Search

Background: Psoriasis is a chronic immune-mediated inflammatory skin disease, it is a disorder of both the innate and adaptive immune system. However, new updates are still emerging in its pathogenesis. Psoriasis is characterized by overexpression of antimicrobial peptides. Granulysin (GNLY) is an antimicrobial peptide that may have a role in psoriasis pathogenesis. Objective: To detect the level of serum and tissue (GNLY) in psoriatic patients and correlate it with psoriasis severity. Patients and Methods: The study was performed on 50 individuals, including 2 groups. The first group included 30 psoriasis vulgaris patients and the second group included 20 age and sex matched apparently healthy control individuals. Serum GNLY was determined in all individuals and tissue GNLY was determined in the skin of 8 patients (from lesional and perilesional skin) and 8 controls. Results: serum GNLY was slightly higher in patients group compared to control group with no statistically significant difference while, the level of tissue GNLY of lesional and perilesional skin in psoriatic patients, was significantly higher when compared to control group. Conclusion: In conclusion, granulysin is supposed to play a role in psoriasis pathogenesis and it is positively correlated with psoriasis severity

Bridge pier is a common feature in hydraulic structure. Its impact to the river usually occurs in group form rather than a single pier, so this challenging pier-group influence towards river hydraulics and turbulence needs to be explored. In this paper, the measurements were conducted using an Acoustic Doppler Velocimeter (ADV) to study velocities in three dimensions (longitudinal, transversal, and vertical). Based on the experimental data, we have observed reversed depth-averaged velocity vector after each pier in the group of three-pier. The analysis has been conducted on the contribution of each bursting event to Reynolds shear stress (RSS) generation, in order to identify the critical bursting events and turbulence structures around the piers. In the upstream near-wake flow in the bed-wall layer, strong sweep and ejection events have been observed; while at downstream, sweeps were more dominant. The pattern of bursting changed in the outer layer of flow, where ejections were more dominant. Furthermore, the contribution fractional ratio to RSS variation at hole size H = 0 indicates that sweeps and ejections were significantly generated at the near wake-flow in upstream.

Educational statistics have shown a growing number of students with special educational needs (SEN), such as learning disorders accepted into different university programs; empirical evidence indicates that they still face difficulties in adapting to the learning environment and education process. In contrast, little empirical research in developing countries has tested strategies that universities can adopt to support these students. Nevertheless, our preliminary study revealed that many Egyptian universities remain unprepared to deal with disabled students. This study has taken a further significant step in contributing to both theory and practice and helps address some gaps in the current body of literature through: (a) Providing a deeper understanding of students with SEN, explicitly learning disorder in developing countries. (b) Outlining some supportive strategies needed to be addressed by universities to meet the needs of these students before and during their course study. (c) Developing and validating a mathematical model predicting and examining the perceived effectiveness of these strategies. The current study used mixed methods research (MMR) as a methodological research paradigm for gathering, assessing, and mixing both qualitative and quantitative approaches to enhance the integrity of the research finding and comprehensively understand a research phenomenon. The developed questionnaire was pretested, and feedback from the pretest and the panel of experts was used to revise the survey instrument. The reliability of instruments was assessed and showed high using internal consistency (Cronbach's alpha > 0.8). Multiple regression analysis with its associated statistical inference tests was applied. Based on our findings, the study has made a number of important managerial and academic implications. These findings provide valuable guidance for researchers and practitioners, open areas for future research, and add empirical weight to research addressing developing countries.

Background:. This study aimed to compare the oncological and functional outcomes of primary whole gland cryoablation of the prostate using the variable ice cryoprobe (V-Probe®) and the conventional fixed-size ice probe. Materials and methods:. We reviewed the Cryo On-Line Data Registry for men who were treated with primary whole gland prostate cryoablation from 2000 through 2017. A multivariate Cox proportional hazards model was used to compare timing to biochemical recurrence between the V-Probe® and fixed-size ice probe after adjusting for preoperative prostate-specific antigen (PSA), neoadjuvant androgen deprivation therapy, preoperative Gleason score, and preoperative T stage. Results:. A total of 1124 men were included. Median age, Gleason score, and pretreatment PSA were 70 years (interquartile range [IQR]: 65–74 years), 7 (IQR: 6–7) and 5.9 ng/mL (IQR: 4.6–8.1 ng/mL), respectively. The median follow-up time was 25.0 months (IQR: 11.2–48.6 months). V-Probes® were used in 269 (23.9%) cases and fixed-size ice probes in 858 (76.1%) cases. After adjusting for clinical T stage, PSA, neoadjuvant androgen deprivation therapy and preoperative Gleason score, on the multivariate Cox regression model, we found that there was no significant difference between the type of probe and timing to biochemical recurrence (p = 0.35). On multivariate logistic regression, using the V-Probe® was associated with a 91% increase in postoperative urinary retention compared to the fixed-size ice probe (p = 0.003). Conclusions:. The use of the V-Probe® versus conventional fixed-size ice probe was not associated with a difference in biochemical recurrence in patients undergoing primary cryoablation of the prostate.

