Miracle-dz/UniFAR-FTUs huggingface dataset:
Chemosensitivity and perception of dyspnea in patients with a history of near-fatal asthma.

BACKGROUND Many deaths from attacks of asthma may be preventable. However, the difficulty in preventing fatal attacks is that not all the pathophysiologic risk factors have been identified. METHODS To examine whether dyspnea and chemosensitivity to hypoxia and hypercapnia are factors in fatal asthma attacks, we studied 11 patients with asthma who had had near-fatal attacks, 11 patients with asthma who had not had near-fatal attacks, and 16 normal subjects. Their respiratory responses to hypoxia and hypercapnia, determined by the standard rebreathing technique while the patients were in remission, were assessed in terms of the slopes of ventilation and airway occlusion pressure as a function of the percentage of arterial oxygen saturation and end-tidal carbon dioxide tension, respectively. The perception of dyspnea was scored on the Borg scale during breathing through inspiratory resistances ranging from 0 to 30.9 cm of water per liter per second. RESULTS The mean (+/- SD) hypoxic ventilatory response (0.14 +/- 0.12 liter per minute per percent of arterial oxygen saturation) and airway occlusion pressure (0.05 +/- 0.05 cm of water per percent of arterial oxygen saturation) were significantly lower in the patients with near-fatal asthma than in the normal subjects (0.60 +/- 0.35, P < 0.001, and 0.16 +/- 0.08, P < 0.001, respectively) and the patients with asthma who had not had near-fatal attacks (0.46 +/- 0.29, P = 0.003, and 0.15 +/- 0.09, P = 0.004). The Borg score was also significantly lower in the patients with near-fatal asthma than in the normal subjects, and their lower hypoxic response was coupled with a blunted perception of dyspnea. CONCLUSIONS Reduced chemosensitivity to hypoxia and blunted perception of dyspnea may predispose patients to fatal asthma attacks.
Methadone-Related Overdose Deaths in a Liberal Opioid Maintenance Treatment Programme

Background/Aims: Increasing rates of overdose deaths involving opioid maintenance treatment (OMT) medications and particularly methadone have been observed concurrently with the implementation of liberal OMT strategies (i.e. minimum of control and high doses prescribed). This study examined methadone-related overdose deaths in a liberal OMT programme. Methods: Drug-overdose deaths (n = 130) with detection of methadone in Copenhagen, Aarhus, and Odense Municipality, Denmark, during the period 2008-2011 were identified from a registry. Cases with and without prescribed methadone as OMT were compared. Treatment delivery strategy among OMT-prescribed methadone cases was investigated. Results: Methadone was detected in 130 overdose deaths (71.4% of all overdose deaths). Among these, 63.1% were receiving methadone maintenance treatment. Of these, 79.3% had co-detection of benzodiazepines. Concomitant detection of heroin, non-prescribed benzodiazepines, and younger age were associated with having non-prescribed methadone in the toxicological findings (adjusted OR 3.1, 4.0 and 9.5, respectively). Of the decedents, 43.8% were prescribed a higher methadone dose than recommended (>120 mg daily), of which 80.0% did not have supervised intake of methadone. Conclusions: Liberal OMT access does not necessarily prevent overdose deaths overall. Prescription of higher doses of methadone combined with benzodiazepines may result in an increased risk of overdose for individuals in as well as outside OMT.
Novel in-wheel axial-flux segmented switched reluctance motor

In this paper a novel axial-flux segmented rotor switched reluctance motor (AFSSRM) with a stator sandwiched by two rotors with a particular form of the segments is presented. The machine has magnetic short paths with no flux reversal and the active magnetic parts are made of soft magnetic composites. An in-wheel AFSSRM, specially intended for direct drive of light motorcycles, is designed. Electromagnetic analysis of the AFSSRM is carried out using 3D finite element. Matlab-Simulink simulations of the whole in-wheel AFSSRM drive are used to verify its behavior.
Riemann's Hypothesis and tests for primality

