Search Results (11)

Background and Objectives: Radical prostatectomy (RP) stands as the predominant instigator of postoperative stress urinary incontinence. Techniques such as the preservation of the neurovascular bundles, bladder neck preservation, and ensuring longer postoperative urethral length have shown positive impacts on continence. The posterior reconstruction is another method that aids in early continence recovery. Anterior suspension as simulator of puboprostatic ligaments is another factor. Materials and Methods: This study was conducted in the Clinic of Urology, University Clinical Center of Serbia, between December 2014 and January 2020, employing a prospective, non-randomized comparative design. Data were meticulously gathered from 192 consecutive patients. The process of regaining continence was monitored at intervals of 1, 3, 6, 12, and 24 months after surgery. The main criterion for assessing the level of urinary continence was the number of pads used daily. Results: The distribution of overall continence rates in the BNP vs. no-BNP group at 3, 6 and 12 months was 86% vs. 60% (p < 0.0001), 89% vs. 67% (p < 0.0001), 93% vs. 83% (p = 0.022). Continence rates in non-posterior reconstruction group (10%, 22%, 34%, and 54% at 1, 3, 6, and 12 months) were statistically significantly lower (p < 0.0001). The patients who underwent urethral suspension exhibited significantly higher rates of overall continence at 1 mo (73% vs. 29%, p < 0.0001), 3 mo (85% vs. 53%, p < 0.001), 6 mo (89% vs. 62%, p < 0.0001), 12 mo (95% vs. 76%, p < 0.0001), and 24 mo (93% vs. 81%, p = 0.007). Patients who underwent urethral suspension had a four-fold greater likelihood of regaining continence (p = 0.015). Conclusions: Patients who underwent urethral suspension or BNP or posterior reconstruction had higher continence rates. Only the urethral suspension was found to be a significant prognostic factor of continence recovery. Full article

Background: Pedicle subtraction osteotomy (PSO) is a powerful tool for sagittal plane correction in patients with rigid adult spinal deformity (ASD); however, it is associated with high intraoperative blood loss and the increased risk of durotomy. The objective of the present study was to identify intraoperative techniques and baseline patient factors capable of predicting intraoperative durotomy. Methods: A tri-institutional database was retrospectively queried for all patients who underwent PSO for ASD. Data on baseline comorbidities, surgical history, surgeon characteristics and intraoperative maneuvers were gathered. PSO aggressiveness was defined as conventional (Schwab 3 PSO) or an extended PSO (Schwab type 4). The primary outcome of the study was the occurrence of durotomy intraoperatively. Univariable analyses were performed with Mann–Whitney U tests, Chi-squared analyses, and Fisher’s exact tests. Statistical significance was defined by p < 0.05. Results: One hundred and sixteen patients were identified (mean age 61.9 ± 12.6 yr; 44.8% male), of whom 51 (44.0%) experienced intraoperative durotomy. There were no significant differences in baseline comorbidities between those who did and did not experience durotomy, with the exception that baseline weight and body mass index were higher in patients who did not suffer durotomy. Prior surgery (OR 2.73; 95% CI [1.13, 6.58]; p = 0.03) and, more specifically, prior decompression at the PSO level (OR 4.23; 95% CI [1.92, 9.34]; p < 0.001) was predictive of durotomy. A comparison of surgeon training showed no statistically significant difference in durotomy rate between fellowship and non-fellowship trained surgeons, or between orthopedic surgeons and neurosurgeons. The PSO level, PSO aggressiveness, the presence of stenosis at the PSO level, nor the surgical instrument used predicted the odds of durotomy occurrence. Those experiencing durotomy had similar hospitalization durations, rates of reoperation and rates of nonroutine discharge. Conclusions: In this large multisite series, a history of prior decompression at the PSO level was associated with a four-fold increase in intraoperative durotomy risk. Notably the use of extended (versus) standard PSO, surgical technique, nor baseline patient characteristics predicted durotomy. Durotomies occurred in 44% of patients and may prolong operative times. Additional prospective investigations are merited. Full article

