Miracle-dz/UniFAR-FTUs huggingface dataset:
SPINAL PAIN , SECTION 1 : SPINAL AND RADICULAR PAIN SYNDROMES Note on Arrangements

In this section, both spinal pain and radicular pain are considered. Definitions of spinal pain and related phenomena are offered first, followed by principles related to spinal pain and a comment on radicular pain and radiculopathy. Next there follows a detailed schedule of classifications of spinal pain affecting the cervical and thoracic regions. This schedule is intended to be comprehensive and includes numerous categories and coded items that are not described. Other elements, the more common and chronic with respect to pain, are described in detail later in the body of the text according to the usual pattern. The coding system and schedules provide categories for both spinal pain and radicular pain when they are associated with each other or when they occur separately. A diagnosis for each should be made as required with the suffix S or R as appropriate, and C when both occur. Subsequent to the schedule of classifications for the cervical and thoracic regions a more detailed description of radicular pain and radiculopathy is provided. The schedule of classifications relating to lumbar, sacral, and coccygeal, spinal, and radicular pains is presented later in the text, after the incorporation of material dealing with other syndromes in the upper limbs, thorax, abdomen, and perineum.
Chapter 1 The Cognitive Anatomy and Functions of Expectations Revisited

Some years ago (in 2003) I wrote my first paper in collaboration with Cristiano Castelfranchi who at that time was the supervisor of my Master project in Cognitive Science. The work was aimed at providing a logical formalization of the notion of expectation and of expectation-based emotions such as hope, fear, disappointment and relief. In this paper I will revisit and extend the analysis we did in 2003. I will propose a refinement of the notion of expectation by formalizing its two primitive components: the value of the goal and the strength of the belief. Thanks to this refinement, I will provide a formal analysis of the intensity of hope and fear.
Classification of Dance Motions with Depth Cameras Using Subsequence Dynamic Time Warping

This paper proposes a method for classifying 3D dance motions especially selected from Korean POP (K-POP) dance performance, which is a key technique for the dance coaching contents and choreography retrieval system. Compared to actions addressed in daily life and existing games, K-POP dance motions are much more dynamic and vary substantially according to the performers. To cope with the variation of the amplitude of pose, we present a practical pose descriptor based on relative rotations between two body joints in the spherical coordinate system. As a method to measure similarity between two incomplete motion sequences, subsequence Dynamic Time Warping (DTW) algorithm is explored that supports partial matches. For the tests, 200 popular dance segments are gathered from 100 K-POP songs by utilizing the Kinect for Windows v2 sensor of Microsoft. The experimental results show that our representation and matching method can achieve an excellent performance in the classification of complex dance motions.
Curvature Singularities: the Good, the Bad, and the Naked

Necessary conditions are proposed for the admissibility of singular classical solutions with 3+1-dimensional Poincare invariance to five-dimensional gravity coupled to scalars. Finite temperature considerations and examples from AdS/CFT support the conjecture that the scalar potential must remain bounded above for a solution to be physical. Having imposed some restrictions on naked singularities allows us to comment on a recent proposal for solving the cosmological constant problem.
Social networking feeds: recommending items of interest

The success of social media has resulted in an information overload problem, where users are faced with hundreds of new contributions, edits and communications at every visit. A prime example of this in social networks is the news or activity feeds, where the actions (friending, commenting, photo sharing, etc) of friends on the network are presented to users in order to inform them of the network activity. In this work we endeavour to reduce the burden on individuals of identifying interesting updates in social network news feeds by automatically identifying and recommending relevant items to individuals where item relevance is based on the observed interactions of the individual with the social network. The results of our offline study show that combining short term interest models, exploiting previous viewing behavior of users, and long-term models, exploiting previous viewing of network actions, was the best predictor of feed item relevance.
Local Orthogonal Discriminate Bases to Hybrid SVM/Self-adaptive HMM Classifier for Discrete Word Speech Recognition