The purpose of this paper is to present new upper bounds on the complexity of algorithms for testing the primality of a number. The first upper bound is 0(n1/7); it improves the previously best known bound of 0(n1/4) due to Pollard [11]. The second upper bound is dependent on the Extended Riemann Hypothesis (ERH): assuming ERH, we produce an algorithm which tests primality and runs in time 0((log n)4) steps. Thus we show that primality is testable in time a polynomial in the length of the binary representation of a number. Finally, we give a partial solution to the relationship between the complexity of computing the prime factorization of a number, computing the Euler phi function, and computing other related functions.
Screening for psychological distress and vulnerability factors in women at increased risk for breast cancer: A review of the literature

Women with a family history of breast cancer are at significantly increased risk of psychological distress, and there are potential benefits to routine psychological screening in women attending familial cancer clinics. Standard psychological screening measures may have limited sensitivity and specificity. Sensitivity and specificity of screening may be improved if screening includes additional routine assessment of empirically demonstrated risk factors for psychological distress specific to this population. To this end, we undertook a systematic literature review to identify demonstrated risk factors for psychological distress amongst high-risk women. Published studies of unaffected women with a family history of breast cancer were included if they: assessed sociodemographic, family history or psychological correlates of psychological distress; and included psychological and emotional outcomes as primary outcome measures. A total of 16 studies met the inclusion criteria. Several factors are empirically demonstrated risk factors in this population: (i) overestimating one's risk of developing breast cancer by more than 50%; (ii) mother's diagnosis with breast cancer; (iii) death of parent from breast cancer; (iv) having acted as caregiver for mother with breast cancer; and (v) having experienced a breast-cancer-related life event in the past year. A screening tool that incorporates these risk factors is presented and its potential role in familial cancer clinics is discussed.
Altered hypothalamic functional connectivity in cluster headache: a longitudinal resting-state functional MRI study

Background Neuroimaging studies implicate hypothalamic dysfunction in the pathogenesis of cluster headache (CH). Disruptions in non-traditional pain processing areas, including the cerebellum and visual cortex, have also been reported in CH. It is unknown whether the hypothalamus interacts significantly with these areas, and whether any such interactions vary between the ‘in-bout’ and ‘out-of-bout’ periods in CH. This study aimed to investigate the resting-state functional connectivity (FC) of the hypothalamus of patients with CH. Methods Using 3-T functional MRI, we conducted a seed-based resting-state intrinsic FC analysis of the hypothalamus in 18 episodic CH patients during in-bout and out-of-bout periods, and in 19 healthy controls. Correlations between hypothalamic FC and clinical variables were also assessed. Results Compared to controls, CH patients showed hypothalamic FC changes with the medial frontal gyrus and occipital cuneus during in-bout and out-of-bout periods. Compared to out-of-bout scans, in-bout scans revealed decreased hypothalamic FC with the medial frontal gyrus, precuneus, and cerebellar areas (tonsil, declive and culmen). Additionally, the annual bout frequency correlated significantly with the hypothalamic FC in the cerebellar culmen (r=−0.576, p=0.02) and cerebellar declive (r=−0.522, p=0.038). Conclusions Our findings suggest that in CH, FC differences between the hypothalamus and its regional distribution extends beyond traditional pain processing areas, primarily to the cerebellar, frontal and occipital areas. These changes may be important and associated with CH pathophysiology.
Body Composition in Type 2 Diabetes: Change in Quality and not Just Quantity that Matters

