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Synovial sarcoma (SS) is a rare soft tissue sarcoma usually arising in the deep soft tissues of the limbs, trunk, and head and neck region. Due to its rarity, diagnosis can be difficult to establish, especially when it involves an uncommon location like the breast. In this case report, we describe a young woman who was found to have primary SS of the breast. Initial immunohistochemistry staining was focally positive for cytokeratin and S100 and she was misdiagnosed with atypical spindle cell carcinoma. Due to the unusual presentation, further testing was performed which showed TLE1 and epithelial membrane antigen positivity, establishing the diagnosis of SS of the breast. A FISH was later sent out and was positive for SS18-SSX fusion transcript. This case highlights the importance of considering rare histopathology in breast lesions and using additional staining and cytogenetics to confirm diagnosis.

Generative adversarial networks (GANs) have emerged as a powerful generative model in computer vision. Given their impressive abilities in generating highly realistic images, they are also being used in novel ways in applications in the life sciences. This raises an interesting question when GANs are used in scientific or biomedical studies. Consider the setting where we are restricted to only using the samples from a trained GAN for downstream group difference analysis (and do not have direct access to the real data). Will we obtain similar conclusions? In this work, we explore if “generated” data, i.e., sampled from such GANs can be used for performing statistical group difference tests in cases versus controls studies, common across many scientific disciplines. We provide a detailed analysis describing regimes where this may be feasible. We complement the technical results with an empirical study focused on the analysis of cortical thickness on brain mesh surfaces in an Alzheimer’s disease dataset. To exploit the geometric nature of the data, we use simple ideas from spectral graph theory to show how adjustments to existing GANs can yield improvements. We also give a generalization error bound by extending recent results on Neural Network Distance. To our knowledge, our work offers the first analysis assessing whether the Null distribution in “healthy versus diseased subjects” type statistical testing using data generated from the GANs coincides with the one obtained from the same analysis with real data. The code is available at https://github.com/yyxiongzju/GLapGAN.

In this paper a system is developed for monitoring the crops in green house using solar energy. India is an agricultural country and the agricultural sector accounts for 18% of GDP of India. This sector provides 50% employment to Indian workforce. As per 2011 census of India, almost 65% of people are fully dependent on agriculture. In spite of fertile land, crops yields are not more than compared to developed countries. Therefore, it is not wrong to say that from time to time there has been less development and research in agriculture sector. Technology may play a vital role in agricultural sector, because it reduces human effort and time. The developed system is a combination of power electronics and power system in which the system uses GSM technique (Global System for Mobile communication), Arduino, and various sensors to sense the real time data in greenhouse. Using sensor, the system obtains the real time data of the crops and then transmits it on the user mobile. The user can monitor and control the temperature, watering and light through mobile.

The demand and supply gap of energy is large and the people are pressured to bear increasing hours of load losing, unnecessary intake of energy makes subjects even worse. So, the importance and requirement for energy conservation is increased exponentially. This paper outlines a step towards the conservation of electricity in standard and electricity especially with the aid of employing efficient constructing system with automation and installation of renewable based Micro Distributed Generator (MDG). The Smart Grid (SG) is a technological transformation from conventional electric grid, electro-mechanically controlled system, to smart, intelligent, and electronically controlled system. There are about 20–30% losses present in the conventional electric grid due to substandard operations at generation, transmission and distribution side. MDG play important role to build an efficient and autonomous micro-grid. In this paper importance of microgrid and some renewable energy sources utilized in formation of microgrid are discussed.

This article focuses on the motion planning and control of an automated differential-driven two-wheeled E-puck robot using Generalized Regression Neural Network (GRNN) architecture in the Virtual Robot Experimentation Platform (V-REP) software platform among scattered obstacles. The main advantage of this GRNN over the feedforward neural network is that it provides accurate results in a short period with minimal error. First, the designed GRNN architecture receives real-time obstacle information from the Infra-Red (IR) sensors of an E-puck robot. According to IR sensor data interpretation, this architecture sends the left and right wheel velocities command to the E-puck robot in the V-REP software platform. In the present study, the GRNN architecture includes the MIMO system, i.e., multiple inputs (IR sensors data) and multiple outputs (left and right wheel velocities). The three-dimensional (3D) motion and orientation results of the GRNN architecture-controlled E-puck robot are carried out in the V-REP software platform among scattered and wall-type obstacles. Further on, compared with the feedforward neural network, the proposed GRNN architecture obtains better navigation path length with minimum error results.