Background: Proximal fifth metatarsal fractures are among the most common forefoot injuries in athletes. The management of this injury can be challenging because of delayed union and refractures. Intramedullary (IM) screw fixation rather than nonoperative management has been recommended in the athletic population. Purpose: To provide an updated summary of the return-to-play (RTP) rate and time to RTP after Jones fractures in athletes with regard to their management, whether operative or nonoperative, and to explore the union rate and time to union as well as the rate of complications such as refractures. Study Design: Meta-analysis. Methods: Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, 2 independent team members searched several databases including PubMed, MEDLINE, Embase, Google Scholar, Web of Science, Cochrane Library, and ClinicalTrials.gov through November 2019 to identify studies reporting on Jones fractures of the fifth metatarsal exclusively in athletes. The primary outcomes were the RTP rate and time to RTP, whereas the secondary outcomes were the number of games missed, time to union, and union rate as well as the rates of nonunion, delayed union, and refractures. Results: Of 168 studies identified, 22 studies were eligible for meta-analysis with a total of 646 Jones fractures. The overall RTP rate was 98.4% (95% CI, 97.3%-99.4%) in 626 of 646 Jones fractures. The RTP rate with IM screw fixation only was 98.8% (95% CI, 97.8%-99.7%), with other surgical fixation methods (plate, Minifix) was 98.4% (95% CI, 95.8%-100.0%), and with nonoperative management was 71.6% (95% CI, 45.6%-97.6%). There were 3 studies directly comparing RTP rates with surgical versus nonoperative management, which showed significant superiority in favor of surgery (odds ratio, 0.033 [95% CI, 0.005-0.215]; P < .001). The RTP rate according to type of sport was 99.0% (95% CI, 97.5%-100.0%) in football, 91.1% (95% CI, 82.2%-99.4%) in basketball, and 96.6% (95% CI, 92.6%-100.0%) in soccer. The overall time to RTP was 9.6 weeks (95% CI, 8.5-10.7 weeks). The time to RTP in the surgical group (IM screw fixation) was 9.6 weeks (95% CI, 8.3-10.9 weeks), which was significantly less than that in the nonoperative group of 13.1 weeks (95% CI, 8.2-18.0 weeks). The pooled union rate in the operative group (excluding refractures) was 97.3% (95% CI, 95.1%-99.4%), whereas the pooled union rate in the nonoperative group was 71.4% (95% CI, 49.1%-93.7%). The overall time to union was 9.1 weeks (95% CI, 7.7-10.4 weeks). The time to union with IM screw fixation (8.2 weeks [95% CI, 7.5-9.0 weeks]) was shorter than that with nonoperative treatment (13.7 weeks [95% CI, 12.7-14.6 weeks]). The rate of delayed union was 2.5% (95% CI, 1.2%-3.7%), and the overall refracture rate was 10.2% (95% CI, 5.9%-14.5%). Conclusion: The RTP rate and time to RTP after the surgical management of Jones fractures in athletes were excellent, regardless of the implant used and type of sport. IM screw fixation was superior to nonoperative management, as it led to a higher rate of RTP, shorter time to RTP, higher rate of union, shorter time to union, and improved functional outcomes. We recommend surgical fixation for all Jones fractures in athletes.

© 1963-2012 IEEE. Achieving high estimation accuracy is significant for semantic simultaneous localization and mapping (SLAM) tasks. Yet, the estimation process is vulnerable to several sources of error, including limitations of the instruments used to perceive the environment, shortcomings of the employed algorithm, environmental conditions, or other unpredictable noise. In this article, a novel stacked long short-term memory (LSTM)-based error reduction approach is developed to enhance the accuracy of semantic SLAM in presence of such error sources. Training and testing data sets were constructed through simulated and real-time experiments. The effectiveness of the proposed approach was demonstrated by its ability to capture and reduce semantic SLAM estimation errors in training and testing data sets. Quantitative performance measurement was carried out using the absolute trajectory error (ATE) metric. The proposed approach was compared with vanilla and bidirectional LSTM networks, shallow and deep neural networks, and support vector machines. The proposed approach outperforms all other structures and was able to significantly improve the accuracy of semantic SLAM. To further verify the applicability of the proposed approach, it was tested on real-time sequences from the TUM RGB-D data set, where it was able to improve the estimated trajectories.

