Comparative study on the effectiveness acetaminophen and diclofenac on pretreatment in the relief of pain after out-patient surgery

The aim of this study is to evaluate and quantify the pain relief after minor surgery when certain analgesics are used before surgery. Double blind study was conducted on 300 outpatient surgery patients who were allocated into two groups. Before surgery, 100 mg of acetaminophen was given to one group and 75 mg of diclofenac to the other one. The pain level after surgery was measured and recorded in both groups by a ruler 10 cm using the Visual Analog Scale (VAS) method at intervals of 30 min, 1, 2 and 4 h after surgery. Also for the patients with VAS more than 7, it was recommended to administer IM 50-100 mg teramadole ampoule. Mean VAS in acetaminophen group was 5.28±1.17, 5.17 ±1.04, 4.47±1.05±, 3.97±1.09 while, in diclofenac group was 5.09±1.10, 5.10±1.024.27±1.05 and 3/73±1.07 at 0.5, 1, 2 and 4 h after surgery, respectively. In fact there was no significant difference in pain level after surgery between acetaminophen and diclofenac groups (p>0.05). Moreover, there was no significant difference in the effectiveness of pain relief induced by administering tramadol calmative ampoule along with acetaminophen and diclofenac groups (p>0.05). Acetaminophen results in as effective pain relief as diclofenac with or without tramadol calmative. Due to minimal side effects of acetaminophen when compared to other analgesics, like diclofenac, it is recommended to use acetaminophen for safe and efficient pain relief after outpatients surgeries

Modelling Social Interaction between Humans and Service Robots in Large Public Spaces

With the advent of service robots in public places (e.g., in airports and shopping malls), understanding socio-psychological interactions between humans and robots is of paramount importance. On the one hand, traditional robotic navigation systems consider humans and robots as moving obstacles and focus on the problem of real-time collision avoidance in Human-Robot Interaction (HRI) using mathematical models. On the other hand, the behavior of a robot has been determined with respect to a human. Parameters for human-human interaction have been assumed and applied to interactions involving robots. One major limitation is the lack of sufficient data for calibration and validation procedures. This paper models, calibrates and validates the socio-psychological interaction of the human in HRIs among crowds. The mathematical model is an extension of the Social Force Model for crowd modelling. The proposed model is calibrated and validated using open source datasets (including uninstructed human trajectories) from the Asia and Pacific Trade Center shopping mall in Osaka (Japan).In summary, the results of the calibration and validation on the multiple HRIs encountered in the datasets show that humans react to a service robot to a higher extend within a larger distance compared to the interaction range towards another human. This microscopic model, calibration and validation framework can be used to simulate HRI between service robots and humans, predict humans' behavior, conduct comparative studies, and gain insights into safe and comfortable human-robot relationships from the human's perspective

Correlation between Situational Awareness and EEG signals

An important aspect in safety–critical domains is Situational Awareness (SA) where operators consolidate data into an understanding of the situation that needs to be updated dynamically as the situation changes over time. Among existing measures of SA, only physiological measures can assess the cognitive processes associated with SA in real-time. Some studies showed promise in detecting cognitive states associated with SA in complex tasks using brain signals (e.g. electroencephalogram/EEG). In this paper, an analytical methodology is proposed to identify EEG signatures associated with SA on various regions of the brain. A new data set from 32 participants completing the SA test in the PEBL is collected using a 32-channel dry-EEG headset. The proposed method is tested on the new data set and a correlation is identified between the frequency bands of b (12 - 30 Hz) and c (30 - 45 Hz) and SA. Also, activation of neurons in the left and right hemisphere of the parietal and temporal lobe is observed. These regions are responsible for the visuo-spatial ability and memory and reasoning tasks. Among the presented results, the highest achieved accuracy on test data is 67%

“Is More Better?”:Impact of Multiple Photos on Perception of Persona Profiles

In this research, we investigate if and how more photos than a single headshot can heighten the level of information provided by persona profiles. We conduct eye-tracking experiments and qualitative interviews with variations in the photos: a single headshot, a headshot and images of the persona in different contexts, and a headshot with pictures of different people representing key persona attributes. The results show that more contextual photos significantly improve the information end users derive from a persona profile; however, showing images of different people creates confusion and lowers the informativeness. Moreover, we discover that choice of pictures results in various interpretations of the persona that are biased by the end users' experiences and preconceptions. The results imply that persona creators should consider the design power of photos when creating persona profiles