This research addresses speech recognition with discrete words and speaker independent by using hybrid support vector machine/self-adaptive hidden Markov model (SVM/self-adaptive HMM) classifier. Our proposed method includes two main units: preprocessing unit, and classification unit. In the first unit speech wave is converted into frames and then extracted time-frequency relevant features in the way that maximizing relative entropy of time-frequency energy distribution among frames. In the second unit a one-versus-one self-adaptive HMM calculates words likelihoods to each existed class and then a support vector machine (SVM) takes all class likelihood as an input vector and classifies it into proper class. To validate our proposed method, we test it on our IAUM dataset that contains Persian digits uttered by Persian speakers. The results are compared with similar method using original HMM
Music mood classification based on lyrical analysis of Hindi songs using Latent Dirichlet Allocation

For over a decade now, due to the introduction of UTF-8 encoding, the digitization of Hindi content has increased rapidly because of which Hindi-music has accomplished popularity on the web. The focus is to identify the emotion, a person is experiencing while listening to a song track. The aim of this research work is to analyze the lyrics of Hindi-language based songs, in order to detect the mood of the listener. We used unigram and term-frequency as the main features. The songs were reduced to a level where only relevant words will be used for mood-detection. We employ unsupervised machine learning namely topic-modeling (Latent Dirichlet Allocation model) for mining the mood out of every song in the corpus. We created our own dataset of 1900 songs consisting of Bollywood tracks, bhajans (spiritual prayers) and ghazals. A mood taxonomy is used to distinguish songs into Happy or Sad. Data is applied to LDA model to discover the hidden emotions within each song. At the end of experimentation, we compare the results with manually pre-annotated dataset for validation purpose and observe good results.
Relationship between Self-Esteem and Aggressive Behaviour among Youths

1 Associate Professor, Head of Department, Department of Psychiatry, Jawaharlal Nehru Institute of Medical Sciences (JNIMS), Imphal, Manipur-795001 2 Clinical Psychologist (M.phil – Clinical psychology) *Corresponding Author Ngairangbam Zevina Chanu Email: zevina.ng2@gmail.com, Mobile no. 7085927987 Abstract The present study aims to find out the relationship between self-esteem and aggression among youths in Manipur. A sample of 300 participants was selected from the colleges of Imphal-East and Imphal-West areas of Manipur, out of which 150 cases were males and the other 150 cases were females. Students within the age group of 18-29 years, graduate and above and who are willing to give consent for participating in the study were selected. Rosenberg Self-Esteem scale and The Aggression Questionnaire by Buss and Perry (1992) were used for measuring self-esteem and aggression, respectively. The finding of the study shows that, in the subscales of aggression, physical aggression and hostility were found to be negatively significant with self-esteem. But, the subscales such as verbal aggression and anger did not show correlation with self-esteem. However, the total score of aggression was found to have significant negative correlation with self-esteem.
Regulation of cytotoxin expression by converging eukaryotic‐type and two‐component signalling mechanisms in Streptococcus agalactiae

Signal transducing mechanisms are essential for regulation of gene expression in both prokaryotic and eukaryotic organisms. Regulation of gene expression in eukaryotes is accomplished by serine/threonine and tyrosine kinases and cognate phosphatases. In contrast, gene expression in prokaryotes is controlled by two‐component systems that comprise a sensor histidine kinase and a cognate DNA binding response regulator. Pathogenic bacteria utilize two‐component systems to regulate expression of their virulence factors and for adaptive responses to the external environment. We have previously shown that the human pathogen Streptococcus agalactiae (Group B Streptococci, GBS) encodes a single eukaryotic‐type serine/threonine kinase Stk1, which is important for virulence of the organism. In this study, we aimed to understand how Stk1 contributes to virulence of GBS. Our results indicate that Stk1 expression is important for resistance of GBS to human blood, neutrophils and oxidative stress. Consistent with these observations, Stk1 positively regulates transcription of a cytotoxin, β‐haemolysin/cytolysin (β‐H/C) that is critical for survival of GBS in the bloodstream and for resistance to oxidative stress. Interestingly, positive regulation of β‐H/C by Stk1 requires the two‐component regulator CovR. Further, we show that Stk1 can negatively regulate transcription of CAMP factor in a CovR‐dependent manner. As Stk1 phosphorylates CovR in vitro, these data suggest that serine/threonine phosphorylation impacts CovR‐mediated regulation of GBS gene expression. In summary, our studies provide novel information that a eukaryotic‐type serine/threonine kinase regulates two‐component‐mediated expression of GBS cytotoxins.
Kinematically optimised predictions of object motion