The highly contagious virus, SARS-CoV-2 causing a human respiratory disease, COVID-19, imposed a global pandemic with significant short- and long-term health consequences. It has challenged the active treatment of oncology patients, having protocols that require frequent monitoring. Some patients' anxiety of the COVID-19 pandemic led to delays in treatment and impaired the effectiveness of anti-cancer therapy. Moreover, the stage migration term was coined to newly referred patients who postponed their doctor's appointment leading to late diagnosis. Prevention of COVID-19 disease among oncology patients is a priority, in order to avert morbidity, complications and mortality. In a recently published article, Waissengrin et al. compared the incidence of COVID-19 disease in oncology patients at Tel-Aviv Medical Center to the general population between March 2020 and October 2020. A lower rate of confirmed cases was demonstrated among oncology patients in comparison to the general population. This difference was attributed to the oncology patients' adherence to COVID-19 avoidance guidelines. In addition, no association was found between a specific type of cancer or oncological treatment and mortality from COVID-19. However, a significant correlation was presented between severe COVID-19 disease, old age and the presence of metastases. Waissengrin et al., support the importance of continuing the oncological care routine to avoid the devastating consequences of postponing treatments. Despite the development of a number of FDA-approved vaccines against the virus, the world is still facing challenges associated with the COVID-19 pandemic, e.g. variant B.1.617.2 ominous of yet more lockdowns due to a rapid rising wave of morbidity.

Vesico-vaginal fistula, is a known complication that can occur following damage to the bladder wall during pelvic surgery or prolonged birth. Prompt and accurate diagnosis and timely repair are essential for a quick solution to the problem, and a reduction in medico-legal claims. Successful treatment requires an accurate assessment of the size and the location of the fistula, determination of timing and the surgical technique. There is an approach that advocates postponing the surgery for several months until "tissue healing" subsides and some advocate immediate repair. In our department, the surgery is performed early, immediately upon diagnosis without delay. The aim of the work is to define the clinical manifestation of fistula after surgery, to analyze the factors, and to summarize the experience of an early intervention.We reviewed the records of consecutive patients undergoing repair of urogenital fistulas at our institution. Patients with only vesico-vaginal fistulas were included. We recorded demographic characteristics, as well as surgical data, and postoperative complications were also collected. The follow-up period was at least 3 months.A total of 67 women with urogenital fistulas were identified, of whom 37 were only with vesico-vaginal fistulas. Iatrogenic injury, during hysterectomy was the main cause in 70.3%; 2 women were treated conservatively. A repair in the vaginal approach was performed in 31 women, and in 4 women the repair was performed in the abdominal approach, of them, two underwent urethral re-implantation simultaneously. Complications included sepsis in one case, and vaginal cuff dehiscence in another. The success rate of the repair was 92%. Recurrence occurred in 3 patients, of whom 2 had a history of previous radiation.A vesico-vaginal fistula can be successfully repaired by early repair, without delay, thus saving the patient considerable distress and discomfort.

The objective of this report is to present the use and efficacy of ado-trastuzumab as an advanced line of therapy in salivary duct carcinoma (SDC) patient. An 84-year-old gentleman diagnosed with metastatic salivary duct tumor harboring overexpressed human epidermal growth factor receptor-2 has gone through resection surgery. The first line of treatment included initial doublet chemotherapy combined with trastuzumab, which was continued later as maintenance. PET-CT follow-up for 4 years has demonstrated no evidence of disease. However, upon recurrence, use of Ado-trastuzumab emtansine was prompted as second-line of treatment. This targeted patient-tailored therapy has accomplished a complete response. The effectiveness of ado-trastuzumab emtansine was notable within a short time period of two treatment cycles leading to full recovery. Specific agents aimed at altered oncogenes should be considered as a potential drug of choice in neoadjuvant HER2 positive SDC.

Myoepithelial tumor is a rare form of cancer, mainly arising from the salivary glands and extremities. Due to its rarity, no formal treatment guidelines exist. Here we report a case of a male patient diagnosed with metastatic myoepithelial tumor which was successfully treated with an androgen-receptor (AR) antagonist (bicalutamide), based on the results of molecular testing. Six years after the initiation of bicalutamide, patient was diagnosed with metastatic prostate cancer. To our knowledge, this is the first case described in literature that demonstrate the effectiveness of anti-androgens in treating myoepithelial tumor. Vigilance should be maintained when screening these patients for prostate cancer as their 'true' prostate specific antigen levels might be masked by the ongoing endocrine therapy.

