Abstract Oilfield systems are a multifaceted ecological niche which consistently experience microbiologically influenced corrosion. However, simulating environmental conditions of an offshore system within the laboratory is notoriously difficult. A novel dual anaerobic biofilm reactor protocol allowed a complex mixed-species marine biofilm to be studied. Interestingly, electroactive corrosive bacteria and fermentative electroactive bacteria growth was supported within the biofilm microenvironment. Critically, the biotic condition exhibited pits with a greater average area which is characteristic of microbiologically influenced corrosion. This research seeks to bridge the gap between experimental and real-world scenarios, ultimately enhancing the reliability of biofilm management strategies in the industry. Importance It is becoming more widely understood that any investigation of microbiologically influenced corrosion requires a multidisciplinary focus on multiple lines of evidence. While there are numerous standards available to guide specific types of testing, there are none that focus on integrating biofilm testing. By developing a novel dual anaerobic reactor model to study biofilms, insights into the different abiotic and biotic corrosion mechanisms under relevant environmental conditions can be gained. Using multiple lines of evidence to gain a holistic understanding, more sustainable prevention and mitigation strategies can be designed. To our knowledge, this is the first time all these metrics have been combined in one unified approach. The overall aim for this paper is to explore recent advances in biofilm testing and corrosion research, to provide recommendations for future standards being drafted. However, it is important to note that this article itself is not intending to serve as a standard.
Abstract Continual challenges due to microbial corrosion are faced by the maritime, offshore renewable and energy sectors. Understanding the biofilm and microbiologically influenced corrosion interaction is hindered by the lack of robust and reproducible physical models that reflect operating environments. A novel dual anaerobic biofilm reactor, using a complex microbial consortium sampled from marine littoral sediment, allowed the electrochemical performance of UNS G10180 carbon steel to be studied simultaneously in anaerobic abiotic and biotic artificial seawater. Critically, DNA extraction and 16S rRNA amplicon sequencing demonstrated the principal biofilm activity was due to electroactive bacteria, specifically sulfate-reducing and iron-reducing bacteria.
Abstract Continual challenges due to microbial corrosion are faced by the maritime, offshore renewable and energy sectors. Understanding the biofilm and microbiologically influenced corrosion interaction is hindered by the lack of robust and reproducible physical models that reflect operating environments. A novel dual anaerobic biofilm reactor, using a complex microbial consortium sampled from a marine littoral sediment, allowed electrochemical performance of UNS G10180 carbon steel to be studied simultaneously in anaerobic abiotic and biotic artificial seawater. Critically, DNA extraction and 16S rRNA amplicon sequencing demonstrated the principal biofilm activity was due to respiratory electrogens, specifically sulphate reducing and iron reducing bacteria.
Abstract Background With the rise in day case surgery, there has been an increase in both nurse-led discharge and patient turnover. Patients recovering from anaesthesia frequently retain less, therefore information delivered to patients regarding post-operative recovery is sometimes lost or forgotten. The aim of this quality improvement project was to improve both the quality of information and the patient satisfaction with the information provided to them upon discharge following laparoscopic cholecystectomy. Methods Patient satisfaction was assessed using questionnaires at baseline and following each Plan- Do-Study-Act (PDSA) cycle. In PDSA 1, a generic discharge summary delivering standard post-operative instructions, was distributed to patients on discharge. For PDSA 2, a detailed leaflet, encompassing information requested by previously surveyed patients, entitled “going home after your gall-bladder surgery” was provided in addition to the discharge summaries. Results At baseline we found all patients were receiving some sort of discharge information after laparoscopic cholecystectomy. Key information such as wound care, dietary advice and expected pain, was frequently missed. We found that patients were not satisfied, with an average reported satisfaction of 55%. After PDSA 1 patient satisfaction rose to 66%. However,the generic discharge summary missed advice for patients going home with drains and driving advice. With introduction of the detailed leaflet, patient reported satisfaction reached 100%. Conclusions Introducing detailed discharge leaflets improved the patient satisfaction with the information they received on discharge. We anticipate this will in turn reduce patient concerns and need to seek further medical attention. Similar leaflets can be distributed for day case operations such as hernias. This serves as a useful measure to aid patient recovery at home and supports a high turnover day case surgery list.
Osteomyelitis is by definition any infection of the bone. It can have a hematogenous or non-hematogenous mechanism of infection, but comorbidities such as cardiovascular disease, diabetes mellitus, and the presence of orthopedic hardware can increase the risk of osteomyelitis. Our case focuses on a 64-year-old Caucasian female with multiple comorbidities who presented with a fractured right patella that was not healing four months after the occurrence of the fracture. The patient reported cramping, fasciculations, and severe pain that was worsening. She also reported that she received nine X-rays from different orthopedists before receiving an MRI, ordered by internal medicine. The MRI showed a small knee effusion with mild generalized edema of the nearby subcutaneous tissues and evidence of nonunion of the fracture as evidenced by fracture fragments of the right patella. The MRI additionally showed increased signal in the bone fragments of the right patella, as well as the anterior and posterior superior rims of the right tibial plateau, concerning for potential osteomyelitis. Referral to infectious disease confirmed the diagnosis of patellar osteomyelitis, a rather rare diagnosis. The patient was promptly started on cefdinir and doxycycline, and within days of starting antibiotic therapy, her right knee pain was reduced to zero. Surgical debridement was not necessary, and the patient was able to resume her daily activities with the pain resolved. The possibility of patients only having to undergo antibiotic treatment for patellar osteomyelitis improves their chances of a full recovery and reduces the risks associated with undergoing surgical debridement.
In this work, we introduce the TriFusion Network, an innovative deep learning framework designed for the simultaneous analysis of auditory, visual, and textual data to accurately assess emotional states. The architecture of the TriFusion Network is uniquely structured, featuring both independent processing pathways for each modality and integrated layers that harness the combined strengths of these modalities to enhance emotion recognition capabilities. Our approach addresses the complexities inherent in multimodal data integration, with a focus on optimizing the interplay between modality-specific features and their joint representation. Extensive experimental evaluations on the challenging AVEC Sentiment Analysis in the Wild dataset highlight the TriFusion Network's robust performance. It significantly outperforms traditional models that rely on simple feature-level concatenation or complex score-level fusion techniques. Notably, the TriFusion Network achieves Concordance Correlation Coefficients (CCC) of 0.606, 0.534, and 0.170 for the arousal, valence, and liking dimensions respectively, demonstrating substantial improvements over existing methods. These results not only confirm the effectiveness of the TriFusion Network in capturing and interpreting complex emotional cues but also underscore its potential as a versatile tool in real-world applications where accurate emotion recognition is critical.
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