Mr. Dr. Health-Assistant Chatbot

Research says 60% of visits to a doctor are for simple small-scale diseases, 80% of which can be diagnosed at home using simple check-up. These diseases mostly include common cold and cough, headache, abdominal pains etc. Whereas, chat-bots in healthcare are highly in demand, which functioning can offer various services from symptom checking and appointment scheduling. Therefore, the purpose of the research aims to design, develop and evaluate a health-assistant Chat-bot Application entitled “MR.Dr.” that helps users to ask any personal query related to healthcare without physically available to the hospital. MR.Dr. is evaluated in term of usability. 30 respondents attended the survey of usability evaluation. In the system usability scale MR.Dr. achieved 87.6 % rating which means Grade A (excellent). User's feedback level was pretty satisfying where 24/7 service is the highest one.

Central μ-opioid receptor antagonism blocks glucoprivic LH pulse suppression and gluconeogenesis/feeding in female rats

Energetic status often affects reproductive function, glucose homeostasis and feeding in mammals. Malnutrition suppresses pulsatile release of the gonadotropin-releasing hormone (GnRH)/luteinizing hormone (LH) and increases gluconeogenesis and feeding. The present study aims to examine whether β-endorphin-μ-opioid receptor (MOR) signaling mediates the suppression of pulsatile GnRH/LH release, and an increase in gluconeogenesis/feeding induced by malnutrition. Ovariectomized female rats treated with a negative feedback level of estradiol-17β (OVX + low E2) receiving 2-deoxy-D-glucose (2DG), an inhibitor of glucose utilization, intravenously (iv), were used as a malnutrition model. An administration of D-Phe-Cys-Tyr-D-Trp-Orn-Thr-Pen-Thr-NH2 (CTOP), a selective MOR antagonist, into the 3 rd ventricle blocked the suppression of the LH pulse and increase in gluconeogenesis/feeding induced by iv 2DG administration. Histological analysis revealed that arcuate Kiss1 (kisspeptin gene)-expressing cells and preoptic Gnrh1 (GnRH gene)-expressing cells co-expressed little Oprm1, while around 10% of arcuate Slc17a6 (glutamatergic marker gene)-expressing cells co-expressed Oprm1. Further, the CTOP treatment decreased the number of fos-positive cells in the paraventricular nucleus (PVN) in OVX + low E2 rats treated with iv 2DG, but failed to affect the number of arcuate fos-expressing Slc17a6-positive cells. Taken together, these results suggest that the central β-endorphin-MOR signaling mediates the suppression of pulsatile LH release and that the β-endorphin may indirectly suppress the arcuate kisspeptin neurons, a master regulator for GnRH/LH pulses during malnutrition. Furthermore, the current study suggests that central β-endorphin-MOR signaling is also involved in gluconeogenesis and an increase in food intake by directly or indirectly acting on the PVN neurons during malnutrition in female rats.

Toward an Estimation of the Optical Feedback Factor C on the Fly for Displacement Sensing

In this paper, a method based on the inherent event-based sampling capability of laser optical feedback interferometry (OFI) is proposed to assess the optical feedback factor C when the laser operates in the moderate and strong feedback regimes. Most of the phase unwrapping open-loop OFI algorithms rely on the estimation of C to retrieve the displacement with nanometric precision. Here, the proposed method operates in open-loop configuration and relies only on OFI’s fringe detection, thereby improving its robustness and ease of use. The proposed method is able to estimate C with a precision of <5%. The obtained performances are compared to three different approaches previously published and the impacts of phase noise and sampling frequency are reported. We also show that this method can assess C on the fly even when C is varying due to speckle. To the best of the authors’ knowledge, these are the first reported results of time-varying C estimation. In addition, through C estimation over time, it could pave the way not only to higher performance phase unwrapping algorithms but also to a better control of the optical feedback level via the use of an adaptive lens and thus to better displacement retrieval performances.

Assessment of Industry Partners: Inputs for Partnership Improvement and Selection of Host Training Establishments

Industry partners such as energy providers (in electric Power Systems for example) are critical in the successful implementation of the University’s internship program and attainment of objectives. Thus, it is important that the University adhere to the criteria and requirements outlined by the Commission on Higher Education for selection of reputable host training establishments. This study aims to provide additional guidelines for the Business Administration program in considering prospective industry partners for internship by incorporating the students’ assessment of industry partners. Using independent samples t-test, the researcher found that the profile of the industry partner has no significant effect on the level of implementation, the students’ feedback, attainment of objectives and the seriousness of problems encountered during internship. Through independent samples t-test and One-Way ANOVA, it was found that the students’ profile also has no effect on the perceived seriousness of problems encountered during the training. However, using Pearson correlation coefficient analysis, it was found that the level of implementation of the internship program within the industry partner has a relationship with the students’ feedback, level of attainment of internship objectives, and the seriousness of problems encountered. The level of implementation positively impacts the level of attainment of objectives and the seriousness of problems encountered. While the relationship with feedback was generally positive, it was found that the level of implementation negatively impacts the students’ feedback of industry partners in terms of decision making and empowerment.

