Miracle-dz/UniFAR-FTUs huggingface dataset:
PIECEWISE CONTINUOUS SOLUTIONS OF IMPULSIVE LANGEVIN TYPE EQUATIONS INVOLVING TWO CAPUTO FRACTIONAL DERIVATIVES AND APPLICATIONS

ABSTRACT: The standard Caputo fractional derivative is generalized for the piecewise continuous functions. The piecewise solutions of a Langevin type differential equation involving with two fractional derivatives are obtained. The obtained result is applied to study a more general boundary value problem for the impulsive Langevin fractional differential equation involving the Caputo fractional derivatives. New existence results for solutions of concerned problems are established. In order to avoiding misleading readers, we present some counter examples to show readers some mistakes happened in [Impulsive boundary value problems for two classes of fractional differential equation with two different Caputo fractional derivatives, Mediterr. J. Math. 13(3)(2016) 1033-1050] and [Presentation of solutions of impulsive fractional Langevin equations and existence results, The European Physical Journal Special Topics, 222(8)(2013), 1857-1874].
A Mathematical Model of Biofilm Growth on Degradable Substratum

We derive a mathematical model for biofilm growth on a degradable substratum. The starting point is the one-dimensional Wanner-Gujer biofilm model. The processes included are diffusion of a dissolved growth controlling substrate into the biofilm, cell lysis, detachment of biomass, and growth from substrate conversion and substratum degradation. The resulting model is a system of two non-linear ordinary differential equations, the evaluation of the right-hand side of which requires the solution of a semi-linear two-point boundary value problem. We perform standard analysis from the existence and uniqueness of solutions to equilibrium and stability analysis. Finally, we study our model through numerical simulations and investigate how biofilms evolve on degradable substratum. We find in our setting that the addition of substratum degradation has no effect on the long-term behaviour of the biofilm, but does affect the transient behaviour.
TRAVAUX DES COLLOQUES LE COURS DE LINGUISTIQUE

The aim of this paper is to take a metatheoretical look at Ferdinand de Saussure’s principle of arbitrariness. What is the status of this principle in the overall theory of language proposed by the Swiss linguist? This question is not just a plaything for historians and philosophers of linguistics, since the answer is intimately related to actual scientific practice, namely the degree of empirical testability of the principle and the degree of protection against falsifying evidence that the principle should receive. The question about the status of the principle of arbitrariness can be broken down into at least two more specific questions. The first one refers to the place of the principle within what Quine and Ullian would call “the web of belief” of Saussurean linguistics. Thus, the principle can be a “metaphysical model,” a part of the “hard core” of the research program, a regular empirical hypothesis, or an a posteriori summary of results from actual investigation of linguistic data. The second question concerns the degree of idealization involved in the principle. Is the principle more similar to what Cartwright calls a “phenomenological law,” i.e. a law about actual observable linguistic phenomena; or to a “theoretical law,” which describes an idealized model of the phenomenon under investigation, but does not always describe empirical data correctly.
Error-Bounded Correction of Noisy Labels

To collect large scale annotated data, it is inevitable to introduce label noise, i.e., incorrect class labels. To be robust against label noise, many successful methods rely on the noisy classifiers (i.e., models trained on the noisy training data) to determine whether a label is trustworthy. However, it remains unknown why this heuristic works well in practice. In this paper, we provide the first theoretical explanation for these methods. We prove that the prediction of a noisy classifier can indeed be a good indicator of whether the label of a training data is clean. Based on the theoretical result, we propose a novel algorithm that corrects the labels based on the noisy classifier prediction. The corrected labels are consistent with the true Bayesian optimal classifier with high probability. We incorporate our label correction algorithm into the training of deep neural networks and train models that achieve superior testing performance on multiple public datasets.
Practical Operational Risk