Predicting the motions of rigid objects under contacts is a necessary precursor to planning of robot manipulation of objects. On the one hand physics based rigid body simulations are used, and on the other learning approaches are being developed. The advantage of physics simulations is that because they explicitly perform collision checking they respect kinematic constraints, producing physically plausible predictions. The advantage of learning approaches is that they can capture the effects on motion of unobservable parameters such as mass distribution, and frictional coefficients, thus producing more accurate predicted trajectories. This paper shows how to bring together the advantages of both approaches to achieve learned simulators of specific objects that outperform previous learning approaches. Our approach employs a fast simplified collision checker and a learning method. The learner predicts trajectories for the object. These are optimised post prediction to minimise interpenetrations according to the collision checker. In addition we show that cleaning the training data prior to learning can also improve performance. Combining both approaches results in consistently strong prediction performance. The new simulator outperforms previous learning based approaches on a single contact push manipulation prediction task. We also present results showing that the method works for multi-contact manipulation, for which rigid body simulators are notoriously unstable.
The application of transport theory to visualization of 3D scalar data fields

The author describes a visualization model for three-dimensional scalar data fields based on linear transport theory. The concept of virtual particles for the extraction of information from data fields in introduced. The role of different types of interaction of the data field with those particles such as absorption, scattering, source and color shift are discussed and demonstrated. Special attention is given to possible tools for the enhancement of interesting data features. Random texturing can provide visual insights as to the magnitude and distribution of deviations of related data fields, e.g., originating from analytic models, and measurements, or in the noise content of a given data field. Hidden symmetries of a data set can often be identified visually by allowing it to interact with a preselected beam of physical particles with the attendant appearance of characteristic structural effects such as channeling. <<ETX>>
Thermospheric mass density variations during geomagnetic storms and a prediction model based on the merging electric field

With the help of four years (2002–2005) of CHAMP accelerometer data we have investigated the dependence of low and mid latitude thermospheric density on the merging electric field, Em, during major magnetic storms. Altogether 30 intensive storm events (Dstmin <? 100 nT) are chosen for a statistical study. In order to achieve a good correlation Em is preconditioned. Contrary to general opinion, Em has to be applied without saturation effect in order to obtain good results for magnetic storms of all activity levels. The memory effect of the thermosphere is accounted for by a weighted integration of Em over the past 3 h. In addition, a lag time of the mass density response to solar wind input of 0 to 4.5 h depending on latitude and local time is considered. A linear model using the preconditioned Em as main controlling parameter for predicting mass density changes during magnetic storms is developed: ? =0.5Em+? amb, where ? amb is based on the mean density during the quiet day before the storm. We show that this simple relation predicts all storm-induced mass density variations at CHAMP altitude fairly well especially if orbital averages are considered.
Adaptive and relaxed visibility-based PRM

In this paper we introduce a new sampler for robotic motion planning using the probabilistic roadmap approach. We improve the previously-introduced visibility-based sampler with two heuristics. First, we adopt a space decomposition approach can guide the sampler by identifying promising areas of the configuration space where milestones can be efficiently generated. While the original visibility-based sampler uses a very selective criterion to determine whether a sampled configuration point is to be accepted as a new milestone, we use a relaxed criterion that can significantly reduce the computational cost in the roadmap construction phase while increasing the size of the roadmap only mildly
Local State in Hoare Logic for Imperative Higher-Order Functions

