Miracle-dz/UniFAR-FTUs huggingface dataset:
Closed-Form Expressions of Multilayered Planar Green's Functions That Account for the Continuous Spectrum in the Far Field

The rational function fitting method has been found useful in the derivation of closed-form expressions of spatial-domain Green's functions for multilayered media. However, former implementations of the rational function fitting method lead to Green's functions expressions that are not accurate in the far field when this far field is dominated by the continuous spectrum instead of being dominated by surface waves (as it happens, for instance, in the case of lossy multilayered media). In this paper, the authors introduce a novel implementation of the rational function fitting method, which leads to Green's functions expressions that are accurate in the far field when this is dominated either by the continuous spectrum or by surface waves. In the new approach, the far-field contribution of the continuous spectrum to the Green's functions is numerically fitted in terms of functions with closed-form Hankel transforms, and this far-field contribution is explicitly added to the total least squares approximations of the Green's functions. The numerical results obtained for the Green's functions with the new approach have been compared with numerical results obtained via direct numerical integration of Sommerfeld integrals, and excellent agreement has been found despite the contribution - continuous spectrum or surface waves - dominating the far field.
Grænsekrydsende ledelse: Byg bro til samarbejde og innovation

I denne artikel sætter vi fokus på grænsekrydsning som ressource for samarbejde og innovation. Med afsæt i en case fra det danske sundhedsvæsen, hvor der etableres et grænsekrydsende innovationsfællesskab [1], kigger vi på muligheder og barrierer for grænsekrydsninger, og vi peger på grænsekrydsende ledelse som nøglen til at gøre grænser til udviklingsforkant for innovation. Vores hovedbudskab er, at grænser er tvetydige og åbne for fortolkning. Det er aldrig på forhånd givet, om en grænse separerer og adskiller eller bygger bro for samarbejde og innovation, og ledere bør derfor i allerhøjeste grad interessere sig for, hvordan de tænker, taler og handler på grænser. Ledere er, qua deres organisatoriske position, i særlig grad ansvarlige for at etablere grænsepraktikker, hvor grænser bliver til ’broer’ og ikke ’barrierer’ for samarbejde og innovation. Lykkes det ikke at gøre grænser til udviklingsforkant for innovation, bør ledere derfor kigge kritisk på deres egen ledelsespraksis, for denne er med stor sandsynlighed med til at fastholde status quo.
Narrative Discourse and Naming Performance in Epilepsy Patients

It has been stated that epilepsy patients can show alterations in their spontaneous speech. Several studies have focussed on different forms of discourse production in epilepsy patients, but still there is not a clear view of the narrative production problems in epilepsy patients. The current study aimed to find differences between patients with temporal lobe epilepsy and healthy participants in narrative discourse production tasks, and also investigate the differences between patients and healthy participants on several naming tasks. The main hypothesis was that the temporal lobe epilepsy patients perform worse on a narrative discourse task than healthy participants. In the current study, the spontaneous speech of two epilepsy patients has been investigated, and compared to a group of neurologically intact individuals. With the use of the book Tuesday (Wiesner, 1991) participants had to tell a story that matched the book. The narratives that were created by the participants were then transcribed and analyzed. Apart from the narrative task, participants were also tested on an object naming task, and an action naming task. The narratives were scored based on content and on measures concerning the length of the narrative, the grammatical complexity, and lexical diversity. Results showed that the patients told fewer crucial story elements, and used fewer mental state expressions in their stories. Patients also tend to use fewer subordinate clauses, use more T-units to tell their story, use fewer words per T-unit to tell it, and have a greater lexical diversity in telling it. Both patients performed poorly on the action naming task, one of the patients also performed poorly on the object naming task.
Rostrolateral prefrontal cortex: Domain‐general or domain‐sensitive?

The ability to jointly consider several structured mental representations, or relations, is fundamental to human cognition. Prior studies have consistently linked this capacity for relational integration to rostrolateral prefrontal cortex (RLPFC). Here, we sought to test two competing hypotheses: (1) RLPFC processes relations in a domain‐general manner, interacting with different brain regions as a function of the type of lower‐level relations that must be integrated; or (2) A dorsal‐ventral gradient exists within RLPFC, such that relational integration in the visuospatial domain involves relatively more dorsal RLPFC than integration in the semantic domain. To this end, we examined patterns of fMRI activation and functional connectivity during performance of visuospatial and semantic variants of a relational matching task. Across the two task variants, the regions that were most strongly engaged during relational comparison were left RLPFC and left intraparietal sulcus (IPS). Within left RLPFC, there was considerable overlap in activation for the semantic and visuospatial tasks. However, visuospatial task activation peaks were located dorsally to the semantic task peaks. In addition, RLPFC exhibited differential functional connectivity on the two tasks, interacting with different brain regions as a function of the type of relations being compared. While neurons throughout RLPFC may share the function of integrating diverse inputs, individual RLPFC neurons may have privileged access to particular representations depending on their anatomical inputs, organized along a dorsal‐ventral gradient. Thus, RLPFC is well‐positioned as a locus of abstraction from concrete, domain‐specific details to the general principles and rules that enable higher‐level cognition. Hum Brain Mapp, 2012. © 2011 Wiley Periodicals, Inc
1 Unconditionally Secure Multi-party Computation from Weak Primitives

