing user perceived utility vs bandwidth usage.
Benchmarking recognition results on word image datasets

We have benchmarked the maximum obtainable recognition accuracy on various word image datasets using manual segmentation and a currently available commercial OCR. We have developed a Matlab program, with graphical user interface, for semi-automated pixel level segmentation of word images. We discuss the advantages of pixel level annotation. We have covered five databases adding up to over 3600 word images. These word images have been cropped from camera captured scene, born-digital and street view images. We recognize the segmented word image using the trial version of Nuance Omnipage OCR. We also discuss, how the degradations introduced during acquisition or inaccuracies introduced during creation of word images affect the recognition of the word present in the image. Word images for different kinds of degradations and correction for slant and curvy nature of words are also discussed. The word recognition rates obtained on ICDAR 2003, Sign evaluation, Street view, Born-digital and ICDAR 2011 datasets are 83.9%, 89.3%, 79.6%, 88.5% and 86.7% respectively.
Function of SREBP1 in the Milk Fat Synthesis of Dairy Cow Mammary Epithelial Cells

Sterol regulatory element-binding proteins (SREBPs) belong to a family of nuclear transcription factors. The question of which is the most important positive regulator in milk fat synthesis in dairy cow mammary epithelial cells (DCMECs) between SREBPs or other nuclear transcription factors, such as peroxisome proliferator-activated receptor γ (PPARγ), remains a controversial one. Recent studies have found that mTORC1 (the mammalian target of rapamycin C1) regulates SREBP1 to promote fat synthesis. Thus far, however, the interaction between the SREBP1 and mTOR (the mammalian target of rapamycin) pathways in the regulation of milk fat synthesis remains poorly understood. This study aimed to identify the function of SREBP1 in milk fat synthesis and to characterize the relationship between SREBP1 and mTOR in DCMECs. The effects of SREBP1 overexpression and gene silencing on milk fat synthesis and the effects of stearic acid and serum on SREBP1 expression in the upregulation of milk fat synthesis were investigated in DCMECs using immunostaining, Western blotting, real-time quantitative PCR, lipid droplet staining, and detection kits for triglyceride content. SREBP1 was found to be a positive regulator of milk fat synthesis and was shown to be regulated by stearic acid and serum. These findings indicate that SREBP1 is the key positive regulator in milk fat synthesis.
AdaBoost classification for model-based segmentation of the outer wall of the common carotid artery in CTA

A novel 2D slice based fully automatic method for model based segmentation of the outer vessel wall of the common carotid artery in CTA data set is introduced. The method utilizes a lumen segmentation and AdaBoost, a fast and robust machine learning algorithm, to initially classify (mark) regions outside and inside the vessel wall using the distance from the lumen and intensity profiles sampled radially from the gravity center of the lumen. A similar method using the distance from the lumen and the image intensity as features is used to classify calcium regions. Subsequently, an ellipse shaped deformable model is fitted to the classification result. The method achieves smaller detection error than the inter observer variability, and the method is robust against variation of the training data sets.
The pharmacokinetics and tissue distribution of curcumin and its metabolites in mice.

Curcumin (CUR) is the major active component of turmeric and plays an important role in the prevention and treatment of many chronic diseases such as respiratory and neurodegenerative disease. In the present work, a rapid and simple LC-MS/MS method was developed to investigate the pharmacokinetics and tissue distribution of CUR and its metabolites in mice after intravenous administration of CUR (20 mg/kg). The results showed that the values of AUC0-∞ were 107.0 ± 18.3, 6.0 ± 1.2 and 12.0 ± 4.0 (mg/L) min, and those for t1/2z were 32.4 ± 10.8, 6.4 ± 2.4 and 5.6 ± 1.8 min for CUR, dihydrocurcumin (DHC) and tetrahydrocurcumin (THC) in plasma, respectively. CUR and THC could be detected in liver while CUR and DHC were detected in kidney. Only CUR was detected in brain. These findings indicated that THC was the main metabolite of CUR in plasma. The exposure of CUR in plasma was 6-fold greater than that in liver, kidney and brain.
A load-balance and interference-aware routing algorithm for multicast in wireless mesh network

With the rapid development of multi-media services, the multi-media traffic flows make the load in wireless mesh network (WMN) increase sharply, which incurs network congestion. In the context of having multiple multicast sessions, the load-balance and interference-aware (LBIA) routing algorithm is proposed by considering the intra-flow interference, inter-flow interference and load balance. This algorithm selects the link with less load to transmit information and uses the load balance factor to balance the load of each link in multicast sessions. NS3 simulation results show that the proposed algorithm can improve the overall network performance.
AN ECOLOGICAL STUDY OF ENDEMIC PLANT POLYGONUM ISTANBULICUM KESKIN AND ITS ENVIRONS

In this study, some ecological features of narrow endemic Polygonum istanbulicum Keskin, which was established as a new plant species in 2009, and its environs were examined. There are 41 known Polygonum taxa in Turkey and the genus is represented by 14 species in Istanbul. Plant and soil samples were collected from the place where the species merely lives in
Ahab: Data-Driven Virtual Cluster Hunting

Virtual clusters are an important concept to provide isolation and predictable performance for multi-tenant applications in shared data centers. The problem of how to embed virtual clusters in a resource efficient manner has received much attention over the last years. However, existing virtual cluster embedding algorithms typically optimize the embedding of a single request. We demonstrate that this can lead to fragmentation and suboptimal data center resource utilization over time. We propose an alternative in two stages: First, we describe a novel embedding algorithm, called Tetris, which, in an effort to avoid resource fragmentation over time, takes into account the specific node-to-link resource ratios of the individual requests. While Tetris can be suboptimal when embedding only one request, we find that it performs much better than the state-of-the-art algorithms over time. Second, we allow the algorithm to strategically reject individual requests, even if there are sufficient resources: our proposed algorithm, Ahab, hence selects ("hunts") useful requests over time. An important property of Ahab is that it is data-driven: it uses information about previous requests and embeddings. We report on extensive simulations, which demonstrate the optimization potential of Tetris (+4%) and Ahab (+13%), compared to existing solutions such as Kraken and Oktopus. Furthermore, Ahab illustrates how data-driven algorithms can replace man-made heuristics.