Background and Objectives: Bone metastasis cancer boards (BMCBs) focusing on the management of bone metastases have been gathering much attention. However, the association of BMCBs with spinal surgery in patients with spinal metastases remains unclear. In this retrospective single-center observational study, we aimed to clarify the effect of a BMCB on spinal metastasis treatment. Materials and Methods: We reviewed consecutive cases of posterior decompression and/or instrumentation surgery for metastatic spinal tumors from 2008 to 2019. The BMCB involved a team of specialists in orthopedics, rehabilitation medicine, radiation oncology, radiology, palliative supportive care, oncology, and hematology. We compared demographics, eastern cooperative oncology group performance status (ECOGPS), Barthel index (BI), number of overall versus emergency surgeries, and primary tumors between patients before (2008–2012) and after (2013–2019) BMCB establishment. Results: A total of 226 patients including 33 patients before BMCB started were enrolled; lung cancer was the most common primary tumor. After BMCB establishment, the mean patient age was 5 years older (p = 0.028), the mean operating time was 34 min shorter (p = 0.025), the mean hospital stay was 34.5 days shorter (p < 0.001), and the mean BI before surgery was 12 points higher (p = 0.049) than before. Moreover, the mean number of surgeries per year increased more than fourfold to 27.6 per year (p < 0.01) and emergency surgery rates decreased from 48.5% to 29.0% (p = 0.041). Patients with an unknown primary tumor before surgery decreased from 24.2% to 9.3% (p = 0.033). Postoperative deterioration rates from 1 to 6 months after surgery of ECOGPS and BI after BMCB started were lower than before (p = 0.045 and p = 0.027, respectively). Conclusion: The BMCB decreased the emergency surgery and unknown primary tumor rate despite an increase in the overall number of spinal surgeries. The BMCB also contributed to shorter operation times, shorter hospital stays, and lower postoperative deterioration rates of ECOGPS and BI. Full article

Jethro’s dialogue with his son-in-law, Moses, in the Book of Exodus 18: 8–26 can be summarised according to the four-fold elements of subsidiarity, communitarian responsibility, delegation, and synodality, which lead to focus in life. The Elder priest of Midian, in north-western Arabia, advises his son-in-law to practise subsidiarity and communitarian ethical responsibility by undertaking the fundamental task of teaching the precepts, statutes, and instructions that would form the backbone of the twelve-tribe nation of Israel. Subsidiarity and delegation were to be exercised by different levels of leadership, together with Moses himself, in the choice of the exemplary leaders who would both teach Israel and judge minor issues among its people. Finally, synodality is advised by Jethro so that the People of Israel and their leaders can reach their ultimate aim in the Promised Land in peace. Subsidiarity, communitarian responsibility, delegation and synodality would bring Israel as a nation gathered around their one God, YHWH, according to the aim for which they were called from slavery in Egypt to freedom in Canaan. Full article

Breaches in the cyberspace due to cyber-physical attacks can harm the physical space, and any type of vehicle is an alluring target for wrongdoers for an assortment of reasons. Especially, as the automobiles are becoming increasingly interconnected within the Cooperative Intelligent Transport System (C-ITS) realm and their level of automation elevates, the risk for cyberattacks augments along with the attack surface, thus inexorably rendering the risk of complacency and inaction sizable. Next to other defensive measures, intrusion detection systems (IDS) already comprise an inextricable component of modern automobiles in charge of detecting intrusions in the system while in operation. This work concentrates on in-vehicle IDS with the goal to deliver a fourfold comprehensive survey of surveys on this topic. First, we collect and analyze all existing in-vehicle IDS classifications and fuse them into a simpler, overarching one that can be used as a base for classifying any work in this area. Second, we gather and elaborate on the so-far available datasets which can be possibly used to train and evaluate an in-vehicle IDS. Third, we survey non-commercial simulators which may be utilized for creating a dataset or evaluating an IDS. The last contribution pertains to a thorough exposition of the future trends and challenges in this area. To our knowledge, this work provides the first wholemeal survey on in-vehicle IDS, and it is therefore anticipated to serve as a groundwork and point of reference for multiple stakeholders at varying levels. Full article