The BNT162b2 vaccine was shown to be highly effective in reducing the risk of COVID-19 infection in healthy individuals and patients with chronic disease. However, there are little data regarding its efficacy in patients treated for cancer. We analyzed the humoral response following vaccination with the second dose of BNT162b2 in 140 patients with solid malignancies who were receiving anti-cancer therapy at the time of vaccination and 215 participants who had not been diagnosed with cancer. Multivariate analysis was performed, followed by matching the two groups by age, gender and days from vaccination. The humoral response in the cancer patient group was significantly lower than in the non-cancer group: 20/140 seronegative (14.3%) vs. 3/215 (1.4%), p &lt, 0.001, median IgG levels 2231 AU/mL (IQR 445-8023) vs. 4100 (IQR 2231-6774) p = 0.001 respectively. The odds ratio for negative serology results in cancer patients adjusted by age and gender was 7.35 compared to participants without cancer. This effect was observed only in chemotherapy treated patients: 17/73 seronegative (23.3%) vs. 3/215 (1.4%), p &lt, median IgG 1361 AU/mL vs. 4100, p &lt, 0.001 but not in patients treated with non-chemotherapeutic drugs. Reduced immunogenicity to COVID-19 vaccine among chemotherapy-treated cancer patients, raises the need to continue exercising protective measures after vaccination in these patients.

Research studies on quadrotors have recently drawn significant interest from academia and industry. Faults and failures handling are the major weaknesses of conventional quadrotor platforms; therefore, an innovative actuation mechanism was introduced to allow tilting the rotors. Tilting rotors of multirotor platforms provide high dexterity for flying between adjacent obstacles and assist the platforms in dealing with various failure scenarios. This paper reviews the state of the research on tilt-quadrotor platforms. Several platforms, software and hardware architectures, were discussed in the literature. Most of the latest developments were focused on conventional quadrotor modelling, combined with rotor tilting dynamics. On the other hand, controlling such platform was mainly studied using two types of controllers: Feedback Linearisation technique and Control Allocator. Recovery strategy in case of fault or failure has been covered extensively for conventional quadrotors, but very limited known work for tilt-quadrotor. This review concludes that the system dynamic modelling is relatively well covered compared to exploring new control techniques for more stringent requirements. However, recovery strategies as the main advantage of tilt-quadrotor platforms are not explored extensively and require more research attention.

Populations' allele frequency studies are one of the major topics of Population genetics. In this research, an Allele Frequency Quality Control System (AFQCS) is proposed as a verification tool for populations' genetics data. This system visualizes and analyses statistically the allele frequencies of 15 Short Tandem Repeats (STRs) autosomal loci based on 65 previously published population genetics studies. Allele Frequency Trajectories (AFTs) for all addressed populations were plotted. The AFTs showed a distinct trend for each locus, which was used to build a global reference template for these loci. Pearson's Correlation Coefficient Matrices (CCM) generated for each locus were used to calculate different statistical parameters to assess the genetic populations' relationships, such as histogram, median, interquartile range, and p-value. P-values and interquartile ranges supported the visualization results by indicating the presence of a global AFT pattern for each locus. The novel developed AFTs template illuminates the idea of the first quality control system for testing new datasets, based on the high genetic similarity among populations. From CCMs statistical results, wide spectrums recorded in loci TH01, D13S317, D2S1338, D18S51, and FGA indicate significant populations' genetics heterogeneity.

Lung cancer is a worldwide prevalent malignancy. This disease has a low survival rate due to diagnosis at a late stage challenged by the involvement of metastatic sites. Non-small-cell lung cancer (NSCLC) is presented in 85% of cases. The last decade has experienced substantial advancements in scientific research, leading to a novel targeted therapeutic approach. The newly developed pharmaceutical agents are aimed towards specific mutations, detected in individual patients inflicted by lung cancer. These drugs have longer and improved response rates compared to traditional chemotherapy. Recent studies were able to identify rare mutations found in pulmonary tumors. Among the gene alterations detected were mesenchymal epithelial transition factor (MET), human epidermal growth factor 2 (HER2), B-type Raf kinase (BRAF), c-ROS proto-oncogene (ROS1), rearranged during transfection (RET) and neurotrophic tyrosine kinase (NTRK). Ongoing clinical trials are gaining insight onto possible first and second lines of medical treatment options intended to enable progression-free survival to lung cancer patients.

The ability to decide if a solution to a pose-graph problem is globally optimal is of high significance for safety-critical applications. Converging to a local-minimum may result in severe estimation errors along the estimated trajectory. In this paper, we propose a graph neural network based on a novel implementation of a graph convolutional-like layer, called PoseConv, to perform classification of pose-graphs as optimal or sub-optimal. The operation of PoseConv required incorporating a new node feature, referred to as cost, to hold the information that the nodes will communicate. A training and testing dataset was generated based on publicly available bench-marking pose-graphs. The neural classifier is then trained and extensively tested on several subsets of the pose-graph samples in the dataset. Testing results have proven the model’s capability to perform classification with 92 – 98% accuracy, for the different partitions of the training and testing dataset. In addition, the model was able to generalize to previously unseen variants of pose-graphs in the training dataset. Our method trades a small amount of accuracy for a large improvement in processing time. This makes it faster than other existing methods by up-to three orders of magnitude, which could be of paramount importance when using computationally-limited robots overseen by human operators.