The fault monitoring and diagnosis of industrial machineries are very significant in Industry 4.0 revolution but are often complicated and labour intensive. The application of artificial intelligence (AI) techniques have now been an important part of condition monitoring of the mechanical and electrical machines because of its fast computation, higher accuracy, and robustness in performance, reducing the dependence on experienced personnel with expert knowledge. This paper presents a review of applications of AI-based fault diagnosis techniques that have had demonstrated success when applied to various industrial machineries. The important literature published in the last twenty years (i.e., 2000 to 2020) have been reviewed and added. In this work, first, a brief of various AI techniques such as artificial neural networks (ANN), deep learning (DL), fuzzy logic (FL), and support vector machine (SVM) are added. The literature on AI-based diagnostics used for various industrial machines, such as induction motor, bearing, gear, and centrifugal pump, are added and discussed in detail. The observation, research gap, and new ideas have been discussed, followed by a conclusion.

Aluminum phosphide (ALP) is a pesticide agent and infrequent culprit of accidental poisoning. We present a case of severe reversible cardiomyopathy and left ventricular apical thrombus in a patient who worked as an exterminator and had ALP poisoning.

Rural women play vital function in carrying out the transformational, financial, conservational and social changes required for sustainable growth. Restriction on get right of entry to credit score, poor health care management and literacy rate are the problems they face. Women empowerment is the important thing now no longer simplest to the welfare of character individuals of the own circle of relatives and rural communities, however additionally to common economic increase of the nation. Half of the arena’s populace is represented with the aid of using ladies and till they're given the same possibilities society cannot gain increase. Government, society and non – governmental organizations (NGOs) round the arena come ahead and take crucial steps to empower ladies and supply them the same rights in monetary and non-monetary improvement. Therefore, that is the perfect time to shift from welfare mode to empowerment mode in governmental regulations designed for the development of ladies. To empower women’s continuous efforts taken with the aid of using Indian authorities and National Bank for Agricultural and Rural Development (NABARD) via microfinance raised the popular of residing of negative ladies and their family members above poverty line to a few extents. Therefore, the tasks have to recognition on the above stated problems confronted with the aid of using ladies. In this way, this paper is analyzed with self assist group's rural women empowerment and satisfaction via micro credit in Kota District. View Article DOI: 10.47856/ijaast.2021.v08i8.009

This paper proposes the right and left motor velocity based multi-objective genetic algorithm controlled navigation method for Two-Wheeled Pioneer P3-DX Robot (TWPR) in Virtual Robot Experimentation Platform (V-REP) software scenarios. The first objective function is made by taking front, left, and right ultrasonic sensors data and right motor velocity. Similarly, the second objective function is designed using front, left, and right ultrasonic sensors data and left motor velocity. Next, the sensor data are considered independent variables or inputs. The velocities of the motors are chosen as dependent variables or outputs for making multi-objective fitness functions for genetic algorithm (GA). This multi-objective GA makes a sensor-actuator control architecture and helps the TWPR to avoid the obstacles in the simulated scenarios. Further, the successful simulation test results show that the multi-objective GA provided a collision-free smooth, and shortest path for TWPR compared to the previously developed benchmark single objective GA.

In recent years, intelligent condition-based monitoring of rotary machinery systems has become a major research focus of machine fault diagnosis. In condition-based monitoring, it is challenging to form a large-scale well-annotated dataset due to the expense of data acquisition and costly annotation. The generated data have a large number of redundant features which degraded the performance of the machine learning models. To overcome this, we have utilized the advantages of minimum redundancy maximum relevance ( mRMR ) and transfer learning with a deep learning model. In this work, mRMR is combined with deep learning and deep transfer learning framework to improve the fault diagnostics performance in terms of accuracy and computational complexity. The mRMR reduces the redundant information from data and increases the deep learning performance, whereas transfer learning, reduces a large amount of data dependency for training the model. In the proposed work, two frameworks, i.e., mRMR with deep learning and mRMR with deep transfer learning, have explored and validated on CWRU and IMS rolling element bearings datasets. The analysis shows that the proposed frameworks can obtain better diagnostic accuracy compared to existing methods and can handle the data with a large number of features more quickly.