Artificial Intelligence (AI) is the revolutionary paradigm to empower sixth generation (6G) edge computing based e-healthcare for everyone. Thus, this research aims to promote an AI-based cost-effective and efficient healthcare application. The cyber physical system (CPS) is a key player in the internet world where humans and their personal devices such as cell phones, laptops, wearables, etc., facilitate the healthcare environment. The data extracting, examining and monitoring strategies from sensors and actuators in the entire medical landscape are facilitated by cloud-enabled technologies for absorbing and accepting the entire emerging wave of revolution. The efficient and accurate examination of voluminous data from the sensor devices poses restrictions in terms of bandwidth, delay and energy. Due to the heterogeneous nature of the Internet of Medical Things (IoMT), the driven healthcare system must be smart, interoperable, convergent, and reliable to provide pervasive and cost-effective healthcare platforms. Unfortunately, because of higher power consumption and lesser packet delivery rate, achieving interoperable, convergent, and reliable transmission is challenging in connected healthcare. In such a scenario, this paper has fourfold major contributions. The first contribution is the development of a single chip wearable electrocardiogram (ECG) with the support of an analog front end (AFE) chip model (i.e., ADS1292R) for gathering the ECG data to examine the health status of elderly or chronic patients with the IoT-based cyber physical system (CPS). The second proposes a fuzzy-based sustainable, interoperable, and reliable algorithm (FSIRA), which is an intelligent and self-adaptive decision-making approach to prioritize emergency and critical patients in association with the selected parameters for improving healthcare quality at reasonable costs. The third is the proposal of a specific cloud-based architecture for mobile and connected healthcare. The fourth is the identification of the right balance between reliability, packet loss ratio, convergence, latency, interoperability, and throughput to support an adaptive IoMT driven connected healthcare. It is examined and observed that our proposed approaches outperform the conventional techniques by providing high reliability, high convergence, interoperability, and a better foundation to analyze and interpret the accuracy in systems from a medical health aspect. As for the IoMT, an enabled healthcare cloud is the key ingredient on which to focus, as it also faces the big hurdle of less bandwidth, more delay and energy drain. Thus, we propose the mathematical trade-offs between bandwidth, interoperability, reliability, delay, and energy dissipation for IoMT-oriented smart healthcare over a 6G platform. Full article

Background: Aggravated by the COVID-19 pandemic, the provision of palliative care for patients with palliative care needs emerges as a necessity more than ever. Most are managed in primary care by their family physicians (FP). This study aimed to understand the perspectives of specialist and trainee FPs about their role in palliative care. Methods: we conducted a double focus-group study consisting of two separate online focus-groups, one with FP specialists (n = 9) and one with FP trainees (n = 10). Results: FPs already gather two fundamental skills for the provision of palliative care: the capacity to identify patients’ needs beyond physical symptoms and the recognition that the patient belongs to a familiar, psychosocial, and even spiritual environment. They perceive their role in palliative care to be four-fold: early identification of patients with palliative care needs, initial treatment, symptom management, and patient advocacy. Participants recognized the need for palliative care training and provided suggestions for training programs. Conclusion: FPs share a holistic approach and identify multiple roles they can play in palliative care, from screening to care and advocacy. Organizational barriers must be addressed. Short training programs that combine theory, practice, and experiential learning may further the potential for FPs to contribute to palliative care. Full article

My paper analyses the 15th-century seven-sacraments font at the medieval church of St Peter and St Paul at Salle in Norfolk (England). The church guides and gazetteers that describe the font, and the church in which it is situated, owe both their style and content to Art History, focusing as they do on their material and aesthetic dimensions. The guides also tend towards isolating the various elements of the font, and these in turn from the rest of the architectural elements, fittings and furniture of the church, as if they could be meaningfully experienced or interpreted as discrete entities, in isolation from one another. While none of the font descriptions can be faulted for being inaccurate, they can, as a result of these tendencies, be held insufficient, and not quite to the purpose. My analysis of the font, by means of Heidegger’s concept of Dwelling, does not separate the font either from the rest of the church, nor from other fonts, but acknowledges that it comes to be, and be seen as, what it is only when considered as standing in ‘myriad referential relations’ to other things, as well as to ourselves. This perspective has enabled me to draw out what it is about the font at Salle that can be experienced as not merely beautiful or interesting, but also as meaningful to those—believers and non-believers alike—who encounter it. By reconsidering the proper mode of perceiving and engaging with the font, we may spare it from being commodified, from becoming a unit in the standing reserve of cultural heritage, and in so doing, we, too, may be momentarily freed from our false identities as units of production and agents of consumption. The medieval fonts and churches of Norfolk are, I argue, not valuable as a result of their putative antiquarian qualities, but invaluable in their extending to us a possibility of dwelling—as mortals—on the earth—under the sky—before the divinities. Full article

Face recognition is a technology with great potential in the field of robotics, due to its prominent role in human-robot interaction (HRI). This interaction is a keystone for the successful deployment of robots in areas requiring a customized assistance like education and healthcare, or assisting humans in everyday tasks. These unconstrained environments present additional difficulties for face recognition, extreme head pose variability being one of the most challenging. In this paper, we address this issue and make a fourfold contribution. First, it has been designed a tool for gathering an uniform distribution of head pose images from a person, which has been used to collect a new dataset of faces, both presented in this work. Then, the dataset has served as a testbed for analyzing the detrimental effects this problem has on a number of state-of-the-art methods, showing their decreased effectiveness outside a limited range of poses. Finally, we propose an optimization method to mitigate said negative effects by considering key pose samples in the recognition system’s set of known faces. The conducted experiments demonstrate that this optimized set of poses significantly improves the performance of a state-of-the-art, cutting-edge system based on Multitask Cascaded Convolutional Neural Networks (MTCNNs) and ArcFace. Full article