Operational losses are generally observed at specific points in time and vary from moderate to possibly very large amounts. Both variables – the time of the event and the amplitude of the associated loss – are random variables whose distributions must be estimated. The concept of compound Poisson process provides an accurate analytical framework to address the modelling problem. The time of the event is captured by the intensity of the Poisson process and losses by an appropriate distribution. The aggregated operational losses are in this setup considered to follow a random process { } 0 ) ( ≥ t t L with
Review of multibody charm analyses 1 68

where |∂φ/∂(s1 . . . sn)| represents the density of states at s, and M the matrix element for the decay at that point in phase space, which is 2, 5, 8, . dimensional for D decays to 3, 4, 5, . spinless particles. Additional parameters are required to fully describe decays involving particles with non-zero spin in the initial or final state. For the important case of D decays to 3 pseudoscalars, the decay kinematics can be represented in a two dimensional Dalitz plot [1]. This is usually parametrized in terms of s12 ≡ (p1 + p2) 2 and s23 ≡ (p2 + p3) 2, where p1, p2, p3 are the four-momenta of the final state particles. In terms of these variables, phase-space density is constant across the kinematically allowed region, so that any structure seen in the Dalitz plot is a direct consequence of the dynamics encoded in |M|. Note that here, because the 3-momenta of the decay products are confined to a plane, no parity violating kinematic observables can be constructed (unless they also violate rotational invariance). This is not the case for decays to four or more particles. These can therefore not be unambiguously described in terms of analogously-defined variables sij , sijk, which are parity-even. The use of parity-odd observables in four body decays is discussed below. In the widely-used isobar approach, the matrix element M is modeled as a sum of interfering decay amplitudes, each proceeding through resonant two-body decays [2]. See Refs. 2–4 for a review of resonance phenomenology. In most analyses, each resonance is described by a Breit-Wigner [5] or Flatté [6] lineshape, and the model includes a non-resonant term with a constant phase and magnitude. This approach has well-known theoretical limitations, such as the violation of unitarity and analyticity, which can break the relationship between magnitude and phase across phase space. This motivates the use of more sophisticated descriptions, especially for broad, overlapping resonances (frequently found in S-wave components) where these limitations are particularly problematic. In charm analyses, these approaches have included the K-matrix approach [5–8] which respects two-body unitarity; the use of LASS scattering data [9]; dispersive methods [10–13]; methods based on chiral symmetry [14–16], QCD factorisation (although this seems better suited to B decays) [17–19]; and quasi model-independent parametrizations which use generic lineshapes, with minimal theory input and many free parameters, for a subset of resonances [20–23]. An important example, with a rich resonance structure, is D0 → KSπ +π−, which is a key channel in Charge-Parity (CP) violation and charm mixing analyses. The first analysis by CLEO [24] described the Dalitz plot with 5k signal events with 10 resonant components. This and later analyses by Belle [25] and CDF [26] model the Dalitz plot as a sum of Breit Wigner and Flatté line shapes, and a non-resonant component. BaBar [27] on the other
Measuring and Hedging Oil Price Sensitivities: A Global Impact Study

The New Year has brought turmoil to global markets. Large sell-offs and high volatility in equity markets have been attributed to the continuing decline in the price of oil, which dipped below $30 a barrel for the first time since 2003. There is no sign of an imminent rebound as Saudi Arabia and other OPEC leaders maintain high production levels in an effort to enforce market competitiveness [3]. Making matters more complex, the dramatic fall in oil over the past 18 months has coincided with other underlying market trends, including tightening monetary policy in the US, fresh rounds of quantitative easing in the EU and Japan, a strengthening dollar, slowing demand in China, and weak global growth. Taking into account current global conditions, this paper builds a novel framework with which to estimate, and subsequently, hedge oil price exposure in various industry sectors. Section 2 introduces the current and historical oil environment. Sections 3 and 4 estimate oil sensitivities of these industries, propose strategies with which to hedge the volatile changes in the oil price, and outline the risks inherent in such strategies. Section 5 examines the impact of Sovereign Wealth Fund liquidations. Sections 6 and 7 explore the macroeconomic and state-wide impacts, respectively, and Section 8 offers our outlook on global growth.
Domain Transfer for Semantic Segmentation of LiDAR Data using Deep Neural Networks

