ABSTRACT
Growing energy consumption has been a contemporary problem, especially in the climate crisis and the COVID-19 pandemic. Many statistical reports have stated that there is an increase in energy consumption from residential households to the industrial sector. Electricity consumption forecasting is extremely important as it supports power system decision-making and management. In this paper, traditional ARIMAX and SARIMAX forecasting models and RNN-based deep learning models were used to model the electricity consumption historical data of a two-storied house located in Houston, Texas, USA. The features used in the modeling process include the daily-average electricity consumption historical data of the two-storied house, day category (weekday, weekend, vacation day, and COVID-lockdown), and weather-related variables. Each model's respective error performance on the testing dataset is compared. The result showed that RNN-based deep learning models outperformed the traditional ARIMAX and SARIMAX models in forecasting the daily-average electricity consumption of the two-storied house and that the performance of the RNN-based deep learning models doesn't differ significantly from each other. © 2022 IEEE.
ABSTRACT
The aim of the study was to determine university stress in a virtual environment during COVID-19. The approach was quantitative, descriptive-correlational design, conducted in 194 students of a public university in Peru, who were administered the online survey of Academic Stress SISCO SV adapted to the context. The prevailing level of university stress is moderate in 62.9%, and severe in 33.5%. According to dimensions it is moderate in stressors with 51%, symptoms 44.8% and coping strategies 63.4%. Statistically, the nonparametric Spearman's Rho test showed a positive and statistically significant correlation of .523 between the variables academic stress and forms of coping. Likewise, between symptoms and academic stressors of .604. The most relevant stressors were competitiveness among classmates and overload of virtual work, reflected by symptoms that can have repercussions on mental health, while the forms of coping were of concern, the most used being listening to music and the least used being physical exercise. These results may justify preventive interventions by academic authorities in the face of adversity to mitigate stress in university students.
ABSTRACT
BACKGROUND AND AIMS: The COVID-19 pandemic has brought to the forefront a wide spectrum of renal injuries that included glomerulopathies, some of which were recently highlighted in various case reports. These consist of focal and segmental glomerulosclerosis (FSGS) and minimal change disease (MCD).1 These changes were found among seemingly vulnerable populations such as the African American and Caucasian ethnicities with paucity of reports among other races. We present two cases of biopsy-confirmed MCD secondary to COVID-19 infection among adult Filipino patients. METHODS: Case Report RESULTS: Case 1 A 40-year-old Filipino female with a history of right total mastectomy 2 years prior for a low-grade phyllodes tumor and no other medical comorbidities was admitted due to stillbirth. She was noted to have bipedal edema with a positive COVID-19 RT-PCR swab. Further workup revealed a serum creatinine 1.04 mg/dL, urine RBC 1/HPF and a 24-h urine protein of 9.22 g with hypoalbuminemia and dyslipidemia. Serologic workup was noted to be negative. She was started on Losartan, Atorvastatin, and Furosemide. A kidney biopsy was performed which demonstrated unremarkable light microscopy and immunofluorescence and widespread podocyte-foot process effacement. These biopsy findings were interpreted to be consistent with minimal change disease. She was started on Prednisone at 1 mg/kg/day with continuation of both Losartan and Atorvastatin. Six weeks after, the patient achieved complete remission with resolution of both hypoalbuminemia and dyslipidemia. She also reports no further recurrence of edema. Case 2 A 61-year-old Filipino male with a history of type 2 diabetes mellitus, hypertension, dyslipidemia and mild COVID-19 infection 4 months prior now presented with diarrhea. A routine COVID-19 RT-PCR swab revealed a re-infection. Physical examination noted bipedal edema. Further workup demonstrated a serum creatinine 3.39 mg/dL, urine RBC 2/HPF and urine ACR 2.6 g/g. Serologic tests were negative. He was diagnosed with Nephrotic Syndrome and underwent kidney biopsy. Findings showed an unremarkable light microscopy and immunofluorescence with widespread podocyte-foot process effacement. These findings were found to be consistent with minimal change disease and acute tubular injury. He was started on Prednisone (1 mg/kg/day), Losartan, Furosemide and Atorvastatin. Eight weeks later, the patient achieved complete remission with resolution of edema. CONCLUSION: It is currently suspected that APOL1 risk variants found in reported cases of COVID-19-associated glomerulopathies are underlying toxic gain-of-function mutations that drive kidney disease.2 It is interesting to note that APOL1 renal risk variants are found exclusively in African-derived chromosomes and are rarely found among European or Asian chromosomes.3 Even though an APOL1 genotyping was not performed, our case reports provide the first examples of MCD among individuals without a high-risk genotype (APOL1) by epidemiology and enlarge the literature on MCD in COVID-19. We posit that there may be other underlying predispositions or mechanisms that may be driving glomerulopathy formation among COVID-19 patients aside from their inherent APOL 1 risk. Both of our patients were started on steroid therapy with a tapering regimen and achieved complete remission on subsequent follow-up. Existing reports suggest that most cases of COVID-19-associated MCD will often achieve resolution of AKI and proteinuria with steroid therapy, even in those with high-risk APOL1 genotype, emphasizing the need for an accurate histologic classification.4 (Figure Presented).