Let us assume that old friends meet again, after a long time. Both have become millionaires since that last time they met would like to find out who has been more successful in making money. However, they don't want the other to find out how much they earn, they both only want to get to know one bit of information. This problem is an example of secure multi-party computation, which has been introduced by Yao [46], where different parties want to collaborate in a secure way in order to achieve a common goal, however they mutually distrust each other and do not want to make use of a trusted third party, i.e., a distinct player that would carry out the computation for them. Note that, opposed to many other problem in cryptography, the players are not apriori good or bad. In this chapter we will only look at special case of secure function evaluation , where every party holds an input to a function, and the output should be computed in a way such that no party has to reveal unnecessary information about her input. A complete solution for this problem with respect to computational security was given in [27]. In [4, 13], it was shown that in a model with only pairwise secure channels, MPC unconditionally secure against an active adversary is achievable if and only if t < n/3 players are corrupted. However, if the players are provided additionally In [3, 39] it was shown that this bound can be improved to t < n/2, assuming that global broadcast channels are additionally given—and this bound was shown tight. A protocol more efficient than those in [3, 39] was given in [15]. For the case where n = 2, there cannot exist a protocol that is unconditionally secure, as we will see later. However, if a primitive called oblivious transfer is assumed, then any function can be calculated unconditionally secure, this was shown by Kilian [31]. In this work we will present several protocols that implement the basic primitives bit-commitment, oblivious transfer and broadcast based on noisy resources, such as noisy channels and correlated randomness.
The Differential Expression of OCT4 Isoforms in Cervical Carcinoma

OCT4 is a transcription factor involved in maintaining stem cell phenotype and pluripotential. However, it remains unclear the expression pattern and biological function of OCT4 isoforms in cervical cancer. Here, we reported that both nuclear OCT4A and cytoplasmic OCT4B were overexpressed in CC. OCT4A was responsible for self-renewal of cervical cancer stem–like cells (CCSCs). Furthermore, OCT4B overexpression in SiHa cervical cancer cell line significantly increased cell proliferation and tumorigenesis by inhibiting apoptosis. Moreover, OCT4B enhanced angiogenesis by the upregulation of CD34, VEGF, HIF-1α and IL-6, and promoted tumor cell mobility to the surrounding tissue by the upregulation of MMP2 and MMP9, and the induction of epithelial-mesenchymal transition (EMT). In conclusion, nuclear OCT4A may serve as a marker of CCSCs and the driving force for cervical cancer metastasis and recurrence, while cytoplasmic OCT4B may cooperate with OCT4A to regulate the progression of cervical cancer through inducing angiogenesis and EMT.
Large Scale Visual Recognition through Adaptation using Joint Representation and Multiple Instance Learning

A major barrier towards scaling visual recognition systems is the difficulty of obtaining labeled images for large numbers of categories. Recently, deep convolutional neural networks (CNNs) trained used 1.2M+ labeled images have emerged as clear winners on object classification benchmarks. Unfortunately, only a small fraction of those labels are available with bounding box localization for training the detection task and even fewer pixel level annotations are available for semantic segmentation. It is much cheaper and easier to collect large quantities of image-level labels from search engines than it is to collect scene-centric images with precisely localized labels. We develop methods for learning large scale recognition models which exploit joint training over both weak (image-level) and strong (bounding box) labels and which transfer learned perceptual representations from strongly-labeled auxiliary tasks. We provide a novel formulation of a joint multiple instance learning method that includes examples from object-centric data with image-level labels when available, and also performs domain transfer learning to improve the underlying detector representation. We then show how to use our large scale detectors to produce pixel level annotations. Using our method, we produce a >7.6K category detector and release code and models at lsda.berkeleyvision. org.
What is the Proper Forensics Approach on Trojan Banking Malware Incidents