The chemical composition of eight (seven shoot and one inflorescence) essential oils (EOs) of Rh. tomentosum H. plants growing in Eastern Lithuania is reported. The plant material was collected during different phases of vegetation (from April to October). The oils were obtained by hydrodistillation from air-dried aerial parts (leaves and inflorescences). In total, up to 70 compounds were identified by GC−MS and GC (flame-ionization detector, FID); they comprised 91.0 ± 4.7%–96.2 ± 3.1% of the oil content. Sesquiterpene hydrocarbons (54.1 ± 1.5%–76.1 ± 4.5%) were found to be the main fraction. The major compounds were palustrol (24.6 ± 2.6%–33.5 ± 4.4%) and ledol (18.0 ± 2.9%–29.0 ± 5.0%). Ascaridol isomers (7.0 ± 2.4%–14.0 ± 2.4% in three oils), myrcene (7.2 ± 0.3% and 10.1 ± 1.3%), lepalol (3.3 ± 0.3% and 7.9 ± 3.0%), and cyclocolorenone isomers (4.1 ± 2.5%) were determined as the third main constituents. The toxic activity of marsh rosemary inflorescence and shoot oils samples was evaluated using a brine shrimp (Artemia sp.) bioassay. LC₅₀ average values (11.23–20.50 µg/mL) obtained after 24 h of exposure revealed that the oils were notably toxic. The oil obtained from shoots gathered in September during the seed-ripening stage and containing appreciable amounts of palustrol (26.0 ± 2.5%), ledol (21.5 ± 4.0%), and ascaridol (7.0 ± 2.4%) showed the highest toxic activity. Radical scavenging activity of Rh. tomentosum EOs depended on the plant vegetation stage. The highest activities were obtained for EOs isolated from young shoots collected in June (48.19 ± 0.1 and 19.89 ± 0.3 mmol/L TROLOX (6-hydroxy-2,5,7,8-tetra-methylchromane-2-carboxylic acid) equivalent obtained by, respectively, ABTS^•+ (2,2′-amino-bis(ethylbenzothiazoline-6-sulfonic acid) diammonium salt) and DPPH^•(2,2-diphenyl-1-picrylhydrazyl) assays). Agar disc diffusion assay against pathogenic yeast Candida parapsilosis revealed the potential antifungal activity of EOs. An alternative investigation of antifungal activity employed mediated amperometry at yeast Saccharomyces cerevisiae-modified electrodes. The subjection of yeast cells to vapors of EO resulted in a three to four-fold increase of electrode responses due to the disruption of yeast cell membranes. Full article

Recently, global climate change discussions have become more prominent, and forests are considered as the ecosystems most at risk by the consequences of climate change. Wildfires are among one of the main drivers leading to losses in forested areas. The increasing availability of free remotely sensed data has enabled the precise locations of wildfires to be reliably monitored. A wildfire data inventory was created by integrating global positioning system (GPS) polygons with data collected from the moderate resolution imaging spectroradiometer (MODIS) thermal anomalies product between 2012 and 2017 for Amol County, northern Iran. The GPS polygon dataset from the state wildlife organization was gathered through extensive field surveys. The integrated inventory dataset, along with sixteen conditioning factors (topographic, meteorological, vegetation, anthropological, and hydrological factors), was used to evaluate the potential of different machine learning (ML) approaches for the spatial prediction of wildfire susceptibility. The applied ML approaches included an artificial neural network (ANN), support vector machines (SVM), and random forest (RF). All ML approaches were trained using 75% of the wildfire inventory dataset and tested using the remaining 25% of the dataset in the four-fold cross-validation (CV) procedure. The CV method is used for dealing with the randomness effects of the training and testing dataset selection on the performance of applied ML approaches. To validate the resulting wildfire susceptibility maps based on three different ML approaches and four different folds of inventory datasets, the true positive and false positive rates were calculated. In the following, the accuracy of each of the twelve resulting maps was assessed through the receiver operating characteristics (ROC) curve. The resulting CV accuracies were 74%, 79% and 88% for the ANN, SVM and RF, respectively. Full article