The emergence of immune checkpoint inhibitors (ICIs) has revolutionized the field of oncology. For many cancer types, treatment paradigms have changed, as immunotherapy is increasingly being integrated into frontline standard-of-care treatments and producing meaningful and prolonged responses. This has inspired an avalanche of clinical trials studying ICIs in all types of malignancies, including gynecological cancers. Ovarian and endometrial cancers are characterized by DNA damage repair defects, either via disruption of the homologous recombination DNA repair mechanism in the former or via defects in the mismatch repair (MMR) pathway in the latter, which lead to a high load of neoantigens in both. Cervical cancer is dependent on the expression of human papillomavirus (HPV) proteins, which induce an immune response. Regardless, clinical trials testing ICIs in gynecological malignancies have initially led to disappointing results. Despite durable responses in some patients, overall response rates have been dismal. Nevertheless, in recent years, with the development of better predictive tumor biomarkers, such as microsatellite instability for endometrial cancer and programmed death ligand 1 for cervical cancer, ICIs have found their way into routine treatments for patients with advanced-stage disease. ICI-based combinations, although adding toxicity, have further improved response rates, and new combinations are currently being tested in clinical trials, as are other immunotherapy modalities, such as adoptive cell transfer and HPV-based vaccines. This review summarizes current clinical evidence supporting the use of immunotherapy in gynecological malignancies and describes studies in progress, with a focus on ICIs and predictive response biomarkers.

Introduction The aim of our study was to evaluate whether a biopsy from the tumor base after transurethral resection of bladder tumor (TURBT) has an impact on subsequent management of patients with bladder tumors. While tumor base biopsy at the completion of TURBT is a common practice, there is no definition of its role within the major international professional guidelines. Material and methods We retrospectively reviewed the records of consecutive patients undergoing TURBT between 2015 and 2019 at our institution. We recorded demographic and tumor characteristics of initial TURBT, tumor base biopsy and restaging TURBT pathology outcomes. The pathologic outcomes were correlated to assess the additional value of a separate tumor base biopsy. Results A total of 532 patients underwent TURBT. A separate tumor base biopsy after completion of TURBT was performed in 154 patients. The mean patient's age was 72.8 ±11.7 years (range 48-94) and 119 (77.2%) were men. In 40 patients (25.9%) muscle was absent in the pathological specimen of the tumor resection. Muscle was present in all but 6 (3.9%) tumor base biopsies. Of the 33 patients who underwent repeated transurethral resection for pT1 tumors, 2 had residual low-grade pTa, 1 had residual high-grade pT1, and 3 patients were upstaged to pT2. Conclusions Although tumor base biopsy at the completion of TURBT is a common practice, our analysis fails to demonstrate any tangible benefit in the staging of bladder tumors. In our experience tumor base biopsy did not change the management in patients with superficial or muscle invasive disease.

Background There has been a significant increase in the use of immunotherapy and cannabis recently, two modalities that have immunomodulatory effects and may have possible interaction. We evaluated the influence of cannabis use during immunotherapy treatment on response rate (RR), progression-free survival (PFS), and overall survival (OS). Subjects, Materials, and Methods In this retrospective, observational study, data were collected from the files of patients treated with nivolumab in the years 2015–2016 at our hospital, and cannabis from six cannabis-supplying companies. Included were 140 patients (89 nivolumab alone, 51 nivolumab plus cannabis) with advanced melanoma, non-small cell lung cancer, and renal clear cell carcinoma. The groups were homogenous regarding demographic and disease characteristics. A comparison between the two arms was made. Results In a multivariate model, cannabis was the only significant factor that reduced RR to immunotherapy (37.5% RR in nivolumab alone compared with 15.9% in the nivolumab-cannabis group (p = .016, odds ratio = 3.13, 95% confidence interval 1.24–8.1). Cannabis use was not a significant factor for PFS or OS. Factors affecting PFS and OS were smoking (adjusted hazard ratio [HR] = 2.41 and 2.41, respectively (and brain metastases (adjusted HR = 2.04 and 2.83, respectively). Low performance status (adjusted HR = 2.83) affected OS alone. Tetrahydrocannabinol and cannabidiol percentages did not affect RR in any group (p = .393 and .116, respectively). Conclusion In this retrospective analysis, the use of cannabis during immunotherapy treatment decreased RR, without affecting PFS or OS and without relation to cannabis composition. Considering the limitations of the study, further prospective clinical study is needed to investigate possible interaction. Implications for Practice Although the data are retrospective and a relation to cannabis composition was not detected, this information can be critical for cannabis users and indicates that caution is required when starting immunotherapy.