Background: Deranged body fat and muscle mass are aftermaths of uncontrolled diabetes. Anthropometric methods like body mass index (BMI) do not give qualitative inferences like total body fat (TBF), visceral fat (VF) or subcutaneous fat (SF) that can be given by bio-electrical impedance analysis (BIA). We studied body composition of type 2 diabetics in comparison to controls matched by age-sex, weight and BMI separately. Methods: Seventy-eight under-treatment type 2 diabetics of either sex with known glycemic and lipidemic control and equal number of controls with three patterns of matching were taken from our city. We derived parameters of body composition in both groups by Omron Karada Scan (Model HBF-510, China), using the principle of tetra poplar BIA and compared them for statistical significance. Results: We found significantly more SF (30.47% ± 7.73%), VF (11.94% ± 4.97%) and TBF (33.96% ± 6.07%) and significantly lesser skeletal muscle mass (23.39% ± 4.49%) in type 2 diabetics as compared to controls, persisting even after matching with weight or BMI. On assessing qualitatively, the risk of high VF, high TBF, low skeletal muscle mass was significantly high in type 2 diabetics, which were 10.41, 3.01, 9.21 respectively for comparable BMI and 6.78, 3.51, 11.93 respectively for comparable weight. Conclusions: BIA reveals that type 2 diabetics have more ectopic fat on the expense of skeletal muscle that persists even after matching by weight or BMI, both quantitatively and qualitatively. Measurement of body composition can be included as a primary care strategy to motivate lifestyle modifications while managing metabolic derangements of type 2 diabetes.
A Method for Sharing Traffic Jam Information using Inter-Vehicle Communication

In this paper, we propose a method for cars to autonomously and cooperatively collect traffic jam statistics to estimate arrival time to destination for each car using inter-vehicle communication. In the method, the target geographical region is divided into areas, and each car measures time to pass through each area. Traffic information is collected by exchanging information between cars using inter-vehicle communication. In order to improve accuracy of estimation, we introduce several mechanisms to avoid same data to be repeatedly counted. Since wireless bandwidth usable for exchanging statistics information is limited, the proposed method includes a mechanism to categorize data, and send important data prior to other data. In order to evaluate effectiveness of the proposed method, we implemented the method on a traffic simulator NETSTREAM developed by Toyota Central R&D Labs, conducted some experiments and confirmed that the method achieves practical performance in sharing traffic jam information using inter-vehicle communication
A 2.5-V 10-b 120-MSample/s CMOS pipelined ADC based on merged-capacitor switching

This work describes a 10-b multibit-per-stage pipelined CMOS analog-to-digital converter (ADC) incorporating the merged-capacitor switching (MCS) technique. The proposed MCS technique improves the signal processing speed and resolution of the ADC by reducing the required number of unit capacitors by half in comparison to a conventional ADC. The ADC resolution based on the proposed MCS technique can be extended further by employing a commutated feedback-capacitor switching (CFCS) technique. The prototype ADC achieves better than 53-dB signal-to-noise-and-distortion ratio (SNDR) at 120 MSample/s and 54-dB SNDR and 68-dB spurious-free dynamic range (SFDR) for input frequencies up to Nyquist at 100 MSample/s. The measured differential and integral nonlinearities of the prototype are within /spl plusmn/0.40 LSB and /spl plusmn/0.48 LSB, respectively. The ADC fabricated in a 0.25-/spl mu/m CMOS occupies 3.6 mm/sup 2/ of active die area and consumes 208 mW under a 2.5-V power supply.
REAL-TIME ANIMATION OF INTERACTIVE AGENTS: SPECIFICATION AND REALIZATION

Embodied agents are a powerful paradigm for current and future multimodal interfaces yet require high effort and expertise for their creation, assembly, and animation control. Therefore, open animation engines and high-level control languages are required to make embodied agents accessible to researchers and developers. We present EMBR, a new real-time character animation engine that offers a high degree of animation control via the EMBRScript language. We argue that a new layer of control, the animation layer, is necessary to keep the higher-level control layers (behavioral/functional) consistent and slim while allowing a unified and abstract access to the animation engine (e.g., for the procedural animation of nonverbal behavior). We also introduce new concepts for the high-level control of motion quality (spatial/temporal extent, power, fluidity). Finally, we describe the architecture of the EMBR engine, its integration into larger project contexts, and conclude with a concrete application.
Hyperspectral Imaging and Analysis for Sparse Reconstruction and Recognition

