Miracle-dz/UniFAR-FTUs huggingface dataset:
Depression Among HIV-infected Patients in Korea: Assessment of Clinical Significance and Risk Factors

Background With prolonged life expectancies, mental illness has emerged as a disabling disorder among people with HIV. Materials and Methods This study was conducted to assess the prevalence of depression and its risk factors among Korean patients with HIV infections. Eighty-two HIV-infected patients completed structured questionnaires including the Beck Depression Inventory and the State-Trait Anxiety Inventory. Subjects with depression were compared to those without depression in terms of demographics, comorbidities, CD4 T-cell count, RNA copy numbers, highly active antiretroviral therapy (HAART) regimens, and adherence. Results The estimated depression rate was 21% (17 of 82 subjects). Comorbidities (47% vs. 20%, P = 0.01) and unemployment (65% vs. 31%, P = 0.02) were risk factors for depression. Depressive patients were more likely to be anxious (71% vs. 29%, P < 0.01), to frequently miss clinical appointments each year (P = 0.04), and to have higher cumulative time lost to follow-up per month (P <0.01) compared to non-depressive patients. Only three depressive patients were referred to neuropsychologists. Conclusions More than 20% of the Korean HIV patients in this study suffered from depression associated with poor adherence. Considering the low level of recognition of depression by clinicians, risk factor-based active assessment is recommended to manage depression properly in HIV-infected patients.
Approximating parameterized convex optimization problems

We consider parameterized convex optimization problems over the unit simplex, that depend on one parameter. We provide a simple and efficient scheme for maintaining an ε-approximate solution (and a corresponding ε-coreset) along the entire parameter path. We prove correctness and optimality of the method. Practically relevant instances of the abstract parameterized optimization problem are for example regularization paths of support vector machines, multiple kernel learning, and minimum enclosing balls of moving points.
Dynamic Routing and Wavelength Assignment in Multifiber WDM Networks with Wavelength Conversion Capability

This paper proposes a dynamic routing and wavelength assignment (RWA) scheme in multifiber WDM networks with wavelength conversion capability. In multifiber WDM networks, each link consists of multiple fibers. Thus, multiple lightpaths with the same wavelength can be established in the same link as long as they use different fibers. In WDM networks with wavelength conversion, the network nodes have wavelength conversion capability which can convert one wavelength to another. In order to efficiently utilize multifiber and wavelength conversion capability, an appropriate RWA scheme is necessary. The proposed scheme provides RWA for multifiber WDM networks with sparse and full wavelength conversion capability. In the proposed scheme, a route and wavelengths are selected for each lightpath based on wavelength availability and location of nodes with wavelength conversion capability. Through simulation experiments, we show that the proposed scheme reduces the blocking probability of lightpath establishment efficiently.
Families of vicious walkers

We consider a generalization of the vicious walker problem in which N random walkers in Rd are grouped into p families. Using field-theoretic renormalization group methods we calculate the asymptotic behaviour of the probability that no pairs of walkers from different families have met up to time t. For d > 2, this is constant, but for d < 2 it decays as a power t−α, which we compute to (e2) in an expansion in e = 2 − d. The second-order term depends on the ratios of the diffusivities of the different families. In two dimensions, we find a logarithmic decay (ln t)− and compute exactly.
Fingerprint Authentication and Classification Using Sparse Representation and Neural Networks

Fingerprint authentication and classification are introduced after compressed images. Sparse representation is used for compression process. In this algorithm, Construct a dictionary for predefined fingerprint image patches. For a new given fingerprint images, represent its patches according to the dictionary by computing l0-minimization and then quantize and encode the representation. It provide high Peak Signal to Noise Ratio and high compression ratio. Experiments also illustrates that the algorithm is robust to extract minutiae. This algorithm is efficient compared with JPEG, JPEG 2000 and WSQ. All previous methods have compressed fingerprint images. Before compression, preprocessing steps are done for future work. The proposed method is fingerprint compressed images are authenticated and classified using neural networks. After that compressed images two finger combination based new finger print create for high secure privacy protection. A novel system for protecting fingerprint privacy by combining two different fingerprints into a new identity for authentication. And also to classify the training samples should include fingerprints with different quality (“good”, “bad”, “ugly”).
Development of a robotic scrub nurse for the operating theatre

This paper describes how a robotic scrub nurse has been developed to assist human scrub nurses during surgical interventions. The robotic scrub nurse developed in this work is equipped with a voice recognition module to know the requested surgical instrument; it locates this element on a storage tray using computer vision and pattern recognition and picks the element from the tray placing it on an interchange tray where the human scrub nurse can finally pick the demanded instrument. Moreover, to develop the system, an electromagnetic gripper has been implemented to pick the instrument. There has been also installed a new connector in the robot arm to make available robot's digital outputs outside his structure. Nowadays the system which controls the robot can identify up to 7 surgical instruments and more than 20 spoken instructions and it has been used in the operating theatre of our research group (bioengineering institute).
Probabilistic approaches in ontologies: Joining semantics and uncertainty for AUV persistent autonomy