In herbal medicine, there is a substantial amount of variety of plants have been used to treat neurodegenerative disorders including Alzheimer's (AD)as well as other memory-related issues. Dementia is a neurological condition characterised by a progressive loss in emotional and cognitive abilities. Dementia is linked to a number of conditions like inadequate cerebral blood flow, poison toxicity, and other risk factors and conditions mitochondrial dysfunction, oxidative injury, and, in certain cases coexistence with other diseases like Alzheimer's disease (AD), Huntington's disease, Parkinson's syndrome (PD) and Attention Deficit Hyperactivity Disorder (ADHD).Despite the fact that there are well-established semi-synthetic medications for the treatment of AD and AD-related dementia, the majority of them have a number of side effects. As a result, conventional medicine offers a variety of plant-derived lead molecules that may be valuable in future medical studies. In this paper, we look at how ayurvedic plants are used to treat neurodegenerative disease around the world. Plants are also neuroprotective against proinflammatory cytokines including IL-6, IL-1b, TNF-a and it was reported that Antioxidant activity was increased, oxidant levels were reduced, and acetylcholinesterase activity was inhibited in the nervous system by these medicinal plants. We've highlighted the most essential ayurvedic medicinal plants as well as their biochemical effects. As a result, the effects of the above medicinals plants and their active constituents strengthened neurodegenerative conditions, indicating their therapeutic potential in ailments like Alzheimer's disease. and depression that are linked to neuroinflammation and neurotransmitter dysfunction.

Background: Saussurea lappa is a traditionally well-known plant appreciated for its biological activities and medicinal uses. Objective: In the present study, the recovery of antioxidants from Saussurea lappa was optimized using Response Surface Methodology (RSM). The efficiency of a newly-patented Infrared (IR) technology, Ired-Irrad®, was compared to that of the emerging ultrasound method (US) and the conventional solid liquid Water Bath (WB) extraction. Methods: The effects of time (t) and Temperature (T), mostly known to affect the extraction process, were tested on maximizing the Total Phenolic compounds Concentration (TPC) and the radical scavenging activity (AA). Response surface methodology was used for the optimization process. Results: A multiple response optimization of both time (t) and Temperature (T) was conducted, showing the best extraction conditions to be for WB: t= 43.86 min, T=33.79°C, for US: t= 65.47 min, T= 57.97°C and for IR: t= 42.5 min, T=34.19°C. The quantity of the optimally extracted polyphenols by WB, US and IR; as well as many of their bioactivities were compared. IR extraction gave the highest yield of TPC (15.3 mg GAE/g DM) followed by US (14.8 mg GAE/g DM) and lastly WB (13.9 mg GAE/g DM). The highest antioxidant and antiradical activities were also obtained by the IR treatment. The optimal IR extract inhibited the growth of Staphylococcus aureus and Escherichia coli up to 65 and 35%, respectively. Moreover, all Saussurea lappa extracts (WB, US and IR) inhibited up to 96% the production of Aflatoxin B1 (AFB1) by Aspergillus flavus. Conclusion: Our findings on the extraction of antioxidants from Saussurea lappa demonstrated that IR technology is an efficient novel method that can be used to extract the maximum yield of polyphenols, with the highest antioxidant, antiradical and antibacterial activities.

For much of the 20th century, smoking was regarded as a socially learned habit and as a personal choice. It is only in the past decade or so that the fundamental role of nicotine in sustaining smoking behaviour has begun to be more widely accepted. It is now recognized that cigarette smoking is primarily a manifestation of nicotine addiction and that smokers have individually characteristic preferences for their level of nicotine intake. Smokers regulate the way they puff and inhale to achieve their desired nicotine dose. The link with nicotine addiction does not imply that pharmacological factors drive smoking behaviour in a simple way and to the exclusion of other influences. Social, economic, personal, and political influences all play an important part in determining patterns of smoking prevalence and cessation. Therefore, the aim of this review was to emphasize information about the nicotine replacement therapy.

Abdominal trauma management has seen a paradigm shift over the last few decades. There is wide variation in the treatment depending on the level of healthcare facilities available. With an aim to standardise the treatment of solid organ injuries in blunt abdominal trauma, Indian Society for Trauma and Acute Care (ISTAC®) formulated consensus guidelines to benefit doctors engaged in trauma care in the country.