This thesis proposes spatio-spectral techniques for hyperspectral image analysis. Adaptive spatio-spectral support and variable exposure hyperspectral imaging is demonstrated to improve spectral reflectance recovery from hyperspectral images. Novel spectral dimensionality reduction techniques have been proposed from the perspective of spectral only and spatio-spectral information preservation. It was found that the joint sparse and joint group sparse hyperspectral image models achieve lower reconstruction error and higher recognition accuracy using only a small subset of bands. Hyperspectral image databases have been developed and made publicly available for further research in compressed hyperspectral imaging, forensic document analysis and spectral reflectance recovery.
A combined KFDA method and GUI realized for face recognition

Traditional face recognition methods such as Principal Components Analysis(PCA), Independent Component Analysis(ICA) and Linear Discriminant Analysis(LDA) are linear discriminant methods, but in the real situation, a lot of problems can't be linear discriminated; therefore, researchers proposed face recognition method based on kernel techniques which can transform the nonlinear problem of inputting space into the linear problem of high dimensional space. In this paper, we propose a recognition method based on kernel function which combines kernel Fisher Discriminant Analysis(KFDA) with kernel Principle Components Analysis(KPCA) and use typical ORL(Olivetti Research Laboratory) face database as our experimental database. There are four key steps: constructing feature subspace, image projection, feature extraction and image recognition. We found that the recognition accuracy has been greatly improved by using nonlinear identification method and combined feature extraction methods. We use MATLAB software as the platform, and use the GUI to demonstrate the process of face recognition in order to achieving human-computer interaction and making the process and result more intuitive.
High-Intensity Intermittent Exercise and its Effects on Heart Rate Variability and Subsequent Strength Performance

Prupose: To investigate the effects of a 5-km high-intensity interval exercise (HIIE) on heart rate variability (HRV) and subsequent strength performance. Methods: Nine trained males performed a control session composed of a half-squat strength exercise (4 × 80% of one repetition maximum—1 RM) in isolation and 30-min, 1-, 4-, 8-, and 24-h after an HIIE (1-min at the velocity peak:1-min passive recovery). All experimental sessions were performed on different days. The maximum number of repetitions (MNR) and total weight lifted (TWL) during the strength exercise were registered in all conditions; in addition, prior to each session, HRV were assessed [beat-to-beat intervals (RR) and log-transformed of root means square of successive differences in the normal-to-normal intervals (lnRMSSD)]. Results: Performance in the strength exercise dropped at 30-min (31%) and 1-h (19%) post-HIIE concomitantly with lower values of RR (781 ± 79 ms; 799 ± 134 ms, respectively) in the same recovery intervals compared to the control (1015 ± 197 ms). Inferential analysis did not detect any effect of condition on lnRMSSD, however, values were lower after 30-min (3.5 ± 0.4 ms) and 1-h (3.3 ± 0.5 ms) with moderate and large effect sizes (0.9 and 1.2, respectively) compared with the control condition (3.9 ± 0.4 ms). Conclusion: Both RR and lnRMSSD seem to be associated with deleterious effects on strength performance, although further studies should be conducted to clarify this association.
Sparse Linear Programming via Primal and Dual Augmented Coordinate Descent

Over the past decades, Linear Programming (LP) has been widely used in different areas and considered as one of the mature technologies in numerical optimization. However, the complexity offered by state-of-the-art algorithms (i.e. interior-point method and primal, dual simplex methods) is still unsatisfactory for problems in machine learning with huge number of variables and constraints. In this paper, we investigate a general LP algorithm based on the combination of Augmented Lagrangian and Coordinate Descent (AL-CD), giving an iteration complexity of O((log(1/∊))2) with O(nnz(A)) cost per iteration, where nnz(A) is the number of non-zeros in the m x n constraint matrix A, and in practice, one can further reduce cost per iteration to the order of non-zeros in columns (rows) corresponding to the active primal (dual) variables through an active-set strategy. The algorithm thus yields a tractable alternative to standard LP methods for large-scale problems of sparse solutions and nnz(A) ≪ mn. We conduct experiments on large-scale LP instances from l1 -regularized multi-class SVM, Sparse Inverse Covariance Estimation, and Nonnegative Matrix Factorization, where the proposed approach finds solutions of 10-3 precision orders of magnitude faster than state-of-the-art implementations of interior-point and simplex methods.1
Antigen-Chip Technology for Accessing Global Information about the State of the Body