This work starts from the need of incorporating uncertainty into ontological representations, given that its presence is an inevitable fact for any real field experience. Applications in the underwater domain are very relevant, especially in the oil&gas field. A vehicle able to maintain such a level of cognition, incorporating uncertainty and semantics, is more reliable, can address different situations and safely operate on underwater infrastructures. The paper presents ways to incorporate a Bayesian framework into traditional owl-based ontologies, and analyses its implications for the overall system. A novel solution is proposed, in order to dynamically update the belief on the world model, providing at the same time means for the other modules - especially the planner - to access discretised values. The full architecture and proposed system have been integrated in Nessie VII AUV and results from post-processing of mission data are presented.
Mutation Accumulation and the Extinction of Small Populations

Although extensive work has been done on the relationship between population size and the risk of extinction due to demographic and environmental stochasticity, the role of genetic deterioration in the extinction process is poorly understood. We develop a general theoretical approach for evaluating the risk of small populations to extinction via the accumulation of mildly deleterious mutations, and we support this with extensive computer simulations. Unlike previous attempts to model the genetic consequences of small population size, our approach is genetically explicit and fully accounts for the mutations inherited by a founder population as well as those introduced by subsequent mutation. Application of empirical estimates of the properties of spontaneous deleterious mutations leads to the conclusion that populations with effective sizes smaller than 100 (and actual sizes smaller than 1,000) are highly vulnerable to extinction via a mutational meltdown on timescales of approximately 100 generations. We point out a number of reasons why this is likely to be an overly optimistic view. Thus, from a purely genetic perspective, current management policies that provide formal protection to species only after they have dwindled to 100-1,000 individuals are inadequate. A doubling of the deleterious mutation rate, as can result from the release of mutagenic pollutants by human activity, is expected to reduce the longevity of a population by about 50%. As some investigators have previously suggested, the genetic load of a population can be readily purged by intentional inbreeding. However, this effect is at best transient, as intentional inbreeding can only enhance the probability of fixation of deleterious alleles, and those alleles that are purged are rapidly replaced with new mutations.
IMPROVING PATH PLANNING PERFORMANCE BY MONITORING HUMAN DECISIONS

Behavioral based control is usually based on a set of previously codified rules to which the system must adhere. Adaptive behavioral modeling involves learning new domain knowledge and applying the newly learned knowledge to the situation while still complying with the rules in the process of performing the task. This paper proposes a solution to improve path planning by observing human decisions in path planning and chunking pieces that are superior to stored paths.
Primary School Teachers and Parents Perception of Peer Bullying Among Children in Iran: A Qualitative Study

Objectives The present study aimed to recognize bullying behavior in the students in Iran and analyze the perception of school teachers and parents in this regard. Materials and Methods Several semi-structured interviews and observations were conducted with four teachers and eight parents of children involved in bully/victim problems and the analysis was interpreted through established comparative evaluation methods. Results Iranian teachers and the parents perceived bullying mainly as physical and verbal attacks with little understanding of the psychological factors. They emphasized that the underlying influence of religious beliefs should also be considered in the context of bullying among Iranian society due to the strict conformance applied by parents upon their child. Conclusions Based on the outcomes of the study, it is recommended that the teachers participate in anti-bullying programs orientated to prevent bullying behaviors and develop strong supportive relationship with parents to reduce this behavior through personal contacts and interactive workshops.
Resource Allocation in Spectrum-Sharing OFDMA Femtocells With Heterogeneous Services

Femtocells are being considered a promising technique to improve the capacity and coverage for indoor wireless users. However, the cross-tier interference in the spectrum-sharing deployment of femtocells can degrade the system performance seriously. The resource allocation problem in both the uplink and the downlink for two-tier networks comprising spectrum-sharing femtocells and macrocells is investigated. A resource allocation scheme for cochannel femtocells is proposed, aiming to maximize the capacity for both delay-sensitive users and delay-tolerant users subject to the delay-sensitive users' quality-of-service constraint and an interference constraint imposed by the macrocell. The subchannel and power allocation problem is modeled as a mixed-integer programming problem, and then, it is transformed into a convex optimization problem by relaxing subchannel sharing; finally, it is solved by the dual decomposition method. Subsequently, an iterative subchannel and power allocation algorithm considering heterogeneous services and cross-tier interference is proposed for the problem using the subgradient update. A practical low-complexity distributed subchannel and power allocation algorithm is developed to reduce the computational cost. The complexity of the proposed algorithms is analyzed, and the effectiveness of the proposed algorithms is verified by simulations.
How Low Business Tax Rates Attract Multinational Headquarters: Municipality-Level Evidence from Germany