The novel coronavirus outbreak is a contagious disease affecting the countries around the world. The quick advancing nature of pandemic has gripped the entire community making it a public health emergency. Infection control preventive measures are necessary to prevent it from further spreading. Medical practitioners, health care workers and Dentists are at high risk of acquiring and transmission of infection. The virus transmission occurs through respiratory tract, aerosols and droplets. Clinical manifestations of virus vary from mild to severe sickness. This review article mainly emphasizes on all the information collected to date on the virus, and future recommendations for dental settings to manage the further spread of this virus.

An incisional hernia is being a universal problem and topic of discussion worldwide. There is no clear-cut guideline of abdominal wall closure after major abdominal surgeries that can effectively prevent the occurrence of incisional hernia. We found out that most of the patients presented with pain over previous surgery scar with swelling. The defect was usually larger than 2 cm. Most postoperative patients complaint of pain, seroma, and hematoma formation. There was a minimal recurrence rate after onlay mesh repair in our setup.

Intraoperative imaging has become one of the most important adjuncts in neurosurgery, especially in the surgical treatment of intra-axial tumors. Navigation and intraoperative magnetic resonance imaging have limitations, and intraoperative ultrasonography (IOUS) has emerged as a versatile and multifaceted alternative. With technological advances in ultrasound scanners and newer multifunctional probes, the potential of IOUS is increasingly being utilized in the resection of tumors. The addition of image guidance to IOUS has exponentially increased the power of this technique. Navigated ultrasonography (nUS) can now overcome many of the limitations of conventional standalone two-dimensional ultrasonography. In this pictorial essay, we outline our nUS technique (both two- and three-dimensional) for the resection of intra-axial tumors with illustrated examples highlighting the various steps and corresponding benefits of the technique.

Owing to the growing population with end stage heart failure, the use of left ventricular assist devices (LVADs) have become more widely accepted. Although survival has improved with newer generation LVADs, multiple complications including pump failure due to outflow graft obstruction have become more clinically relevant. Patients with this complication will present with heart failure symptoms due to inadequate unloading of the left ventricle by LVAD. This rare complication often requires open surgical repair in an already high-risk patient population. Alternative means to relieve the obstruction via percutaneous intervention has been described in rare cases. We present two unique cases of LVAD outflow graft obstruction which were percutaneously treated successfully. This article illustrates a potential treatment strategy for outflow graft obstruction with stenting as an alternative to open-heart surgery.

Maximizing resection is an oft-sought-after albeit challenging goal in diffuse gliomas. Microsurgical technique remains the mainstay. By virtue of their pattern of growth and spread, gliomas respect anatomical boundaries like the pia. Using subpial dissection, en bloc resections provide the most optimal surgical technique. This paper revisits this technique and describes the rationale and basic principles integrating it in the modern multimodal glioma surgery workflow. Subpial resection is a very useful and “anatomical” technique for en bloc resection of diffuse gliomas which is easy to master and execute and optimizes the extent of resection and minimizes complications effectively.

Several data-driven methods such as signal processing and machine learning exist separately to analyze non-linear and non-stationary data but their performance degrades due to insufficient information in the real-time application. In order to improve the performance, this paper proposes a novel feature extraction method using fusion of hand-crafted (low-level) features and high-level features, followed by feature extraction/selection on fused features. Local energy-based hand-crafted features have been derived from empirical mode decomposition, and high-level features have been extracted from the deep neural network. A method is also proposed for reduction of massive data points in the samples. The proposed scheme has studied the effect of variation in the number of extracted/selected features. The effectiveness of the proposed scheme is validated through three case studies: a) on acoustic dataset collected from the reciprocating type air compressor, b) on vibration dataset collected from deep groove ball bearing, and c) on steel plate faults dataset. The classification accuracy on acoustic dataset are obtained as high as 100.0%, 99.78%, and 99.78% using the random forest, linear support vector machine, and radial basis function support vector machine, respectively, with 5-fold cross-validation. Similarly, on vibration dataset obtained accuracies are 100.0%. The proposed scheme has been compared with ten conventional methods on five-fold cross-validation. These experimental results show considerable improvement in the prediction performance of machine conditions using the proposed scheme.

