INTERNATIONAL JOURNAL OF PURE AND APPLIED RESEARCH IN ENGINEERING AND TECHNOLOGY A PATH FOR HORIZING YOUR INNOVATIVE WORK SURVEY ON RASPBERRY PI FOR INDUSTRIAL SENSOR

Abstract: This paper shows Raspberry Pi feature, advantages, and comparison with single board computer. Raspberry pi cheap, flexible, fully customizable and programmable small computer board. Raspberry Pi board consist of ARM11 programmable processer, Real time operating system and on -chip memory. Raspberry Pi Most effective factor is Reduce Complexibility of devices, Reduce over all cost of system

Effect of Covid-19 Pandemic on Shrimp Farming at Navsari, Gujarat, India

The lockdown on account of the Coronavirus disease 2019 (COVID-19) adversely impacted the food production sector including aquaculture globally. Unfortunately, it coincided with the major shrimp farming season in India which contributes 60% of the national annual shrimp production hence the impact was substantial. Shrimp farmers follow the different management practices in shrimp farming operations like seed, feed, probiotics, medicine, disruptions in the supply chain, transportation, harvesting and marketing. Therefore, the objective of present study was to find out the impact of COVID-19 pandemic on shrimp farming sector in Navsari (Gujarat). These findings are depicted that management practices of the shrimp farming in study area was disturbed and huge economic losses was faced by the shrimp farmers during pandemic situations. It is suggested that technical and financial assistance for safe, sufficient and hygienic supply of seed, feed, probiotics, chemicals, medicines and probiotics by the government agencies should be ensured which help to shrimp enhance the aquaculture production and survive of shrimp farmers. The result of present study is also helpful for the government authorities to develop policies and execution of the plans during such pandemic condition for shrimp farmers that can prevent the production loss and sustain the shrimp farming industry

Gaps Up To 9 Months Between HIV Primary Care Visits Do Not Worsen Viral Load

Current guidelines specify that visit intervals with viral monitoring should not exceed 6 months for HIV patients. Yet, gaps in care exceeding 6 months are common. In an observational cohort using US patients, we examined the association between gap length and changes in viral load status and sought to determine the length of the gap at which significant increases in viral load occur. We identified patients with gaps in care greater than 6 months from 6399 patients from six US HIV clinics. Gap strata were >6 to <7, 7 to <8, 8 to <9, 9 to <12, and ≥12 months, with viral load measurements matched to the opening and closing dates for the gaps. We examined visit gap lengths in association with two viral load measurements: continuous (log 10 viral load at gap opening and closing) and dichotomous (whether patients initially suppressed but lost viral suppression by close of the care gap). Viral load increases were nonsignificant or modest when gap length was <9 months, corresponding to 10% or fewer patients who lost viral suppression. For gaps ≥12 months, there was a significant increase in viral load as well as a much larger loss of viral suppression (in 23% of patients). Detrimental effects on viral load after a care gap were greater in young patients, black patients, and those without private health insurance. On average, shorter gaps in care were not detrimental to patient viral load status. HIV primary care visit intervals of 6 to 9 months for select patients may be appropriate

Evaluation of a computer-based and counseling support intervention to improve HIV patients' viral loads

We sought to integrate a brief computer and counseling support intervention into the routine practices of HIV clinics and evaluate effects on patients' viral loads. The project targeted HIV patients in care whose viral loads exceeded 1000 copies/ml at the time of recruitment. Three HIV clinics initiated the intervention immediately, and three other HIV clinics delayed onset for 16 months and served as concurrent controls for evaluating outcomes. The intervention components included a brief computer-based intervention (CBI) focused on antiretroviral therapy adherence; health coaching from project counselors for participants whose viral loads did not improve after doing the CBI; and behavioral screening and palm cards with empowering messages available to all patients at intervention clinics regardless of viral load level. The analytic cohort included 982 patients at intervention clinics and 946 patients at control clinics. Viral loads were assessed at 270 days before recruitment, at time of recruitment, and +270 days later. Results indicated that both the control and intervention groups had significant reductions in viral load, ending with approximately the same viral level at +270 days. There was no evidence that the CBI or the targeted health coaching was responsible for the viral reduction in the intervention group. Results may stem partially from statistical regression to the mean in both groups. Also, clinical providers at control and intervention clinics may have taken action (e.g., conversations with patients, referrals to case managers, adherence counselors, mental health, substance use specialists) to help their patients reduce their viral loads. In conclusion, neither a brief computer-based nor targeted health coaching intervention reduced patients' viral loads beyond levels achieved with standard of care services available to patients at well-resourced HIV clinics

