Psychiatric Comorbidity in Transformed Migraine: Presentation, Treatment, Impact and Outcome

Transformed migraine is one of the subtypes of chronic daily headache (CDH), and is similar to chronic migraine, described in the new International Headache Society (IHS) classification 2004. The term CDH refers to the Headache disorders experienced 15 or more days a month and includes headaches associated with medication overuse. CDH can be divided into primary and secondary varieties. Primary CDH is not related to a structural or systemic illness. It includes diseases such as Transformed migraine (TM). Chronic tension-type headache (CTTH), new daily persistent headache (NDPH), and hemicrania continua (HC). Secondary CDH has an identifiable underlying cause, including post-traumatic headache, cervical spine disorders, vascular disorders, nonvascular intracranial disorders and headaches associated with temporomandibular joint disorders, sinus infections, chronic meningitis, low and high intracranial pressure. In this study we have adopted the 1996 definition of TM proposed by Silberstein and Lipton in preference to the new discredited 2004 IHS criteria for chronic migraine. The association between migraine and psychiatric disorders has long been established. Several clinic-based and population-based studies have discussed the relationship. However psychiatric comorbidity in transformed migraine has seldom been discussed, and the effect on overall outcome has not been examined . Population based studies have shown that 4% to 5% of the general population has primary CDH. Transformed migraine is the major cause of CDH and is associated with poor quality of life and greater medical and social expenses compared to episodic migraine. CDH is most commonly transformed Migraine and is accompanied by high anxiety levels in most patients and with hysterical traits in some. These patients frequently have a coexisting depressive disorder. The purpose of this study is to characterize psychiatric disorders accompanying TM in a tertiary headache center and to examine their impact on outcome

Reductive Leaching Kinetics of Low Grade Manganese Deposits in H2SO4 Solution Using Malonic Acid as Reducing Agent

A leaching process was developed to extract manganese and metal values from Alloga manganese concentrate. The preferential leaching process was achieved through reductive leaching in dilute sulfuric acid medium with malonic acid as the reducing agent. Leaching parameters were optimized as 1.0 M H2SO4, 10% malonic acid in solid/liquid ratio 1:10 for 90 min at 8

Orbital effects of a monochromatic plane gravitational wave with ultra-low frequency incident on a gravitationally bound two-body system

We analytically compute the long-term orbital variations of a test particle orbiting a central body acted upon by an incident monochromatic plane gravitational wave. We assume that the characteristic size of the perturbed two-body system is much smaller than the wavelength of the wave. Moreover, we also suppose that the wave's frequency is much smaller than the particle's orbital one. We make neither a priori assumptions about the direction of the wavevector nor on the orbital geometry of the planet. We find that, while the semi-major axis is left unaffected, the eccentricity, the inclination, the longitude of the ascending node, the longitude of pericenter and the mean anomaly undergo non-vanishing long-term changes. They are not secular trends because of the slow modulation introduced by the tidal matrix coefficients and by the orbital elements themselves. They could be useful to indepenedently constrain the ultra-low frequency waves which may have been indirectly detected in the BICEP2 experiment. Our calculation holds, in general, for any gravitationally bound two-body system whose characteristic frequency is much larger than the frequency of the external wave. It is also valid for a generic perturbation of tidal type with constant coefficients over timescales of the order of the orbital period of the perturbed particle.Comment: LaTex2e, 24 pages, no figures, no tables. Changes suggested by the referees include

Medium- and short-chain dehydrogenase/reductase gene and protein families: The MDR superfamily

The MDR superfamily with ~350-residue subunits contains the classical liver alcohol dehydrogenase (ADH), quinone reductase, leukotriene B4 dehydrogenase and many more forms. ADH is a dimeric zinc metalloprotein and occurs as five different classes in humans, resulting from gene duplications during vertebrate evolution, the first one traced to ~500 MYA (million years ago) from an ancestral formaldehyde dehydrogenase line. Like many duplications at that time, it correlates with enzymogenesis of new activities, contributing to conditions for emergence of vertebrate land life from osseous fish. The speed of changes correlates with function, as do differential evolutionary patterns in separate segments. Subsequent recognitions now define at least 40 human MDR members in the Uniprot database (corresponding to 25 genes when excluding close homologues), and in all species at least 10888 entries. Overall, variability is large, but like for many dehydrogenases, subdivided into constant and variable forms, corresponding to household and emerging enzyme activities, respectively. This review covers basic facts and describes eight large MDR families and nine smaller families. Combined, they have specific substrates in metabolic pathways, some with wide substrate specificity, and several with little known functions