Inferring semantic information towards an understanding of the surrounding environment is crucial for autonomous vehicles to drive safely. Deep learning-based segmentation methods can infer semantic information directly from laser range data, even in the absence of other sensor modalities such as cameras. In this paper, we address improving the generalization capabilities of such deep learning models to range data that was captured using a different sensor and in situations where no labeled data is available for the new sensor setup. Our approach assists the domain transfer of a LiDAR-only semantic segmentation model to a different sensor and environment exploiting existing geometric mapping systems. To this end, we fuse sequential scans in the source dataset into a dense mesh and render semi-synthetic scans that match those of the target sensor setup. Unlike simulation, this approach provides a real-to-real transfer of geometric information and delivers additionally more accurate remission information. We implemented and thoroughly tested our approach by transferring semantic scans between two different real-world datasets with different sensor setups. Our experiments show that we can improve the segmentation performance substantially with zero manual re-labeling. This approach solves the number one feature request since we released our semantic segmentation library LiDAR-bonnetal [18].
Structural Change Detection by Sparse Density Ratio Estimation

The objective of change detection is to investigate whether change exists between two data sets f x i g ni =1 and f x ′ i ′ g n ′ i ′ =1 . In this paper, we explore methods of structural change detection , which are aimed at analyzing change in the dependency structure between elements of d -dimensional variable x = ( x (1) ; : : : ; x ( d ) ) ⊤ .
Automatic Segmentation for Retinal Vessel Based on Multi-scale 2D Gabor Wavelet

Segmentation of retinal vessels plays an important role in the diagnostic procedure of retinopathy. Due to the fact that the retinal vessels usually have some tiny structures and blurred boundaries, especially with remarkable noises resulted from retinal image acquisition, it is diﬃcult to segment vessels from retinal images. In this paper, a new automatic segmentation method for retinal vessels is proposed. Firstly, the retinal vessel image is enhanced by the contrast-limited adaptive histogram equalization, and followed by multi-scale 2D Gabor wavelet transformation. Then, the use morphological reconstruction (MR) and region growing (RG) are used respectively to extract retinal vessels. Finally, both the segmented results are combined to achieve the ﬁnal segmentation by reclassifying the vessel and background pixels. Experiments are conducted on the publicly available DRIVE and STARE databases, which show the eﬀectiveness of the proposed method on retinal vessel segmentation.
Designing for Inter/Generational Communities Proceedings of the 3rd International Workshop “Fostering Social Interactions in the Ageing Society”, COOP Conference 2012

Demographic change has stimulated ICT development and research in different fields, such as CSCW, HCI, or the AAL (Ambient Assisted Living) domain. Enabling ‘aging at home’ has become a main target in many nations due to economic challenges and demographic changes. ‘Aging at home’ is situated in a tension between keeping ones’ autonomy and social inclusion. This strong socio-cultural embedding of relationships in higher ages contoured by individual and societal norms and values require socio-technical and user-oriented research approaches common in e.g. the CSCW community. However, due to the extremely heterogeneous target group in terms of technology affinity and acceptance as well as individual needs and conducts of life, it is time to reconsider common research methodologies, technological solutions and research paradigms. The workshop aimed at exploring technology design research, focusing on the particular
The American Holstein dairy cow during early lactation: grazer or browser?