Evaluation of a computer-based and counseling support intervention to improve HIV patients’ viral loads

We sought to integrate a brief computer and counseling support intervention into the routine practices of HIV clinics and evaluate effects on patients' viral loads. The project targeted HIV patients in care whose viral loads exceeded 1000 copies/ml at the time of recruitment. Three HIV clinics initiated the intervention immediately, and three other HIV clinics delayed onset for 16 months and served as concurrent controls for evaluating outcomes. The intervention components included a brief computer-based intervention (CBI) focused on antiretroviral therapy adherence; health coaching from project counselors for participants whose viral loads did not improve after doing the CBI; and behavioral screening and palm cards with empowering messages available to all patients at intervention clinics regardless of viral load level. The analytic cohort included 982 patients at intervention clinics and 946 patients at control clinics. Viral loads were assessed at 270 days before recruitment, at time of recruitment, and +270 days later. Results indicated that both the control and intervention groups had significant reductions in viral load, ending with approximately the same viral level at +270 days. There was no evidence that the CBI or the targeted health coaching was responsible for the viral reduction in the intervention group. Results may stem partially from statistical regression to the mean in both groups. Also, clinical providers at control and intervention clinics may have taken action (e.g., conversations with patients, referrals to case managers, adherence counselors, mental health, substance use specialists) to help their patients reduce their viral loads. In conclusion, neither a brief computer-based nor targeted health coaching intervention reduced patients' viral loads beyond levels achieved with standard of care services available to patients at well-resourced HIV clinics

Single Viral Load Measurements Overestimate Stable Viral Suppression Among HIV Patients in Care: Clinical and Public Health Implications

The HIV continuum of care paradigm uses a single viral load test per patient to estimate the prevalence of viral suppression. We compared this single-value approach with approaches that used multiple viral load tests to examine the stability of suppression. The retrospective analysis included HIV patients who had at least 2 viral load tests during a 12-month observation period. We assessed the (1) percent with suppressed viral load (<200 copies/mL) based on a single test during observation, (2) percent with suppressed viral loads on all tests during observation, (3) percent who maintained viral suppression among patients whose first observed viral load was suppressed, and (4) change in viral suppression status comparing first with last measurement occasions. Prevalence ratios compared demographic and clinical subgroups. Of 10,942 patients, 78.5% had a suppressed viral load based on a single test, whereas 65.9% were virally suppressed on all tests during observation. Of patients whose first observed viral load was suppressed, 87.5% were suppressed on all subsequent tests in the next 12 months. More patients exhibited improving status (13.3% went from unsuppressed to suppressed) than worsening status (5.6% went from suppressed to unsuppressed). Stable suppression was less likely among women, younger patients, black patients, those recently diagnosed with HIV, and those who missed ≥1 scheduled clinic visits. Using single viral load measurements overestimated the percent of HIV patients with stable suppressed viral load by 16% (relative difference). Targeted clinical interventions are needed to increase the percent of patients with stable suppression

Analysis of Outcomes in Ischemic vs Nonischemic Cardiomyopathy in Patients With Atrial Fibrillation A Report From the GARFIELD-AF Registry

IMPORTANCE Congestive heart failure (CHF) is commonly associated with nonvalvular atrial fibrillation (AF), and their combination may affect treatment strategies and outcomes