Digital forensics procedures should be developed to obtain digital evidence with regard to legal requirements such as admissibility, authenticity, completeness, reliability and believability. On the other hand, Trojan banking malware incident has grown significantly and creates a great threat to online banking users globally. This type of malware is known to use anti-forensic technique to avoid forensic detection. Moreover, there are numerous works and researches that impose the drawbacks on post-mortem forensics approach in dealing with evidence that only resided on non-persistence memory or non-volatile memory. There are works that reveal the disadvantage of live-response approach on incident response that might compromise the evidence as well. For the last four years, there is notably developed on memory forensics approach that focusing on malware incidents. This paper demonstrates the procedures that use three different forensics approaches on three different Trojan banking malware samples: Cridex, ZeuS and SpyEye. The aim of this work is to obtain the proper forensics approach on Trojan banking malware incidents. The paper also uses a network forensics approach to gather and analyse the network-based evidence.
The Benefit of Pooling Operating Rooms and Parallel Surgery Processing under Uncertainty

Operating room (OR) scheduling is an important operational problem for most hospitals. In this study, we present a novel two-stage stochastic mixed-integer programming (SMIP) model to minimize total expected operating cost given that scheduling decisions are made before the resolution of uncertainty in surgery durations. By using our model, we quantify the benefit of pooling ORs as a shared resource and the value of parallel surgery processing. Decisions in our model include the number of ORs to open each day, the allocation of surgeries to ORs, the sequence of surgeries within each OR, and the start time for each surgeon. Realisticsized instances of our model are difficult or impossible to solve with standard stochastic programming techniques. Therefore, we exploit several structural properties of the model to achieve computational advantages. Furthermore, we describe a novel set of widely applicable valid inequalities that make it possible to solve practical instances. Based on our results for different resource usage schemes, we conclude that the benefit of pooling ORs and parallel surgery processing lead to total cost reductions as high as 60% and 80%, respectively.
Sieving technique to solve the discrete log hard problem in Diffie-Hellman Key Exchange

Timing attack is a type of side-channel attack directed at weakly secured computing devices and aims at extracting private keys from cryptosystems. The incidence of timing attacks is expected to rise in the age of Internet of Things (IoT) where devices are mostly power-constrained and cryptographic implementations are minimal. These types of attacks rely on precise timings obtained from cryptographic operations and reconstructing the cryptographic key from such information. This paper presents a method to implement timing attack in the Diffie-Hellman Key Exchange (DHKE) algorithm in an embedded system environment. The approach discussed in this paper aims at decreasing the key search area to reduce the time taken to solve the Discrete Log Hard Problem (DLHP).
An alternative model for the evaluation of tyre shear forces under steady-state conditions

Modeling of traction forces generated by wheels is a problem which is being investigated by many years. Several models have been proposed whose complexity depends on the desired accuracy. An evergreen model, which is very often cited and used, is the one proposed by Dugoff et al. in 1970. Despite its simplicity it returns a very good characterization of the phenomena acting on a wheel and has the undoubt advantage of being obtained on the basis of physical considerations. In this paper the original model is revised in order to solve some inconsistencies. Two models have been proposed where the variables conventionally used to characterize the wheel forces, i.e., slip s and side slip alpha, are replaced with a new vectorial variable. A more accurate estimate of the wheel forces has been obtained by removing one simplifying approximation of the original model. Comparisons are proposed between the Dugoff model and the new models.
A BIOFEEDBACK-BASED PHYSICAL ACTIVITY ADVISORY SYSTEM by Hawazin

Physical inactivity, a phenomenon on the rise in numerous countries, has gained global attention because of its negative effects on humans' physical wellness. It represents a stumbling block in the way of living a healthy lifestyle. Recent statistics of World Health Organization (WHO) ranked physical inactivity as the fourth leading risk factors for adults' mortality all over the world [1]. Also, physical inactivity is considered as one of the most prominent contributing factors in several severe diseases such as breast and colon cancer, diabetes and many heartrelated diseases [1]. Therefore, improving daily physical activity levels is an urgent societal goal in order to tackle the physical inactivity problem. Achieving such challenging goal requires addressing the factors that affect adults’ physical activity. In fact, there are many factors that lead to physical inactivity such as the busy lifestyle, lack of awareness regarding required physical activity levels and other environmental factors. Physical activity advisory systems can be seen as a promising solution for the inactivity problem. In order to enhance their effectiveness, these systems must take into account most of the factors previously mentioned. In this thesis, we aim to provide a method to promote the increase of daily physical activity levels by leveraging biofeedback and context awareness features. In order to achieve this purpose, we design and develop an algorithm that provides a user with personalized physical activity advice. This advice increases the user's awareness through the use of calories expenditure. To add a context awareness component to our algorithm, we propose an extension of the Ubiquitous Biofeedback (UB) Model [2]. We believe that combining the biofeedback feature with context awareness component would make the system sensitive to the user’s status and thus increase the chances of her or him following it. This advice represents the daily-recommended amount of physical activity for maintaining healthy lifestyle according to [3, 4]and other international organizations' recommendations. In order to prove the concept of the proposed algorithm and extended UB Model, we design and develop a system called "CAB". It is a context aware biofeedback system that tracks user's physical movement and estimates the amount of calories burnt to provide the user with a personalized physical activity advice that considers user's current status, preferences and surrounding environmental context. The system utilizes a biofeedback sensor and a smart phone in order to provide the personalized advice that is
Understanding the Marketing Department's Influence within the Firm