Early lactation in high producing dairy cows has be en the focus of extensive research for indoor feeding systems covering an ample range of t opics (eg. Thatcher et al., 2006; Van Knegsel et al., 2007; Liu et al., 2009; Robinson, 2010). This volume of scientific information contrasts with the limited and rather recent resear ch on early lactation in high producing grazing dairy cows (Meikle et al., 2004; Kennedy et al., 2007; McEvoy et al., 2008, 2009; Adrien et al., 2010).
Evaluation of on-Farm Irrigation Scheduling: Case Study of Drip Irrigated Potatoes in Southern Tunisia

Effective irrigation scheduling and the use of modern irrigation systems are two possible options to improve water use efficiency in arid regions. Drip irrigation is highly efficient, but is not always used properly. Over irrigation seems to be a common problem encountered with this system, due to inadequate scheduling. The potential of irrigation scheduling to improve yield and to save water is investigated in this work. A case study of drip irrigated potato grown on sandy soil in field trials is used. The growers method consisting of supplying a fixed amount of water is compared to the method of a daily compensation of calculated crop consumption (ETc =Kc*ET0) and the method of the soil water balance (SWB) by compensating cumulated ETc. Well water with an ECi of 3.25 dS.m was used for irrigation over two cropping seasons. Yield, water supply and soil salinity were measured. Results show that in both seasons, fresh tuber yield was highest for the SWB scheduling technique, (40 and 30 t.ha) although no significant differences were observed with the daily irrigation method. The producer method not only caused significant reductions in yield but also resulted in using 20 to 25% more water and increased soil salinity. The highest water use efficiency was obtained with SWB: 11.77 and 9.13 kg.m of fresh potato, respectively for spring and autumn seasons i.e. about 64 and 86% more than that of the grower. The SWB method is recommended as a tool to use saline water for irrigation in arid Tunisia.
A Survey on Perceptual image hash for authentication of content.

- Perceptual picture hash has been broadly explored trying to tackle the issues of picture content verification and content based picture recovery (CBIR). In this paper, we consolidate visual recognition hypothesis and measurable examination systems to build up a genuine perceptual picture hash strategy for substance validation. To accomplish perceptual affectability and genuine perceptual strength, the proposed strategy uses Watson's visual model to extricate outwardly delicate components that assume a critical part in the process of people seeing picture content. We then produce vigorous perceptual hash code by consolidating picture square based elements and key-point-based elements. The proposed technique accomplishes a tradeoff between perceptual heartiness to endure substance protecting controls and an extensive variety of geometric contortions and perceptual affectability to identify malevolent altering. Besides, it has the usefulness to recognize bargained picture locales. Contrasted and best in class plots, the proposed system gets a superior far reaching execution in content based picture altering localization and identification.
Comparative Study of Antioxidant Activity and Hepato-Protective Effect of Extracts of Tetracarpidium conophorum and Dacryodes edulis on Sodium Arsenate Exposed Rats

DOI: 10.21276/sjbr.2018. 3.2. 5 Abstract: This study comparatively evaluated the in vitro antioxidant activity and the hepato-protective effect of extracts of two locally consumed fruits, Dacryodes edulis (African pear) and Tetracarpidium conophorum (African walnut) in sodium arsenate exposed rats. Antioxidant activity was determined by spectrophotometric methods using 2, 2-diphenyl-2picrylhydrazyl (DPPH) radical, hydrogen peroxide (H2O2) and malondialdehyde (MDA) assays. Total phenol, flavonoids and anthocyanins content of extracts were also determined. Results from the study indicated that DPPH and H2O2 scavenging capacity as well as percentage inhibition of MDA were significantly higher (P˂0.05) in extract of T. conophorum (48.34%, 46.9% and 53.5%, respectively) when compared with D. edulis extract (45.47%, 18.1% and 45.3%, respectively). The anthocyanins content was significantly higher (P˂0.05) in D. edulis extract than in T. conophorum. Whereas, T. conophorum extract recorded higher phenol content (52.3GAE/100g) compared with D. edulis extract (22.5GEA/100g). The flavonoids content of T. conophorum extract was comparable to that of D. edulis. The hepato-protective effects of the extracts were examined in vivo in male Wister rats challenged with sodium arsenate. Results showed that the rats fed with the two extracts had significant reduction (p<0.05) in lipid peroxidation, increase in SOD and catalase activities relative to control values. These results suggest that rat fed with Dacryodes edulis and Tetracarpidium conophorum extracts possess varied degree of potent antioxidant activity and may serve as important sources of antioxidants in food, cosmetics and pharmaceutical industries.
The Effect of Company Size, Green Capability and Profitability on Green Product Innovation