Artificial Intelligence Coaches for Sales Agents: Caveats and Solutions

Firms are exploiting artificial intelligence (AI) coaches to provide training to sales agents and improve their job skills. The authors present several caveats associated with such practices based on a series of randomized field experiments. Experiment 1 shows that the incremental benefit of the AI coach over human managers is heterogeneous across agents in an inverted-U shape: whereas middle-ranked agents improve their performance by the largest amount, both bottom- and top-ranked agents show limited incremental gains. This pattern is driven by a learning-based mechanism in which bottom-ranked agents encounter the most severe information overload problem with the AI versus human coach, while top-ranked agents hold the strongest aversion to the AI relative to a human coach. To alleviate the challenge faced by bottom-ranked agents, Experiment 2 redesigns the AI coach by restricting the training feedback level and shows a significant improvement in agent performance. Experiment 3 reveals that the AI–human coach assemblage outperforms either the AI or human coach alone. This assemblage can harness the hard data skills of the AI coach and soft interpersonal skills of human managers, solving both problems faced by bottom- and top-ranked agents. These findings offer novel insights into AI coaches for researchers and managers alike.

Paraventricular Dynorphin A Neurons Mediate LH Pulse Suppression Induced by Hindbrain Glucoprivation in Female Rats

Malnutrition suppresses reproductive functions in mammals, which is considered to be mostly due to the inhibition of pulsatile gonadotropin-releasing hormone (GnRH)/gonadotropin secretion. Accumulating evidence suggests that kisspeptin neurons in the arcuate nucleus (ARC) play a critical role in the regulation of pulsatile GnRH/gonadotropin release. The present study aimed to examine if the hypothalamic dynorphin A (Dyn) neurons mediate the suppression of GnRH/luteinizing hormone (LH) pulses during malnutrition. Ovariectomized rats treated with a negative feedback level of estradiol-17β-treated (OVX+E2) were administered with intravenous (iv) or fourth cerebroventricle (4V) 2-deoxy-D-glucose (2DG), an inhibitor of glucose utilization, to serve as a malnutrition model. Central administration of a Dyn receptor antagonist blocked the iv- or 4V-2DG-induced suppression of LH pulses in OVX+E2 rats. The 4V 2DG administration significantly increased the number of Pdyn (Dyn gene)-positive cells co-expressing fos in the paraventricular nucleus (PVN), but not in the ARC and supraoptic nucleus (SON), and the iv 2DG treatment significantly increased the number of fos and Pdyn-co-expressing cells in the PVN and SON, but decreased it in the ARC. The E2 treatment significantly increased Pdyn expression in the PVN, but not in the ARC and SON. Double in situ hybridization for Kiss1 (kisspeptin gene) and Oprk1 (Dyn receptor gene) revealed that around 60% of ARC Kiss1-expressing cells co-expressed Oprk1. These results suggest that the PVN Dyn neurons, at least in part, mediate LH pulse suppression induced by the hindbrain or peripheral glucoprivation, and Dyn neurons may directly suppress the ARC kisspeptin neurons in female rats.

An analytical method for estimation of parameters of Self Mixing Interferometric phase equation over all feedback regimes

This paper presents a novel algorithm for measuring the linewidth enhancement factor of semiconductor lasers and the optical feedback level factor in a semiconductor laser with an external cavity. The proposed approach is based on analysis of the self-mixing phase equation to deduce equations for finding parameters given only knowledge of the perturbed phase. The effectiveness of the method has been validated with accuracy of 8.6%and 1.7% for 'C' and alpha respectively while covering all feedback regimes.

An analytical method for estimation of parameters of Self Mixing Interferometric phase equation over all feedback regimes

This paper presents a novel algorithm for measuring the linewidth enhancement factor of semiconductor lasers and the optical feedback level factor in a semiconductor laser with an external cavity. The proposed approach is based on analysis of the self-mixing phase equation to deduce equations for finding parameters given only knowledge of the perturbed phase. The effectiveness of the method has been validated with accuracy of 8.6%and 1.7% for 'C' and alpha respectively while covering all feedback regimes.

Routes to Chaos of a Semiconductor Laser Subjected to External Optical Feedback: A Review

This paper reviews experimental investigations of the route to chaos of a semiconductor laser subjected to optical feedback from a distant reflector. When the laser is biased close to threshold, as the feedback strength is increased, an alternation between stable continuous wave (CW) behavior and irregular, chaotic fluctuations, involving numerous external-cavity modes, is observed. CW operation occurs on an external-cavity mode whose optical frequency is significantly lower than that of the solitary laser. The scenario is significantly different for larger currents as the feedback level is increased. At low feedback, the laser displays periodic or quasiperiodic behavior, mostly around external-cavity modes whose frequency is slightly larger than that of the solitary laser. As the feedback level increases, the RF and optical frequencies involved progressively lock until complete locking is achieved in a mixed external-cavity mode state. In this regime, the optical intensity and voltage oscillate at a frequency that is also equal to the optical frequency spacing between the modes participating in the dynamics. For even higher feedback, the locking cannot be maintained and the laser displays fully developed coherence collapse.