Designing Retail Facilities to Improve Product Exposure

A retail facility should effectively engage consumers during their shopping trips if they want to convert demand into purchases. Unfortunately, the complexity of the retailing environment and lack of scientific tools often results in gut-feel approaches experimented in practice. A key factor to retail design often alluded to, but rarely analyzed, is product exposure to the travelling shopper. We define the extent of the shopper\u27s field of vision in order to determine the actual exposure of products experienced by a traveling shopper. In so doing, we can explore the effect rack orientation has on product exposure. Our main contributions include defining product exposure and an approach to estimate it at any point along the travel path. Our results indicate that certain rack orientations result in product exposures as high as 2.5 times that of the traditional 90° orientation

Power Reduction Sleep Scheduling Technique for Cloud Integrated Green Social Sensor Network

The wireless sensor network is the maximum appropriate technology nowadays with such awesome applications and areas including Infrastructure tracking, environment tracking, health care tracking, etc. Cloud Computing has fantastic data collecting skills and effective data processing ability. Social Network is a group of People or organizations of human beings with similar intentions. Social Sensor Cloud is one type of expertise-sharing mechanism wherein similar types of human beings can connect. Energy Consumption is nowadays the largest challenge as far as the concern with green environment. Because the battery life of the sensor is so limited, the Social Sensor Cloud must be energy efficient. As a result, this article will concentrate on Energy-Efficient Techniques for the Social Sensor Cloud. According to our findings, findings, the majority of energy-saving measures will cope with not unusual place Parameters including Network Lifetime, Network Work rate, Throughput, Energy, Bandwidth, etc. We will Summarize current Technology and we Will Provide Our Architecture for Energy Reduction in Social Sensor Cloud

Distribution Planning Considering Warehousing Decisions

Modern supply chains heavily depend on warehouses for rapidly fulfilling customer demands through retail, web-based, and catalogue channels. The traditional approach that considers warehouses as cost-centers has affected the profitability of numerous supply chains. A lack of synchronization between procurement and allocation decisions causes warehouses to scramble for resources during peak times and be faced with under-utilized resources during drought times. Warehouses, however, have emerged as service-centers and it is imperative that warehousing decisions be an integral part of supply chain decisions. In this paper we propose a mixed-integer programming model to integrate warehousing decisions with those of inventory and transportation to minimize long-run distribution cost. Preliminary experiments suggest a sizeable reduction in the level and variance in the warehouse workforce requirements. A cost savings ranging between 2-6% is also realized

Location Based Power Reduction Cloud Integrated Social Sensor Network

It is great to hear about the advancements in wireless sensor networks and their applications, as well as the integration of cloud computing to enhance data analysis and storage capabilities. Indeed, these technologies have opened up numerous possibilities across various fields, including infrastructure tracking, environmental monitoring, healthcare, and more. The concept of a social sensor cloud, as you mentioned, brings an interesting dimension to this technology landscape by focusing on knowledge-sharing and connecting like-minded individuals or organizations. This could potentially lead to more collaborative and efficient solutions across a wide range of domains. Energy efficiency is a critical consideration in the design and operation of wireless sensor networks and the cloud infrastructure that supports them. The limited battery life of sensors necessitates careful management of energy consumption to ensure optimal functionality and longevity. Sleep scheduling methods are a common technique used to manage energy consumption in these networks. By coordinating when sensors are active and when they are in a low-power sleep mode, energy consumption can be significantly reduced without compromising the network's overall effectiveness. In the context of the Social Sensor Cloud, managing energy efficiency becomes even more crucial due to the shorter battery life of the sensors involved. This is particularly relevant given the growing concerns about environmental sustainability and the need to reduce energy consumption across technological systems. It's clear that your research paper addresses these challenges head-on, by exploring energy-efficient techniques for the Social Sensor Cloud. Sleep scheduling is just one of the many strategies that researchers and engineers are working on to strike a balance between functionality and energy consumption. Other methods might include optimizing data transfer protocols, developing energy-harvesting mechanisms, and enhancing sensor hardware efficiency. As technology continues to evolve, the integration of wireless sensor networks, cloud computing, and social networks will likely pave the way for innovative solutions and transformative applications. Addressing energy efficiency concerns will undoubtedly play a crucial role in ensuring the long-term viability and positive impact of these technologies

Aerodynamic Study of Payload Fairing

ABSTRACT: Payload Fairing protects a spacecraft from temperature heating during the initial launch stages in region of dense atmosphere. Shock waves are formed in the transonic region of flow, which makes the faring the most unstable in this phase. This paper aims at studying and reducing the unsteady pressure levels and hence also the aero acoustic loading in the transonic region i.e. Mach number 0.7 to 1.2. The separation area as well as the shock strength must be reduced. For this reason, flow stimulation to study pressure distribution, shock strength and separation was carried out. The Mach number at which the minimum flow separation as well as the shock strength is the most preferable one

Capnocytophaga canimorsus meningitis in a 38-year-old immunocompetent woman from household pet exposure.

A 38-year-old otherwise healthy woman with no history of immunocompromise, recent travel, or concerning exposures presented to the ED with several days of nonspecific cold-like symptoms with associated generalized headache. After the patient was symptomatically treated and discharged, she returned several hours later with worsening of symptoms and new vomiting, confusion, and sensorineural hearing loss. Blood and cerebrospinal fluid cultures eventually returned positive for a Capnocytophaga canimorsus infection, a bacterial pathogen found in the saliva of dogs and cats. Only after that, the patient recalled being scratched and licked by her pets, two dogs and a cat. She was treated with a course of systemic steroids, antibiotics and discharged home

Use of Intravascular Imaging During Chronic Total Occlusion Percutaneous Coronary Intervention: Insights From a Contemporary Multicenter Registry

Background: Intravascular imaging can facilitate chronic total occlusion (CTO) percutaneous coronary intervention. Methods and Results: We examined the frequency of use and outcomes of intravascular imaging among 619 CTO percutaneous coronary interventions performed between 2012 and 2015 at 7 US centers. Mean age was 65.4±10 years and 85% of the patients were men. Intravascular imaging was used in 38%: intravascular ultrasound in 36%, optical coherence tomography in 3%, and both in 1.45%. Intravascular imaging was used for stent sizing (26.3%), stent optimization (38.0%), and CTO crossing (35.7%, antegrade in 27.9%, and retrograde in 7.8%). Intravascular imaging to facilitate crossing was used more frequently in lesions with proximal cap ambiguity (49% versus 26%, P<0.0001) and with retrograde as compared with antegrade‐only cases (67% versus 31%, P<0.0001). Despite higher complexity (Japanese CTO score: 2.86±1.19 versus 2.43±1.19, P=0.001), cases in which imaging was used for crossing had similar technical and procedural success (92.8% versus 89.6%, P=0.302 and 90.1% versus 88.3%, P=0.588, respectively) and similar incidence of major cardiac adverse events (2.7% versus 3.2%, P=0.772). Use of intravascular imaging was associated with longer procedure (192 minutes [interquartile range 130, 255] versus 131 minutes [90, 192], P<0.0001) and fluoroscopy (71 minutes [44, 93] versus 39 minutes [25, 69], P<0.0001) time. Conclusions: Intravascular imaging is frequently performed during CTO percutaneous coronary intervention both for crossing and for stent selection/optimization. Despite its use in more complex lesion subsets, intravascular imaging was associated with similar rates of technical and procedural success for CTO percutaneous coronary intervention. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT02061436

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570