Most existing empirical evidence on the impact of profit taxation on multinational firm activity is based on cross-country data. One major drawback of such data is that countries differ not only with regard to taxes but along other dimensions which might be hard to capture by means of observable characteristics. We compile a database of more than 11,000 municipalities in Germany to analyze the sensitivity of the location decisions of foreign MNEs with respect to business tax rates which are levied directly by the municipalities. Using count data models suited for cross-sectional and panel data, we find that higher business tax rates have a negative effect on the number of foreign MNE headquarters, after controlling for other determinants of firm location decisions. On average, a one-percent reduction of the municipal business tax rate (equivalent to a decline by about 0.14 percentage points) leads to an increase in the number of headquarters of foreign MNEs by about 0.05. Hence, the average municipality needs to reduce its business tax rate by 20% to attract one foreign MNE.
Rubik's cube based private key management in wireless networks

Key management using public key cryptography is less preferable due to several limitations like relatively high computation cost, encryption of preferably short messages, complex encryption-decryption algorithms etc. So we resort to private key management technique. In order to exchange messages between nodes in a Wireless Network, secret shared cryptographic keys must be established between the nodes of the network. Key management is a challenging task in wireless networks as the hostile environment of wireless networks makes it more prone to attacks. In order to ensure safe key management, dynamic generation of keys must occur. Hence the need of this study. This paper proposes a completely novel method for key generation using the concept which is slightly based on design of the Rubik's cube. As the complexity to solve the cube is quite high, it is almost impossible for an outsider to obtain the key that is shared among nodes. Also, a node Hop Count check is provided, which reduces the possibility of procurement of the keys on node capture. The main advantage of the method suggested in this paper is that keys are not exchanged between the nodes over the network, which reduces the possibility of key capture to a great extent.
THRESHOLDS OF AUDIBILITY FOR BONE-CONDUCTION HEADSETS

Despite advantages of using headphones, including privacy and portability, headphones have one essential drawback: they cover the ears of the listener, thus deteriorating detection and localization of ambient sounds. Bone-conduction headsets leave the ears uncovered, yet maintain portability and privacy. An initial step in establishing guidelines for using these “bonephones” is taken in the present research. The input into the bonephones necessary to reach a 71% detection threshold is measured at critical band centers ranging from 150 Hz to 13500 Hz. These thresholds were measured with an open ear canal, a plugged ear canal, and a masking noise. Results were consistent with other bone-conduction threshold measurements. The utility of this information in the context of equalization for the audio presented through the bonephones is discussed.
Estimation of contact forces using a virtual force sensor

Physical human-robot collaboration is characterized by a suitable exchange of contact forces between human and robot, which can occur in general at any point along the robot structure. If the contact location and the exchanged forces were known in real time, a safe and controlled collaboration could be established. We present a novel approach that allows localizing the contact between a robot and human parts with a depth camera, while determining in parallel the joint torques generated by the physical interaction using the so-called residual method. The combination of such exteroceptive sensing and model-based techniques is sufficient, under suitable conditions, for a reliable estimation of the actual exchanged force at the contact, realizing thus a virtual force sensor. Multiple contacts can be handled as well. We validate quantitatively the proposed estimation method with a number of static experiments on a KUKA LWR. An illustration of the use of estimated contact forces in the realization of collaborative behaviors is given, reporting preliminary experiments on a generalized admittance control scheme at the contact point.
Technical Report : Endoscope Calibration and Derivation for Shape from Shading

(a) (b) (c) (d) (e) (f) (g) (h) Figure 1. Endoscope calibration setup: (a) geometric calibration (b-d) images of 5 × 4 checker board used for geometric calibration. (e) photometric calibration. (f-g) images of Macbeth color chart used for photometric calibration. The orthopedic endoscope has a single camera and one or more point light sources equipped at the tip of the scope. For this work, we use Stryker 344-71 arthroscope Vista (70 degree, 4mm), an oblique endoscope with two point light sources. The device is showed in Fig. 2. Unlike regular cameras with forward viewing, most current endoscopes are designed for oblique viewing with a tilt from the scope axis at the tip. The viewing direction can be changed by simply rotating the scope cylinder without having to move it. To increase flexibility of imaging in terms of focus and resolution, the lens system (in the cylinder) and the CCD plane (in the camera head) can be rotated with respect to one another (see Fig. 2 (b), 3 and 4 (a-b)). While they are desirable, these properties make the geometric calibration harder than in regular cameras. Yamaguchi et al. [4] calibrate an oblique scope using Tsai's model [3, 5], by attaching an optical marker to the camera head. However, since there can be a rotation between the head and the cylinder, their model is a complicated function of the rotation angle. Instead, we attach the marker on the scope cylinder and calibration turns out to be very simple. Still as an extension of Tsai's model, the geometric model illustrated in Fig. 3 can be written as: λp i = A · c T s · m T w · P w p i = R(θ) · (p i − cc) + cc (1)
The values of Mahler measures