We introduce an extension of Hoare logic for imperative higherorder functions with local state and full aliasing. Local state may be generated dynamically and exported outside its scope, may store higher-order functions, and may be used to construct complex shared mutable data structures. The logic is built on the authors’ previous study on Hoare logics for imperative higher-order functions and aliasing [5, 15–17]. Complex behaviour induced by local state is captured with a minimal syntax extension: a first order predicate which asserts reachability of reference names. After establishing soundness and observational completeness, we explore the logic’s descriptive and reasoning power with non-trivial examples, offering effective reasoning principles for a general class of higher-order behaviours in the presence of local state.
Multichannel and Wideband Power Amplifier Design Methodology for 4G Communication Systems Based on Hybrid Class-J Operation

A methodology for the design of multichannel, wideband, highly efficient hybrid Class-J power amplifiers for fourth-generation (4G) communication transmitters is proposed. The design procedure is based on the automatic generation and evaluation of a vast number of output matching networks of the same topology but different dimensions, with respect to efficiency, output power, and linearity. The approach can find application in the management of the efficiency/linearity/bandwidth tradeoff in amplifier design. In this paper, two matching network architectures have been considered. One multistubbed network and a stepped-impedance microstrip line network. The approach has been validated through the design, simulation, and measurement of two power amplifiers realized using the aforementioned procedure. The first amplifier covers 1.6-2.2 GHz (31.6% fractional bandwidth) with 55%-68% drain efficiency at the 2-dB compression point and worst case adjacent channel power ratio (ACRP) and error vector magnitude (EVM) of - 21.8 dBc and 8.35%, respectively, over the bandwidth. The second covers 0.5-1.8 GHz (113% fractional bandwidth) with 50%-69% drain efficiency at the 2-dB compression point and worst case ACRP of - 27.5 dBc and EVM of 4.22%. Both amplifiers are based on a commercial, packaged 10-W GaN HEMT transistor.
Effects of dynamic office chairs on trunk kinematics, trunk extensor EMG and spinal shrinkage

Seated work has been shown to constitute a risk factor for low-back pain. This is attributed to the prolonged and monotonous low-level mechanical load imposed by a seated posture. To evaluate the potential health effects with respect to the low back of office chairs with a movable seat and back rest, trunk kinematics, erector spinae EMG, spinal shrinkage and local discomfort were assessed in 10 subjects performing simulated office work. On three separate occasions subjects performed a 3 h task consisting of word processing, computer-aided design and reading. Three chairs were used, one with a fixed seat and back rest and two dynamic chairs, one with a seat and back rest movable in a fixed ratio with respect to each other, and one with a freely movable seat and back rest. Spinal shrinkage measurements showed a larger stature gain when working on the two dynamic chairs as compared with working on the chair with fixed seat and back rest. Trunk kinematics and erector spinae EMG were strongly affected by the task performed but not by the chair type. The results imply that dynamic office chairs offer a potential advantage over fixed chairs, but the effects of the task on the indicators of trunk load investigated were more pronounced than the effects of the chair.
Function-Orientated Structural Analysis of the Proximal Human Femur

In his model of the biomechanics of the proximal human femur, Friedrich Pauwels assumes a resultant force acting on the femoral head that is created by the partial body weight and the force of the abductor muscles inserting at the greater trochanter. This model suggests a tensile force in the region of the greater trochanter. An exact examination of the muscle insertions at the greater trochanter resulted in a contrasting hypothesis assuming a local compression stress in the region of the greater trochanter. The aim of this study was to examine which hypothesis is favored by the internal architecture of the proximal femur. Based on the architectural software Allplan®, we performed an extended analysis of the trabecular structure within the proximal femur using CT scans of 10 human cadaver femora altogether. According to our results, both the medial and the trochanteric trabecular systems are orientated approximately perpendicular to the arcuate trabecular system [angles between systems ranging from 84.6 to 93.0° (mean angle 90.7°) and from 80.9 to 86.5°, (mean angle 84.9°), respectively]; furthermore, the medial trabecular system is orientated perpendicular to the epiphysis of the femoral head (mean of angles: 94.7°). The biomechanical interpretation of these results strongly supports the idea of compressive stress in the region of the greater trochanter and makes a predominant tensile force of the abductor muscles highly unlikely.
Like Doktorvater, like Son? Tracing Role Model Learning in the Evolution of German Laser Research