Cancer is one of the prominent global causes of death and the foremost worldwide health concern. Despite unprecedented progress in cancer chemoprevention, a vast number of cancers, however, remain an undefeatable challenge for treatment modalities. Immense therapeutic activities of puerarin contribute to its use in various health disorders. In this review, we explored the potential molecular mechanisms and targets of puerarin, proving its potential as a novel anticancer agent, for future cancer therapy and chemoprevention. Several mechanisms account for anticancer activity of puerarin which includes downregulation of NF-kB signalling pathway, mTOR signalling pathway, PI3K and BCl-2 proteins and upregulation of miR-16, caspase proteins, c- Jun N terminal kinase and extracellular signal-regulated kinase 1/2. These alterations result in inhibition of cancer cell proliferation and/or induction of apoptosis. Understanding the molecular mechanisms involved in chemotherapy and chemoprevention could aid in the more pronounced exploration of puerarin in effective cancer treatment.

Background: Laparoscopic inguinal hernia repair is a common surgical procedure performed worldwide. In this era of rapidly advancing surgical technology, surgeons are often keen to modify the technique of laparoscopic surgery by reducing the number and size of incisions. The aim of this observational study was to present the results of a single incision laparoscopic surgical (SILS) approach for trans- abdominal preperitoneal mesh hernioplasty (SITAPP) in cases of bilateral inguinal hernia. Methods: Forty eight patients with bilateral inguinal hernia who underwent TAPP were prospectively evaluated. Data regarding patient demographics, type of hernia, operating time, complications and duration of hospital stay were prospectively collected. Single incision TAPP (SITAPP) was performed using conventional instruments and surgical technique similar to standard 3 port TAPP was used, except that it was conducted through a single umbilical port. Results: All patients were male and the mean age was 50 years (range 30 - 68 years). The mean duration of surgery was 155.83 minutes (range 120 - 310 minutes). The procedures were completed successfully in all the patients without requiring conversion to the traditional laparoscopic surgery or use of additional ports. There was no evidence of early recurrence after a follow up period of 42 days. Conclusion: SITAPP for bilateral hernia is feasible and seems to be safe in experienced hands. However, studies with larger sample size with comparative analysis are required to establish long term clinical outcomes and recurrence rates.

Evidence-based recommendations for clinical practice are intended to help health care providers and patients make decisions, minimize inappropriate practice variation, promote effective resource use, improve clinical outcomes, and direct future research. The Society for Cardiovascular Angiography and Interventions (SCAI) has been engaged in the creation and dissemination of clinical guidance documents since the 1990s. These documents are a cornerstone of the society's education, advocacy, and quality improvement initiatives. The publications committee is charged with oversight of SCAI's clinical documents program and has created this manual of standard operating procedures to ensure consistency, methodological rigor, and transparency in the development and endorsement of the society's documents. The manual is intended for use by the publications committee, document writing groups, external collaborators, SCAI representatives, peer reviewers, and anyone seeking information about the SCAI documents program.

INTRODUCTION The NCCN recommends either PCV (Procarbazine, CCNU and vincristine) or Temozolomide (TMZ) as adjuvant therapy in high-risk grade 2 & grade 3 gliomas. In this ongoing study we are comparing PCV with TMZ as adjuvant therapy in this setting. METHODS This is a randomised phase 3 study that includes patients with high risk (as per RTOG) grade 2 gliomas and grade 3 gliomas after surgery. Patient are randomly assigned in 1: 2 to receive either adjuvant PCV or TMZ after adjuvant RT. The primary end-point is progression-free survival & key secondary end points are overall survival, toxicity and quality of life. The current analysis focuses on the compliance and adverse events seen in patients enrolled till 30th April 2020. RESULTS 46 patients were enrolled, with 30 patients in TMZ arm. The median age of patients was 37 years (range 23-64). The ECOG PS was 1 in 45 (97.8%) patients and 2 in 1(2.2%) patient at enrolment. The number of patients who have completed all planned cycles of chemotherapy in the PCV arm is 62.5% (10, n=16) as compared to 90% (27, n=30) in the TMZ arm (P=0.047). The incidence of grade 3 or higher adverse events is 68.8% (n=11) in the PCV arm and 16.7% (n=5) in the TMZ arm (P=0.001). The most common grade 3 or higher toxicities noted are lymphopenia in 50% (n=8), neutropenia in 37.5% (n=6), and thrombocytopenia in 25% (n=4) in the PCV arm; while the corresponding numbers in the TMZ arm are 13.3% (n=4), 3.3% (n=1) and 10% (n=3) respectively. CONCLUSION In the current study the chemotherapy completion rates are higher with TMZ and it is associated with lower grade 3-4 events, whether this will lead to an improvement in outcomes remains to be seen.