Aerial manipulation has direct application prospects in environment, construction, forestry, agriculture, search, and rescue. It can be used to pick and place objects and hence can be used for transportation of goods. Aerial manipulation can be used to perform operations in environments inaccessible or unsafe for human workers. This paper is a survey of recent research in aerial manipulation. The aerial manipulation research has diverse aspects, which include the designing of aerial manipulation platforms, manipulators, grippers, the control of aerial platform and manipulators, the interaction of aerial manipulator with the environment, through forces and torque. In particular, the review paper presents the survey of the airborne platforms that can be used for aerial manipulation including the new aerial platforms with aerial manipulation capability. We also classified the aerial grippers and aerial manipulators based on their designs and characteristics. The recent contributions regarding the control of the aerial manipulator platform is also discussed. The environment interaction of aerial manipulators is also surveyed which includes, different strategies used for end-effectors interaction with the environment, application of force, application of torque and visual servoing. A recent and growing interest of researchers about the multi-UAV collaborative aerial manipulation was also noticed and hence different strategies for collaborative aerial manipulation are also surveyed, discussed and critically analyzed. Some key challenges regarding outdoor aerial manipulation and energy constraints in aerial manipulation are also discussed.

In this paper, a novel dual-UAV collaborative aerial transport strategy based on energy distribution and load sharing is proposed. This paper presents the first experimental demonstration of dual-UAV collaborative aerial transport while distributing power consumption. The demonstration is performed while distributing the power consumption between two drones sharing a load based on their battery state of charge. A numerical model of the dual-hex-rotor-payload is used to validate the proposed strategy. Numerical and hardware tests were conducted to demonstrate the load distribution using multiple UAV with certain spatial configurations. Finally, collaborative aerial transport test scenarios are performed numerically and experimentally. The simulation and experimental results show the effectiveness and applicability of the proposed strategy.

Semantic simultaneous localization and mapping (SLAM) is susceptible to several sources of noise that hinder the accuracy of its trajectory and map estimates. Such sources include inaccurate landmark pose estimation and sensor limitations. In this paper, a novel deep learning based approach is proposed to improve the accuracy of semantic SLAM by reducing the trajectory estimation error. A deep neural network consisting of various non-linear activation functions is structured and pre-trained by means of an unsupervised greedy layer-wise pre-training technique. The network is then fine-tuned using the adaptive moment estimation (Adam) optimizer. The training datasets were collected using several simulated and realtime experiments and are composed of two parts, the estimated trajectory and the corresponding ground truth. Ground truth trajectories were obtained using a motion capture system in realtime experiments. The effectiveness of the proposed approach was shown through simulated experiments, real-time experiments, and a sequence from the Technical University of Munich (TUM) RGB-D dataset. The performance of the deep neural network (DNN) was tested with different pre-training techniques and the proposed unsupervised greedy layer-wise pre-training technique proved to perform the best across training, validation, and testing datasets in terms of reducing the mean absolute trajectory error (ATE).

Loss ratio is one of the most important indicator that has many strategic decisions applications, such as pricing, underwriting, investment, reinsurance and reserving decisions. It serves as an early warning of financial solvency of insurance companies and it can be judged on the strength of the financial position of these companies. The aim of this study is to identify the reliable time series-forecasting model to forecast loss ratio estimates of fire segment in Misr insurance company. Box-Jenkins Analysis is applied on actual reported loss ratios data for Misr insurance company for the period 1980/1981– 2013/2014. The study concludes that the best forecasting model is ARMA(1,1).

Ureteral reconstructions pose a challenge for urologists. We describe a novel reconstructive technique for long upper ureteral obliteration with an intrarenal pelvis. The obliterated ureteral segment was excised and the healthy segment of the ureter was spatulated and anastomosed end-to-side to the intrarenal lower calyx (ureterocalycostomy). The procedure was successfully performed without any complication. To date, the patient's clinical state, renal function and radiographic imaging are stable without any evidence of deterioration. The described technique is a useful surgical option for select patients with long upper ureteral obliteration and intrarenal pelvis.

Visual simultaneous localization and mapping (SLAM) has attracted high attention over the past few years. In this paper, a comprehensive survey of the state-of-the-art feature-based visual SLAM approaches is presented. The reviewed approaches are classified based on the visual features observed in the environment. Visual features can be seen at different levels; low-level features like points and edges, middle-level features like planes and blobs, and high-level features like semantically labeled objects. One of the most critical research gaps regarding visual SLAM approaches concluded from this study is the lack of generality. Some approaches exhibit a very high level of maturity, in terms of accuracy and efficiency. Yet, they are tailored to very specific environments, like feature-rich and static environments. When operating in different environments, such approaches experience severe degradation in performance. In addition, due to software and hardware limitations, guaranteeing a robust visual SLAM approach is extremely challenging. Although semantics have been heavily exploited in visual SLAM, understanding of the scene by incorporating relationships between features is not yet fully explored. A detailed discussion of such research challenges is provided throughout the paper.