This study aims to examine the effect of company size, green capability and profitability on green product innovation. The sample used in this study was 637 manufacturing companies listed on the Indonesia Stock Exchange (IDX) for the year 2012–16. Multiple regression techniques are used to find empirical evidence about company size, green capability, profitability and green product innovation. The results show that company size has a positive effect on green product innovation while green capability and profitability have a positive effect on green product innovation.
Alleviating Biases in Infrastructure Decisions for Sustainability: A Summary Of Five Experiments And A Call To Action For The Engineering Project Management Research Community

By blending theory from behavioral science and infrastructure project planning, we studied whether interventions to the choice structure of an infrastructure planning tool could alleviate biases in decision making for infrastructure planning about sustainability. We empirically tested interventions to the Envision rating system for infrastructure using simplified case studies which simulated a real-world decision environment. We found that endowing engineers with sustainability points to induce loss aversion and showing them an exemplary role model project produced significant gains in setting high goals for sustainability. The combined effect was greater than either intervention separately. While these types of interventions can be controversial when not disclosed, we found that pre-disclosing the interventions to participants did not diminish the results. We repeated the study with groups of decision-makers and found a similar effect on sustainability points. These results, combined with previous research, suggest that approaches from behavioral science (loss aversion, role models, and combined interventions) can translate to, and improve, multi-stakeholder infrastructure planning decisions. The results also advance understanding of underexplored areas in behavioral science: nonconsumer decisions, combined interventions, pre-post disclosure, and the effect of choice interventions on group decision making. We hope to grow the interdisciplinary community studying these interventions, which hold great promise to improve infrastructure outcomes, yet require the unique expertise of the engineering project management community. 1 Assistant Professor, Department of Civil and Environmental Engineering, Virginia Tech, 200 Patton Hall, Blacksburg, VA 24061, tshealy@vt.edu 2 Associate Professor, Department of Civil Engineering, Clemson University, 208 Lowry Hall, Clemson, SC 29634,
Engaging a community for youth mental health and wellness: Reflections and lessons learned

As clinicians at a university-affiliated health centre faced with youth mental health and substance use concerns, we reached out to the local community for guidance. We partnered with community leaders to explore how to best understand the issues and engage with the community. Using a community-engaged research (CEnR) approach, we conducted a needs assessment to explore the issues and inform change. We formalised a partnership with the local school and community board, which led to the creation of a Community Alliance. Our engagement efforts allowed us to understand the community more deeply and establish more effective change. Our most successful outcome was the development of a youth mental health and wellness Action Plan which helped direct our strategies moving forward. This article highlights our community engagement activities, processes and lessons learned, which may be of benefit to other academic researchers and clinicians who are interested in CEnR.
THE 5 STUDENT SYMPOSIUM ON MECHANICAL AND MANUFACTURING ENGINEERING ANALYSIS AND REDESIGN OF SPOKES ON ROTARY KILN

In asphalt mixing plants, the rotary kiln is a massive machine whose function is to dry and heat a mixture of sand and gravel. The rotation of the kiln is transferred through supporting rings which are fitted to the drum shell by means of spokes. Loads acting on these spokes are both thermal and mechanical. Indeed, the rotary kiln is highly heated by a burner and loaded as well by its self-weight and the raw material passing through it. The spokes are welded onto both the supporting ring and the drum shell. Fatigue can lead after some time of operation to spoke or weld crack. In this article, a load investigation is carried out using analytical and numerical approaches. Stress results are obtained by finite element simulation and numerical model is compared with strain gauge measurements performed on an operating rotary kiln. Then, fatigue analysis is conducted to find the expected lifetime of both the spoke and the welds. Finally, an optimized redesign of the spoke is presented to improve fatigue lifetime.