Background and Objectives There are reports of outcomes of elective major cancer surgery during the COVID‐19 pandemic. We evaluated if reinforcement of hand hygiene, universal masking, and distancing as a part of pandemic precautions led to a decrease in the incidence of surgical site infections (SSIs) in major oncologic resections. Methods Propensity score matching using the nearest neighbor algorithm was performed on 3123 patients over seven covariates (age, comorbidities, surgery duration, prior treatment, disease stage, reconstruction, and surgical wound type) yielding 2614 matched (pre‐COVID 1612 and COVID 1002) patients. Conditional logistic regression was used to identify if SSI incidence was lower amongst patients operated during the pandemic. Results There was a 4.2% (p = 0.006) decrease in SSI in patients operated during the pandemic. On multivariate regression, surgery during the COVID‐19 period (odds ratio [OR] = 0.77; 95% confidence interval [CI] = 0.61–0.98; p = 0.03), prior chemoradiation (OR = 2.46; CI = 1.45–4.17; p 4 h (OR = 2.17; 95%CI = 1.55–3.05; p

Coronary air embolism is a rare iatrogenic complication during invasive coronary angiography or angioplasty that can cause acute chest pain, hypotension, ST-segment elevation myocardial infarction, and even death. We present a case of left anterior descending coronary artery air embolization in a 58-year-old heart transplant patient that occurred during cardiac allograft vasculopathy surveillance angiography. The patient was managed successfully with rapid coronary injections of heparinized saline, catheter disengagement to increase coronary blood flow, and supplementation of 100% oxygen to dissolve the coronary air embolus. This case highlights this rare complication of coronary angiography, importance of prompt recognition of the pathology and subsequent management.

Olecranon bursa endoscopy (bursoscopy) is a minimally invasive technique for resection of olecranon bursitis and spurs. The principal advantages are minimal operative site morbidity, excellent visualization secondary to endoscopic magnification, and early return to function. Dry endoscopy is performed with the hooded endoscope to keep the operating space patent, allowing illumination while also eliminating potential issues with wet endoscopy like postoperative soft tissue edema, sinus formation, and swelling.

Accumulation of anomalous tissue in the head formed the Brain Tumor. Brain tumor is basically caused by the uncommon growth of the anomalous cells in the brain. Since the skull encloses the very rigid brain. Any unspecified growth inside the restricted space where the cells multiply abruptly and ceaselessly can create the major problem. After the 20th century, the number of the patient who have the brain tumor is increasing day by day for the aging population is a worldwide health problem. Basically Malformed mass called tumor can be identified into two types cancerous (malignant) or noncancerous (benign). The main objective of this research is to create the technique that reliably identifies the existence of a tumor that includes all cancerous tissues. Fish schooling Genetic algorithm is used to recognize a presence of cancerous part called tumor area from a soft tissue called brain MRI images and to predict that detected area whether it is a tumor or not. The proposed module consists of the steps such as Brain MRI dataset Pre-processing of MRI image, remove noise through image Enhancement, stripping the skull part, fish school search algorithm based indication are used in the research. According to the results acquire from the performance of Fish School Search Algorithm in detection of tumor achieves the better performance in terms of comparing the quality parameters such as accuracy, efficiency with the previous method used.

Pre-operative optimization of cardiovascular conditions in patients awaiting renal transplantation significantly improves post-transplantation cardiac complications. We describe a case of symptomatic coronary fistula treated with percutaneous coil embolization in a young adult awaiting renal transplantation. (Level of Difficulty: Advanced.), Graphical abstract

Background: The availability of safe, clinically useful, and cost-effective bone allografts have led to modifications in surgical therapy, as well as a rise in demand for bone allografts grafts for use in plastic surgery reconstruction. They are an appealing alternative to bone autograft because their supply is less limited, they allow structural restoration of the skeleton, and their surfaces promote bone formation. Case Series: We provide a case series of 13 patients who were treated with freeze-dried bone allografts. The FDA and the Bone Banks both advised that all grafts meet certain parameters. The objective evaluation of graft volume persistence was achieved using radiography, whereas the subjective estimation of graft volume was obtained through patient response throughout a one-year period of follow-up. Objective of this study was to establish the clinical use of bone allografts in various reconstructive surgeries and compare its utility with bone autografts. Conclusion: Bone allografts can be used in any type of bone surgery, from minor defects to major bone loss following tumour resection. Without donor-site morbidity, freeze-dried allograft bone is a safe and equal alternative to bone autograft.