Dynamic Pricing:An Efficient Solution for True Demand Response Enabling

A dynamic pricing scheme, also known as real-time pricing (RTP), can be more efficient and technically beneficial than the other price-based schemes (such as flat-rate or time-of-use pricing) for enabling demand response (DR) actions. Over the past few years, the advantages of RTP-based schemes have been extensively discussed for DR purposes in electricity markets; however, they have not been proven mathematically according to a valid economics-based model. Instead, most of the related literature has only relied on observations and experiences in the markets of other commodities. Thus, to provide a reliable reference point based on mathematical models, this paper utilizes well-known economic theories and mathematical formulations to prove the impact of RTP on true enabling of DR actions in electricity markets. Based on the theory of saving under uncertainty, it is shown that the use of dynamic pricing can lead to increased willingness of consumers to participate in DR programs which in turn improve the operation of liberalized electricity markets

Data-driven model of the power-grid frequency dynamics

The energy system is rapidly changing to accommodate the increasing number of renewable generators and the general transition towards a more sustainable future. Simultaneously, business models and market designs evolve, affecting power-grid operation and power-grid frequency. Problems raised by this ongoing transition are increasingly addressed by transdisciplinary research approaches, ranging from purely mathematical modelling to applied case studies. These approaches require a stochastic description of consumer behaviour, fluctuations by renewables, market rules, and how they influence the stability of the power-grid frequency. Here, we introduce an easy-to-use, data-driven, stochastic model for the power-grid frequency and demonstrate how it reproduces key characteristics of the observed statistics of the Continental European and British power grids. Using data analysis tools and a Fokker–Planck approach, we estimate parameters of our deterministic and stochastic model. We offer executable code and guidelines on how to use the model on any power grid for various mathematical or engineering applications

Subclausal Local Contexts

One of the central topics in semantic theory over the last few decades concerns the nature of local contexts. Recently, theorists have tried to develop general, non-stipulative accounts of local contexts (Schlenker, 2009; Ingason, 2016; Mandelkern & Romoli, 2017a). In this paper, we contribute to this literature by drawing attention to the local contexts of subclausal expressions. More specifically, we focus on the local contexts of quantificational determiners, e.g. `all', `both', etc. Our central tool for probing the local contexts of subclausal elements is the principle Maximize Presupposition! (Percus, 2006; Singh, 2011). The empirical basis of our investigation concerns some data discussed by Anvari (2018b), e.g. the fact that sentences such as `All of the two presidential candidates are crooked' are unacceptable. In order to explain this, we suggest that the local context of determiners needs to contain the information carried by their restrictor. However, no existing non-stipulative account predicts this. Consequently, we think that the local contexts of subclausal expressions will likely have to be stipulated. This result has important consequences for debates in semantics and pragmatics, e.g. those around the so-called "explanatory problem" for dynamic semantics (Soames, 1982; Heim, 1990; Schlenker, 2009)

Application of some herbal medicine used for the treatment of osteoarthritis and chondrogenesis

Rheumatic diseases such as osteoarthritis (OA), rheumatoid arthritis (RA), and low back pain are very popular. The drugs available to treat these diseases are almost ineffective and have significant side effects. There are several approaches used to replace conventional drugs to treat these diseases. One of these methods is the use of herbal medicines. In this study, the effects of herbal medicines and medicinal plants used in the treatment of these diseases include. Searching for articles published in English from 1985 to 2020 using keywords include scientific and traditional names of plants reviewing Scopus and PubMed databases. There is limited research on the anti-rheumatic effects of these plants and the active ingredients. Therefore, further research is needed to determine the mechanism of action, the interaction of effects, the efficacy and safety of medicinal plants, and the potentially beneficial plant nutrients in treatment of these diseases seems necessary. The aim of this review was to update information on OA and chondrogenesis, also importance of herbal drugs for the management of arthritis. © 2020 Tehran University of Medical Sciences. All rights reserved

At-risk elementary school children with one year of classroom music instruction are better at keeping a beat

Temporal processing underlies both music and language skills. There is increasing evidence that rhythm abilities track with reading performance and that language disorders such as dyslexia are associated with poor rhythm abilities. However, little is known about how basic time-keeping skills can be shaped by musical training, particularly during critical literacy development years. This study was carried out in collaboration with Harmony Project, a non-profit organization providing free music education to children in the gang reduction zones of Los Angeles. Our findings reveal that elementary school children with just one year of classroom music instruction perform more accurately in a basic finger-tapping task than their untrained peers, providing important evidence that fundamental time-keeping skills may be strengthened by short-term music training. This sets the stage for further examination of how music programs may be used to support the development of basic skills underlying learning and literacy, particularly in at-risk populations which may benefit the most