Bakersfield College

While large bowel obstruction (LBO) is a less common cause of bowel obstruction, it has a broad range of differentials. Its most common etiology in the United States is colorectal adenocarcinoma. Patients usually present with diffuse abdominal pain, constipation, abdominal distension, and nausea. Abdominal X-rays can quickly assess bowel dilation, but a CT scan is the gold standard to determine the location and severity of the blockage. The treatment can range from IV fluid to emergent colectomy. A 41-year-old male with a history of bronchitis and hypertension presented for a surgical consult six days post-incarcerated umbilical hernia repair. The patient complained of nausea, diffuse abdominal distension and tenderness, and inability to pass gas. Physical examination revealed a severely distended abdomen with rebound and guarding at the lower right quadrant. CT scan showed severely dilated ascending colon and cecum along with pneumatosis. There was also an obstructing mass at the sigmoid colon. A diagnosis of severe LBO with impending perforation was made, and the patient underwent emergent exploratory laparotomy. Subtotal colectomy was done with anastomosis between the ileum and sigmoid colon. The pathology report showed an 8.0 cm dilated cecum, necrosis of the ascending colon, and diverticulitis with scar fibrosis along the wall of the colonic membrane. The patient had an ileus and kidney injury postoperatively but they subsequently resolved. Diverticulitis is historically common in the elderly population, but recent studies have shown a rising incidence amongyounger individuals. It is a common cause of obstruction but rarely causes severe complications like pneumatosis and perforation that require emergent surgery. When occluded, the mass and patent ileocecal valve can cause closed-loop bowel syndrome. Even though an unhealthy diet is a known trigger for diverticulitis, surgery is possibly anotherfactor in rare cases. Patients of all ages should be educated on the symptoms of diverticular disease, and surgical monitoring is key in those with known diverticulosis.

Advanced digital technologies provide invaluable opportunities for sustainable water management infrastructure. AI and ML are buzzing technologies for esteem data analytics with capabilities to notice complicated patterns and correlations. These are insightful for understanding water treatment and management process elements. Leveraging AI and ML logic for analyzing data generated from water engineering treatment processes, enabling esteem plans, implementing predictive maintenance, and optimizing operational procedures are the core aspects of this study. Extracting applicable insights using complicated data trends facilitates AI and ML to develop initiative-taking water treatment strategies. ML modeling possesses capabilities to predict water demand accurately. This represents anomalies in quality due to potential system failures. Involving technical paradigms in handling wastewater treatment processes is important to mitigate the influence of climate and consumption surge. These processes are critical for managing climate/urbanization pressures on processes with future research directions. AI and ML are capable of resiliently treating wastewater with initiative-taking monitoring and implementing predictive maintenance mechanisms. This involves capabilities to oversee climate fluctuations. This paper depicts about ambivalent capabilities of implementing these technologies by mentioning practical challenges in process. This study is an attempt to explore research directions toward integrating wastewater treatment solutions with AI and ML systems. The motive of this research is to extend the aspects and investigate literature available regarding technical and data analytics potential in managing water resources. This paper underscores capabilities of AI and ML to motivate utilization of advanced technology paradigms for resilient wastewater treatment. Recommendations are included with future research motives for contributing to sustainable water management domain.

Introduction: Facial droop (FD) is a common symptom (45-60%) of stroke so early detection is critical for timely treatment. FD is a part of almost all stroke scales. Our study is to develop a machine learning (ML)/AI based tool that uses an automated detection of FD as one of the components. Our approach uses a normalized value of minor facial expressions called a blendshape. Methods: Google’s Mediapipe was used to create 52 different blendshape values (e.g., left eyebrow raised, right mouth lowered, etc.) from an input image, which were then used as inputs for a simple deep neural network (DNN). We trained this DNN using the blendshapes from 872 images of people with symptoms of facial palsy (FP) and 872 images of people without symptoms exhibiting multiple emotions (neutral, smiling, frowning, etc.). Results: The proposed approach was evaluated on a dataset of facial images of patients with FD and strokes. Our model showed promising results with over 91% test accuracy. This result suggests that the proposed approach is a promising new method for the early detection of FP with high accuracy. The approach is integrated in our ML/AI based tool to replicate different stroke scales. Conclusions: Our model shows that the use of Blendshapes as features in a ML classifier can produce great results in the detection of FP. For greater accuracy, a better dataset with higher quality images as well as unilateral facial expressions (winking, smirks, etc.) should be used. In a future study, a ML model that uses Blendshapes as inputs could be used to classify FP on a scale.