Summary We trace individual-level learning and knowledge transfer in public research by matching about 5,000 doctoral dissertations and their advisors over the full history of German laser research. We study the number of laser-related dissertations per advisor, publication and patent outputs of advisors and doctoral students, as well as the likelihood that former students started laser firms or attained professorships. Our results suggest a substantial relevance of non-codified knowledge and role model learning in public research. There is little evidence of pronounced barriers to entry into laser research.
Hepatitis B and Hepatitis C Seroprevalence in the Center of Sanliurfa Province From Southeastern Anatolia Region and Related Risk Factors

Objective: The aim of this study was to evaluate the seroprevalence of HBV and HCV and related risk factors in Sanliurfa, a province of southeastern Anatolia. Material and Methods: This cross-sectional study was conducted between April and May, 2008 in Sanliurfaa#39;s city center. A community-based representative sample (N=1070) was randomly selected using cluster sampling from the catchment areas served by 19 different primary healthcare centers. A questionnaire evaluating demographic information and probable risk factors for HBV and HCV was administered, and HBsAg and anti-HCV markers were analyzed from blood samples. Results: Among the 1070 individuals who participated in the study, 33.1% were male (n=354) and 66.9% female (n=716). The average age was 35.4aplusmn;13.5 (15-90) years. The seroprevalence of HBsAg positivity was 4.2% (n=45), while anti-HCV seropositivity was found to be 1.0% (n=11). Among participants who previously suffered a known hepatitis infection or who reported a family history of hepatitis, the HBsAg positivity was found to be higher (palt;0.05). There was no statistically significant difference between HCV transmission risk factors and anti-HCV positivity. Conclusion: This is the first hepatitis seroprevalence study in central Sanliurfa and demonstrated moderate HBV infection endemicity. Turkish Baslik: Guneydogu Anadolu Bolgesinden Şanliurfa Il Merkezinde Hepatit B ve Hepatit C Seroprevalansi ve Iliskili Risk Faktorleri Anahtar Kelimeler: HBsAg; Anti-HCV; seroprevalans; Şanliurfa Amac: Bu calismada Guneydogu Anadolu Bolgesinde yer alan Şanliurfaa#39;da HBV ve HCV seroprevalansinin ve iliskili risk faktorlerinin saptanmasi amaclandi. Gerec ve Yontemler: Kesitsel tipteki bu arastirma, Nisan 2008-Mayis 2008 tarihleri arasinda Şanliurfa il merkezinde yapildi. Kume ornekleme yontemi ile 19 farkli saglik ocagi bolgesinden toplumu temsil eden katilimcilar (N=1070) randomize secildi. Katilimcilara demografik ozelliklerini ve HBV ile HCV bulasmasinda risk olusturabilecek durumlari irdeleyen bir anket uygulandi ve HBsAg ve anti-HCV testleri yapildi. Bulgular: Arastirmaya dahil edilen 1070 kisinin %33.1a#39;i (n=354) erkek, %66.9a#39;u (n=716) kadin idi. Katilimcilarin yas ortalamasi 35.4aplusmn;13.5 (15-90) yil idi. HBsAg seropozitifligi %4.2 (n=45), anti-HCV seropozitifligi ise %1.0 (n=11) olarak bulundu. Katilimcilardan sarilik gecirme oykusu verenlerde ve ailede sarilik olanlarda, olmayanlara gore HBsAg pozitifligi yuksek saptandi (palt;0.05). HCV bulasina yonelik risk faktorlerinin anti-HCV pozitifligine etkisi istatistiksel olarak anlamli bulunmadi. Sonuc: Bu calisma, Şanliurfa il merkezinden yapilan ilk hepatit seroprevalans calismasidir ve HBV enfeksiyonu sikligi acisindan orta endemisite gostermektedir.