Urban search and rescue missions require rapid intervention to locate victims and survivors in the affected environments. To facilitate this activity, Unmanned Aerial Vehicles (UAVs) have been recently used to explore the environment and locate possible victims. In this paper, a UAV equipped with multiple complementary sensors is used to detect the presence of a human in an unknown environment. A novel human localization approach in unknown environments is proposed that merges information gathered from deep-learning-based human detection, wireless signal mapping, and thermal signature mapping to build an accurate global human location map. A next-best-view (NBV) approach with a proposed multi-objective utility function is used to iteratively evaluate the map to locate the presence of humans rapidly. Results demonstrate that the proposed strategy outperforms other methods in several performance measures such as the number of iterations, entropy reduction, and traveled distance.

Purpose The purpose of this paper is to examine the automotive product recall risk in terms of social sustainability performance and to evaluate the role of buyer‒supplier relationships in improving social sustainability during product recall crises. Design/methodology/approach A multi-methodology approach is used to empirically analyse the interrelationship between the proposed constructs and enablers of the buyer‒supplier relationship. Structural equation modelling and interpretive structural modelling are followed to analyse the data gathered thorough a questionnaire survey of 204 executives and interviews with 15 managers from the automotive industry. Findings The results of the study provide evidence regarding the impact of the responsible buyer‒supplier relationship on customer recall concerns and the social sustainability performance of supply chains (SCs). This study also leads to the development of a conceptual model, providing a relationship between the three key concepts used in this study. Research limitations/implications Following social sustainability principles, this study addresses the importance of developing strong, responsible relational ties with suppliers to reduce vehicle recalls or successfully recover from a product recall crisis. Originality/value This study contributes to the literature by providing theoretical and empirical insights for developing socially responsible SCs and confirming the role of the buyer‒supplier governance mechanism during product recalls in the context of the automotive industry.

There has been an increasing interest in researching, developing and deploying multi-robot systems. This has been driven mainly by: the maturity of the practical deployment of a single-robot system and its ability to solve some of the most challenging tasks. Coverage path planning (CPP) is one of the active research topics that could benefit greatly from multi-robot systems. In this paper, we surveyed the research topics related to multi-robot CPP for the purpose of mapping and model reconstructions. We classified the topics into: viewpoints generation approaches; coverage planning strategies; coordination and decision-making processes; communication mechanism and mapping approaches. This paper provides a detailed analysis and comparison of the recent research work in this area, and concludes with a critical analysis of the field, and future research perspectives.

In this paper, a frequency-domain modeling methodology that can be applied to various multi-rotor aerial vehicles is introduced. The primary contribution of this work is a systematic integration of the first-principles modeling and system identification approaches to generate flight dynamics models with good accuracy. The first-principles modeling and model linearization are conducted to obtain an appropriate baseline model for the subsequent system identification. Next, a four-step parameter identification process, which consists of: (1) baseline model determination; (2) data collection and preprocessing; (3) mode-wise parameter identification; and (4) model fidelity validation, is performed in the frequency domain to identify the uncertain parameters. Our method has been applied to two custom-built multi-rotor aircraft (one X-type quadcopter and one QU4D quadcopter) for efficiency demonstration.

We introduce a simple method to fabricate a highly flexible resistive-type strain sensor composed of carbon paper (CP) and polydimethylsiloxane (PDMS) elastomer. The key resistance sensitive material of the sensor, carbon paper, is prepared from tissue paper by a simple high-temperature pyrolysis process. At the same time, the as-fabricated CP/PDMS strain senor is highly sensitive to applied strain with a gauge factor of 25.3, almost 10 times higher than that of conventional metallic strain gauge. Furthermore, the response of CP/PDMS strain sensor under cyclic tensile strain with a peak strain of 3% was also investigated, which exhibits fast and steady response with excellent durability within the frequency range 0.01–10 Hz. Finally, we demonstrate the successful utilization of the CP/PDMS strain sensor as wearable electronics in breath monitoring and robot controlling. The eminent performance, low material cost, and facile fabrication process make the CP/PDMS strain sensor exceptionally promising in flex...