Increasing debate centers on the decreasing influence of the marketing department within firms. This study investigates such influence and assesses its determinants and consequences. The results show that the accountability and innovativeness of the marketing department represent the two major drivers of its influence. However, the results do not indicate that the customer-connecting role of the marketing department increases its influence, though this role is important for shaping the firm's market orientation. A marketing department's influence is related positively to market orientation, which in turn is related positively to firm performance. This study also suggests a dual relationship between the marketing department's influence and market orientation. A key implication of this study is that marketers should become more accountable and innovative to gain more influence.
Lower Secondary School Pupils’ Perception of e-Textbooks

The main research aim of the study was to investigate pupils’ perception of the (future) use of e-textbooks. The aim was achieved by a survey involving 250 lower secondary school pupils in the Czech Republic. To analyse the data collected by means of a questionnaire, methods of descriptive and inferential statistics were used. The results showed that no matter if pupils use e-textbooks, the majority of respondents would like to use the e-textbooks in the future. In addition, according to the study pupils have more positive perception of the e-textbook than the printed textbook.
Seizures in Severe Malaria: Is there Direct Brain Involvement?

Seizures are a frequent manifestation of severe malaria in children especially those less than 5 years of age. Al- though simple febrile seizures occur in young children of the same age group, for a long time it has not been established whether seizures following severe malaria in children of this age group are a consequence of febrile illness or due to cere- bral involvement. The possibility of determining whether these seizures are simply febrile or due to cerebral involvement is important for accuracy of diagnosis and case management; it forms the basis for making prognostic assessments and predicting future neurologic outcome as part of the burden of the disease in sub-Saharan Africa. The purpose of this review is not to pro- duce any new findings. Instead, we aim to present existing evidence for and against the possible involvement of the cen- tral nervous system in seizures accompanying cerebral malaria. This review reveals that controversy still exists and the weight of evidence seems to be on the side of a direct neurologic involvement in patients with seizures from cerebral ma- laria. We conclude with a call for a heightened sense of awareness and the establishment of stringent treatment regimens in patients who present with malaria complicated by seizures.
Hot halos around high redshift protogalaxies : Observations of O VI and N V absorption in damped Lyman-α systems

Aims. We present a study of the highly ionized gas (plasma) associated with damped Lyman-α (DLA) systems at z = 2.1−3.1. Methods. We search for O vi absorption and corresponding Si iv ,C iv ,a nd Nv in a Very Large Telescope/Ultraviolet-Visible Echelle Spectrograph (VLT/UVES) sample of 35 DLA systems with data covering O vi at S /N > 10. We then use optical depth profile comparisons and ionization modelling to investigate the properties, phase structure, and origin of the plasma. Results. We report twelve DLAs (nine intervening and three at 19. 5t o>21.1, and logN Warmii > 19. 4t o>20.9. On average, the hot and warm phases thus contain >40% and >20% of the baryonic mass of the neutral phase in DLAs, respectively. Conclusions. If the temperature in the O vi phase is ≈10 6 Ka nd sofOvi = Ovi/O � 0. 2, the plasma can make as ignif icant contribution to the metal budget at high redshift. Additional searches for O vi in Lyman Limit Systems (QSO absorbers with 17.0 < NHi < 20.3) will be necessary to determine the total quantity of baryons and metals hidden in hot halos at z ≈ 2.
Multi-threaded real root isolation on multi-core architectures ( Spine title : Real Root Isolation for Polynomial System Solvers )

Today, most computer algebra systems offer efficient solvers for computing the complex solutions of polynomial systems. Some of them, such as Maple, provide tools for “identifying” which of those solutions are real. These tools support many applications in areas like robotics, program verification, and dynamical system analysis, to name a few. In this thesis, we investigate parallel algorithms for isolating the real roots of univariate equations with rational number coefficients. This type of calculation is fundamental to the computation of the real solutions of polynomial systems. Our objective is to improve performance of real root isolation on multicore processors in terms of parallelism and cache complexity, such that harder problems can be tackled on these architectures. On multicores, the parallelization of real root isolation reduces to that of Taylor shift computations, which generalize the Pascal Triangle construction. With respect to previous works, we provide a more realistic analysis (in terms of work, span, burdened span, cache complexity) of the parallelization of this method. This leads us to develop poly-algorithms which can adapt the granularity of their parallelism dynamically depending on the local amount of work. Experimentation illustrates the effectiveness of this approach.