Traditionally, immunologic diagnosis has been based on an attempt to correlate each disease with a specific immune reactivity, such as an antibody or a T-cell response to a single antigen specific for the disease entity. The state of the body, however, appears to be encoded by the immune system in collectives of reactivities and not by single reactivities. Here we describe our use of microarray technology and informatics to develop an antigen chip capable of detecting global patterns of antibodies binding to hundreds of antigens simultaneously. The patterns fashion diagnostic signatures.
Maximum a posteriori linear regression (MAPLR) variance adaptation for continuous density HMMS

In this paper, the theoretical framework of maximum a posteriori linear regression (MAPLR) based variance adaptation for continuous density HMMs is described. In our approach, a class of informative prior distribution for MAPLR based variance adaptation is identified, from which the close form solution of MAPLR based variance adaptation is obtained under its EM formulation. Effects of the proposed prior distribution in MAPLR based variance adaptation are characterized and compared with conventional maximum likelihood linear regression (MLLR) based variance adaptation. These findings provide a consistent Bayesian theoretical framework to incorporate prior knowledge in linear regression based variance adaptation. Experiments on large vocabulary speech recognition tasks were performed. The experimental results indicate that significant performance gain over the MLLR based variance adaptation can be obtained based on the proposed approach.
The child custody evaluation: Issues and trends

Custody disputes are often the crisis point in the divorcing process and the numbers of contested custody cases are increasing. Mental health professionals are being called upon to provide evaluations of these families more frequently than ever. This article focuses on how to perform child custody evaluations. It touches on the highly troublesome cases where accusations of abuse and alcoholism have been made, and how to convey to attorneys the findings of an evaluation. It begins by reviewing developments in child custody law and concludes by addressing the problems between behavioral sciences and the law in these stressful cases. The presentation of clinical examples provides a view of the decision making process, while addressing the contextual setting for these cases as well. Language: en
Teacher Perspective Development: A Study of Preservice Social Studies Teachers

Abstract This study investigated the formation and development of preservice social studies teachers' perspectives. An individual's teaching perspective is a way of thinking and acting in a teaching situation. Examples of teaching perspectives were obtained through observations of and interviews with social studies education majors (N = 21) at a major midwestern university. The interview data were consistent with the hypothesis that preservice teachers' perspectives are the product of a dialectical process of professional socialization. The influence of social structural variables, such as teacher education course work and field experiences, appeared to be marginal and apparently did not produce deep internal changes in the belief systems of the participants. The participants were active mediators in their relationships with socializing institutions as represented by the schools and university teacher education. The active role of the individual in the development of a teaching perspective was illustrated.
Improving transfer-based MT systems with automatic refinements

In this paper, we describe an Automatic Rule Refiner that, given online post-editing information, traces errors back to problematic translation rules and proposes concrete fixes to such rules. Evaluation results on an English-to-Spanish Transfer-based MT system show that this approach generalizes beyond sentences corrected by bilingual speakers to unseen data. We show that by applying automatic refinements, higher translation accuracy can be achieved as measured by automatic evaluation metrics.
Revising the SES: A Collaborative Process to Improve Assessment of Sexual Aggression and Victimization

The Sexual Experiences Survey (SES) assesses victimization and perpetration of unwanted sexual experiences (e.g., Koss, Gidycz, & Wisniewski, 1987). Revised versions of the SES that resulted from the work of the SES Collaboration are now available. This article reviews weaknesses of the SES that were identified, strengths that were preserved, and methodological considerations in the measurement of unwanted sexual experiences that informed the revisions. The primary changes include: more behavioral specificity; conversion to gender neutrality; full crossing of unwanted acts and coercive tactics; and revised and updated wording for assessing consent, alcohol-related incidents, unwanted acts, and coercive tactics. For illustration, the full text of the revised victimization version and its scoring rules are provided. The article concludes with suggestions for future research. These suggestions aim to involve researchers in a coordinated agenda to develop data that clarify methodological questions and contribute to continued improvement in assessing sexual victimization and perpetration.