Approximately one-half of advanced cutaneous melanomas have a V600 mutation in the BRAF gene that activates the mitogen-activated protein kinase pathway. The combination of BRAF plus MEK inhibitors is one of the most effective treatments for these patients. Severe neurological toxicities have been reported in the literature. However, these toxicities are very rare. Here, we present one patient with acute motor and sensory axonal neuropathy, which is a subtype of Guillain-Barre syndrome, secondary to treatment with MEK inhibitors. This side effect had never been described as related to these agents. However, the mitogen-activated protein kinase pathway can be involved in Guillain-Barre syndrome, and awareness of early neurological injury signs is important in patients treated with MEK inhibitors.

The study of genetic correlation between ethnic groups, constituting one nation, is an important issue. This work aims to study the correlation between allele frequencies of nine Short Tandem Repeats (STRs) autosomal loci (D3S1358, VWA, FGA, THO1, TPOX, CSF1PO, D5S818, D13S317, and D7S820) for the main two Egyptian ethnic groups, Muslims and Christians, in order to test the hypothesis of a common ancestral for the whole Egyptian population. Each group is represented by a sample of 100 unrelated healthy individuals. The genetic correlation of the two ethnic groups is investigated using alleles’ frequencies statistics, forensic efficiency parameters and populations’ homogeneity charts. Graphical methods were used to check the harmony between the two ethnic groups. The results support that Egyptian Muslims and Egyptian Christians genetically originate from the same ancestors.

Blockchain technology starts to reconfigure all aspects of society to make it clear and beneficial for the legal system. The chapter introduces “The Blockchain Revolution” in categories 1.0, 2.0, and 3.0; in the form of analyzing the use of the technology that is being applied in new innovative business models, Blockchain 1.0 starts with the creation of the first blockchain and the introduction of the technology in the “Bitcoin Whitepaper,” the crypto-currency model, via Bitcoin's application in services related to cash, payments, and transfers. Blockchain 2.0 starts with the indication that using smart contracts on blockchains will be available via the development of syntax (i.e., “solidity” that would enable developers to create solutions with blockchain technology at the backend). The chapter explores the feature of the new disruptive business models-based blockchain technology as a new approach in delivering business products and services. In the chapter, the authors explore the new technologies raised in different fields of business.

The most critical process in the inspection is the structure coverage which is a time and resource intensive task. In this paper, Search Space Coverage Path Planning (SSCPP) algorithm for inspecting complex structure using a vehicular system consisting of Unmanned Aerial Vehicle (UAV) is proposed. The proposed algorithm exploits our knowledge of the structure model, and the UAV’s onboard sensors to generate coverage paths that maximizes coverage and accuracy. The algorithm supports the integration of multiple sensors to increase the coverage at each viewpoint and reduce the mission time. A weighted heuristic reward function is developed in the algorithm to target coverage, accuracy, travelled distance and turning angle at each viewpoint. The iterative processes of the proposed algorithm were accelerated exploiting the parallel architecture of the Graphics Processing Unit (GPU). A set of experiments using models of different shapes were conducted in simulated and real environments. The simulation and experimental results show the validity and effectiveness of the proposed algorithm.

This paper presents a strategy to autonomously explore unknown indoor environments, focusing on 3D mapping of the environment and performing grid level semantic labeling to identify all available objects. Unlike conventional exploration techniques that utilize geometric heuristics and information gain theory on an occupancy grid map, the work presented in this paper considers semantic information, such as the class of objects, in order to gear the exploration towards environmental segmentation and object labeling. The proposed approach utilizes deep learning to map 2D semantically segmented images into 3D semantic point clouds that encapsulate both occupancy and semantic annotations. A next-best-view exploration algorithm is employed to iteratively explore and label all the objects in the environment using a novel utility function that balances exploration and semantic object labeling. The proposed strategy was evaluated in a realistically simulated indoor environment, and results were benchmarked against other exploration strategies.

Fabrication of anisotropic piezoresistive materials is ultimately important for the realization of multi-loading recognization in robotics, auto-driving, artificial intelligence and health care, etc., whereas most of the existing production strategies are time-consuming and costly. Herein, we applied a simple structural design of carbonized cotton thread (CCT) to produce anisotropic piezoresistive CCT/silicone composites. Specifically, the rectangular wave shaped CCT/silicone composite (Re-CCT) and straight CCT/silicone composite (St-CCT), which exhibit distinct sensing performance to tension and compression, are fabricated. Their sensors’ gauge factor (GF) for tension and compression obeys: GFTen-St > GFCom-St ≈ GFCom-Re > GFTen-Re ≈ 0. Consequently, the flexible multifunctional anisotropic piezoresistive composite integrated with Re-CCT and St-CCT is able to distinguish multiple loading modes, including compression, tension and their combination, via monitoring the micro-deformation applied by a finger and the status of a bottle handled by a robotic hand. The current strategy shows a great promise in manufacturing flexible anisotropic piezoresistive composite sensors for robotics, auto-driving, artificial intelligence and health care applications, etc.