Groundwater is the main source of drinking water for a number of towns in north-eastern Algeria located in the downstream subbasin of the Oued Guebli, namely the urban areas of Ouled Ma'zouz, Hadjria and Guergoura, which are facing a serious threat of groundwater deterioration due to various sources of contaminants.In this respect, the present work focuses on studying the groundwater hydrochemistry of the shallow aquifer within the Collo plain, identifying drinking water quality levels and observing spatial evolution by combining statistical indexing approaches with GIS mapping techniques.To this end, thirty (30) groundwater samples were taken and analysed for thirteen (13) physico-chemical parameters to evaluate water quality.The Entropy-weighted Water Quality Index (EWQI) model was selected to ascertain groundwater potability using the drinking water limits of World Health Organization (WHO).The EWQI mapping showed that 50% of the samples analyzed belong to the "good" water quality class (EWQI<100), 43% to the "fair" quality class (100<EWQI<150), while around 7% of samples belong to the "poor" water quality class (EWQI>150).This poor class is mainly located in the littoral zone to the north-west of the plain (Ouled Ma'zouz), where anthropogenic activities are concentrated, such as agricultural activities and untreated domestic discharges, as well as marine intrusion caused by overexploitation of the aquifer, are considered to have a much greater impact on groundwater quality in the study area.A strong positive correlation was recorded between the EWQI and EC, Na + , Cl -, NO3 -, NH4 + , NO2 -and PO4 3-(R 2 >0.7), revealing that these elements strongly influence the EWQI values and are the elements responsible for the degradation of water quality in the study area.These results will help decision-makers to protect the groundwater of the Collo plain from degrading anthropogenic practices, and to ensure continuous monitoring of water quality and its sustainable management.

Groundwater resources are typically affected by both global climate factors and anthropogenic activities. This influence is most apparent in arid and semi-arid climates of the Saharan desert. With rising temperatures and minimal precipitation, climate variability in these regions has a particularly significant and systemic impact on the chemical composition of shallow aquifer water. In this regard, our study aims to evaluate the climatic effects on groundwater in Saharan environments, using the Ouargla basin as a prime example. Water samples taken from 45 observation piezometers in our selected study area in February and June 2021 were used to assess the overall impact of inter-annual climate variations on salinity within this shallow groundwater basin. The obtained results show that groundwater located in the first three meters of shallow aquifer depth is directly influenced by surface climate. This pattern holds true for both observed seasonal periods. Stratification indices within the saturated zone were found to be positive, indicating an increase in groundwater salinity at lower depths and negative in shallower depths. This suggests a direct climate influence on this groundwater. These findings can be used to enhance sustainable development strategies in such environments, notably by quantifying salt accumulation and efficiently managing salinity exchange between saturated and vadose horizons.

A review of Doru Radosav, ed., Istoriografia românească (București: Editura Academiei Române/ Univers Enciclopedic Gold, 2019), xi + 404 pp. + illustrations; and Victor Spinei and Dorina N. Rusu, eds., Enciclopedia reprezentanților scrisul istoric românesc, five volumes (Suceava: Editura Karl A. Romstorfer al Muzeului Național al Bucovinei, 2021), Vol. I (A–C), XL + 699 pp.; Vol. II (D–K), XXVII + 588 pp.; Vol. III (L–N), XXVII + 443 pp.; Vol. IV (O–R), XXVII + 431 pp.; Vol. V (S–Z), XXVII + 553 pp.; and Victor Spinei and Dorina N. Rusu, “Addenda la Enciclopedia Reprezentanților Scrisului Istoric Românesc,” Memoriile Secției de Științe Istorice și Arheologie a Academiei Română, Seria V, Vol. 41 (2022), pp. 195–250.