We investigate the setM of numbers which occur as Mahler measures of integer polynomials and the subsetM of Mahler measures of algebraic numbers (that is, of irreducible integer polynomials). We prove that every number of degree d inM is the Mahler measure of a separable integer polynomial of degree at most P 1 r d=2 d r with all its roots lying in the Galois closure F of Q( ), and every unit in M is the Mahler measure of a unit in F of degree at most d bd=2c over Q. We use this to show that some numbers considered earlier by D.W. Boyd are not Mahler measures. We also investigate the set of numbers which occur as Mahler measures of both reciprocal and nonreciprocal algebraic numbers. In particular, we describe all cubic units in this set and show that the smallest Pisot number is not the measure of a reciprocal number.
Delay-based congestion control for multipath TCP

With the aid of multipath transport protocols, a multihomed host can shift some of its traffic from more congested paths to less congested ones, thus compensating for lost bandwidth on some paths by moderately increasing transmission rates on other ones. However, existing multipath proposals achieve only coarse-grained load balancing due to a rough estimate of network congestion using packet losses. This paper formulates the problem of multipath congestion control and proposes an approximate iterative algorithm to solve it. We prove that a fair and efficient traffic shifting implies that every flow strives to equalize the extent of congestion that it perceives on all its available paths.We call this result “Congestion Equality Principle”. By instantiating the approximate iterative algorithm, we develop weighted Vegas (wVegas), a delay-based algorithm for multipath congestion control, which uses packet queuing delay as congestion signals, thus achieving fine-grained load balancing. Our simulations show that, compared with loss-based algorithms, wVegas is more sensitive to changes of network congestion and thus achieves more timely traffic shifting and quicker convergence. Additionally, as it occupies fewer link buffers, wVegas rarely causes packet losses and shows better intra-protocol fairness.
Selecting a Project 's Methodology

How do we determine the need for various software processes or methodologies, and what helps us choose the appropriate one for our project? To answer these questions, we need to get to the bottom of the controversy over methodologies and discover the dimensions along which they vary. This article describes a framework for methodology differentiation, principles for methodology selection, and project experiences using these ideas.
Should Reviewers Stand in the Shoes of Review Readers? The Role of Perspective Taking in Online Reviews

Reviewers can describe their experience with a product or service from their own perspective or from the perspective of review readers (or prospective consumers). The present paper investigates how and why reviewers’ perspective taking may influence review readers’ perception of review helpfulness. Drawing on the perspective taking literature, we posit that reviews that take (vs. do not take) the perspective of prospective consumers are more likely to be perceived helpful, and that this effect can be explained through greater reviewer attractiveness perceived by consumers. In Study 1, real app reviews from Apple’s App Store were collected to examine the relationship between perspective taking and review helpfulness. In Study 2, experimental methodology was utilized to identify and explain the effect of perspective taking in terms of perceived reviewer attractiveness. The findings provide converging evidence for the important role of perspective taking in online reviews.
The ALOCOM Framework: Towards Scalable Content Reuse

This paper presents a framework that enables flexible content reuse. Unlike the usual practice where document components, such as images, definitions, text fragments, tables or diagrams, are assembled manually through copy-and-paste, the framework enables on-the-fly access and reuse. Retrieval of relevant components is enabled by automatic decomposition of legacy documents and storage of individual components, enriched with metadata. Furthermore, the automatic assembly of these components in mainstream authoring tools is supported. The paper describes the framework and its current support for re-assembling PowerPoint, Wikipedia and SCORM components in authoring tools. In addition, an evaluation is presented that aims to assess the effectiveness and efficiency of such content reuse for presentations.
An approximate Bayesian fundamental frequency estimator

Joint fundamental frequency and model order estimation is an important problem in several applications such as speech and music processing. In this paper, we develop an approximate estimation algorithm of these quantities using Bayesian inference. The inference about the fundamental frequency and the model order is based on a probability model which corresponds to a minimum of prior information. From this probability model, we give the exact posterior distributions on the fundamental frequency and the model order, and we also present analytical approximations of these distributions which lower the computational load of the algorithm. By use of simulations on both a synthetic signal and a speech signal, the algorithm is demonstrated to be more accurate than a state-of-the-art maximum likelihood-based method.