Analysis of effective capacity and throughput of polling-based device-to-device networks

© 1967-2012 IEEE. Next-generation wireless networks will give rise to heterogeneous networks by integrating multiple wireless access technologies to provide seamless mobility to mobile users with high-speed wireless connectivity. Device-to-device (D2D) communication has proven to be a promising technology that can increase the capacity and coverage of wireless networks. The D2D communication was first introduced in long-term evolution advanced (LTE-A) and has gained immense popularity for the offloading traffic using the licensed and unlicensed band. Challenges arise from resource allocation, provision of quality-of-service (QoS), and the quantification of capacity in an unlicensed band due to the distributed nature of Wi-Fi. In this paper, we propose an analytical performance model for the scalable MAC protocol (SC-MP) in which a resource allocation mechanism is based on the IEEE 802.11 point coordinated function to access the Wi-Fi channel for voice and video/multimedia traffic. In the SC-MP, D2D communication is applied to further offload the video/multimedia traffic. In particular, this paper establishes a three-state semi-Markovian model to derive a closed-form expression of effective capacity in terms of transmission rate and quality-of-service. Further, the SC-MP is analytically modeled using the four-state traditional Markov model to derive the saturation throughput. The analytical results are validated through simulations, hence, proving the appropriateness of the model

PCF-based LTE Wi-Fi aggregation for coordinating and offloading the cellular traffic to D2D network

© 2018 IEEE. Device-to-device (D2D) communication is a promising technology towards 5G networks. D2D communication can offload traffic using licensed/unlicensed band by establishing a direct communication between two users without traversing the base station or core network. However, one of the major challenges of D2D communication is resource allocation and guaranteeing quality-of-service (QoS). In this paper, we establish an optimal queuing scheduling and resource allocation problem for three-tier heterogeneous network based on LTE Wi-Fi aggregation, to offload voice/multimedia traffic from licensed band to unlicensed band using scalable MAC protocol (SC-MP) under various static delay constraints. The access mechanism used for Wi-Fi in SC-MP is point coordination function, which further offloads the multimedia traffic using D2D communication in unlicensed band. Resource allocation and optimal joint queuing scheduling problems are formulated with diverse QoS guarantee between licensed and unlicensed band to minimize the bandwidth of licensed band. Furthermore, an iterative algorithm is proposed to express the nonconvex problem as a series of subproblems based on block coordinate descent and difference of two convex functions (D.C) program. We have simulated the proposed scheme using two scenarios: Voice traffic using licensed band and voice traffic using both licensed and unlicensed band, whereas multimedia traffic uses unlicensed band for both the scenarios. The simulation results show that both the schemes perform better than the existing scheme and scenario 2 outperforms scenario 1

Automated Chicago Classification for Esophageal Motility Disorder Diagnosis Using Machine Learning

The goal of this paper is to provide a Machine Learning-based solution that can be utilized to automate the Chicago Classification algorithm, the state-of-the-art scheme for esophageal motility disease identification. First, the photos were preprocessed by locating the area of interest—the precise instant of swallowing. After resizing and rescaling the photos, they were utilized as input for the Deep Learning models. The InceptionV3 Deep Learning model was used to identify the precise class of the IRP. We used the DenseNet201 CNN architecture to classify the images into 5 different classes of swallowing disorders. Finally, we combined the results of the two trained ML models to automate the Chicago Classification algorithm. With this solution we obtained a top-1 accuracy and f1-score of 86% with no human intervention, automating the whole flow, from image preprocessing until Chicago classification and diagnosis