In recent years, there has been a growing emphasis on utilizing energy storage to enhance grid resilience against disruptive events. While renewable energy supply continues to expand, gravity-based solutions like pumped hydro remain dominant in the commercial space. However, their geographical limitations constrain availability, scalability, and increase costs for co-locating solar and wind energy. An alternative approach proposes repurposing idle oil and gas wells located closer to existing grid infrastructure, offering a promising and cost-effective solution. This paper addresses the optimization and control of a regenerative drive system coupled to an interior permanent magnet synchronous machine in a 300-meter well with a 100-Newton weight. The study employs a dynamic MATLAB/Simulink model to simulate the operation of the electric drivetrain system during storage and discharge operations. The results demonstrate an initial round-trip efficiency of 85.9% for the electrical system alone and identify crucial factors for maximizing efficiency. The optimized operation and control of the electromechanical drivetrain system hold great potential for minimizing the levelized cost of storage while maximizing efficiency and revenue generation.

Abstract Cotton (Gossypium hirsutum L.) is an important crop in drought‐prone central Texas. Foliar potassium (K) application and skip‐row planting have the potential to improve productivity of rainfed cotton in this region. The objective of this study was to quantify the effects of skip‐row planting and foliar K on cotton lint yield, biomass, nutrient uptake, and lint quality in rainfed cotton from 2017 to 2020. Foliar K was applied at 0, 20, and 40 kg ha−1. Row arrangement treatments consisted of two planting geometries: 2 × 1 skip row and standard full row. Cotton yield was not affected by foliar K in all years or by row spacing in 2017, 2019, or 2020. In 2018 alone, there was greater lint yield from skip row (530 kg ha−1) compared to full row (423 kg ha−1). The skip‐row treatment resulted in significantly lower vegetative biomass and vegetative K uptake, but improved fiber quality. While foliar K application did not impact lint yield, total biomass and vegetative nitrogen and phosphorus uptake were increased with foliar K. There were year‐to‐year differences in seed and vegetative biomass, nutrient uptake, and lint quality, likely driven by differences in rainfall, with 2018 being unusually dry. Weather variation had more impact on cotton productivity than either treatment. However, given that the skip‐row treatment increased quality and yield in the driest year while not affecting yield in wetter years makes it a viable option for cotton producers looking to reduce costs and increase profits in drought‐prone regions.

Abstract. We investigate the role of wildfire smoke on ozone photochemical production (P(O3)) and atmospheric boundary layer (ABL) dynamics in California's Central Valley during June–September from 2016 to 2020. Wildfire events are identified by the Hazard Mapping System (HMS) and the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT). Air quality and meteorological data are analyzed from 10 monitoring sites operated by the California Air Resources Board (CARB) across the Central Valley. On average, wildfires were found to influence air quality in the Central Valley on about 20 % of the total summer days of the study. During wildfire-influenced periods, maximum daily 8 h averaged (MDA8) O3 was enhanced by about 5.5 ppb or 10 % of the median MDA8 (once corrected for the slightly warmer temperatures) over the entire valley. Overall, nearly half of the total exceedances of the National Ambient Air Quality Standards (NAAQS) where MDA8 O3 &gt; 70 ppb occur under the influence of wildfires, and approximately 10 % of those were in exceedance by 5 ppb or less indicating circumstances that would have been in compliance with the NAAQS were it not for wildfire emissions. The photochemical ozone production rate calculated from the modified Leighton relationship was also found to be higher by 50 % on average compared with non-fire periods despite the average diminution of j(NO2) by ∼ 7 % due to the shading effect of the wildfire smoke plumes. Surface heat flux measurements from two AmeriFlux sites in the northern San Joaquin Valley show midday surface buoyancy fluxes decrease by 30 % on average when influenced by wildfire smoke. Similarly, afternoon peak ABL heights measured from a radio acoustic sounding system (RASS) located in Visalia in the southern San Joaquin Valley were found to decrease on average by 80 m (∼ 15 %) with a concomitant reduction of downwelling shortwave radiation of 54 Wm−2, consistent with past observations of the dependence of boundary layer heights on insolation.