Achilles tendon rupture is a well‐documented adverse effect of Fluoroquinolones; however, herein we present a case of complete iliopsoas and Achilles, and partial semimembranosus tendon rupture secondary to Levofloxacin.

Certified coffee production is an opportunity for the cultivator to differ his product. In any case, the quantity of certified producers is still comparatively very less. So as to contribute to the spread of accreditation among ranchers, the purpose of this research work is to distinguish the components that decide its reception, based on a sample of certified and non-certified cultivators from Karnataka and Kerala in India. Quantitative information was dissected through logistic regression. Results demonstrated that three factors were critical in clarifying the accreditation reception: membership in the organization; source of income from different yields as well as the size of landholding. These outcomes extend the current information about coffee certifications and can manage activities to build the number of certified producers.

The emergence of deep learning has impacted numerous machine learning based applications and research. The reason for its success lies in two main advantages: 1) it provides the ability to learn very complex non-linear relationships between features and 2) it allows one to leverage information from unlabeled data that does not belong to the problem being handled. This paper presents a transfer learning procedure for cancer classification, which uses feature selection and normalization techniques in conjunction with s sparse auto-encoders on gene expression data. While classifying any two tumor types, data of other tumor types were used in unsupervised manner to improve the feature representation. The performance of our algorithm was tested on 36 two-class benchmark datasets from the GEMLeR repository. On performing statistical tests, it is clearly ascertained that our algorithm statistically outperforms several generally used cancer classification approaches. The deep learning based molecular disease classification can be used to guide decisions made on the diagnosis and treatment of diseases, and therefore may have important applications in precision medicine.

Risk-averse behavior has been reported among physicians and facilities treating cardiogenic shock in states with public reporting. Our objective was to evaluate if public reporting leads to a lower use of mechanical circulatory support in cardiogenic shock. We conducted a retrospective study with the use of the National Inpatient Sample from 2005 to 2011. Hospitalizations of patients ≥18 years old with a diagnosis of cardiogenic shock were included. A regional comparison was performed to identify differences between reporting and nonreporting states. The main outcome of interest was the use of mechanical circulatory support. A total of 13043 hospitalizations for cardiogenic shock were identified of which 9664 occurred in reporting and 3379 in nonreporting states (age 69.9 ± 0.4 years, 56.8% men). Use of mechanical circulatory support was 32.8% in this high-risk population. Odds of receiving mechanical circulatory support were lower (OR 0.50; 95% CI 0.43–0.57; p<0.01) and in-hospital mortality higher (OR 1.19; 95% CI 1.06–1.34; p<0.01) in reporting states. Use of mechanical circulatory support was also lower in the subgroup of patients with acute myocardial infarction and cardiogenic shock in reporting states (OR 0.61; 95% CI 0.51–0.72; p<0.01). In conclusion, patients with cardiogenic shock in reporting states are less likely to receive mechanical circulatory support than patients in nonreporting states.

Purpose The purpose of this study was to evaluate the relative utility and benefits of free-hand 2-dimensional intraoperative ultrasound (FUS) and navigated 3-dimensional intraoperative ultrasound (NUS) as ultrasound-guided biopsy (USGB) techniques for supratentorial lesions. Methods All patients who underwent USGB for suspected supratentorial tumours from January 2008 to December 2017 were retrospectively analyzed. The charts and electronic medical records of these patients were studied. Demographic, surgical, and pathological variables were collected and analyzed. The study group consisted of patients who underwent either FUS or NUS for biopsy. Results A total of 125 patients (112 adults and 13 children) underwent USGB during the study period (89 FUS and 36 NUS). NUS was used more often for deep-seated lesions (58% vs. 18% for FUS, P

In this paper, we describe a theoretical design for the realization of a high capacity (bandwidth) atomic quantum memory based on wavelength division multiplexing and electromagnetically induced tr...

An increase in the share of distributed generation (DG) in the global generation system is a direct indication of the development of available technologies. The extraction of natural energy resources and their use as DG has several advantages, such as the reduction in line losses, improved voltage profile and reliability, etc., but the incorrect installation of these power plants can also have some negative effects. The innovation in technology has motivated to extract the maximum benefit of natural energy resources. Due to this, the capacity and location of these energy resources should be carefully identified. The optimal placement of a distributed generation power plant, in the existing network, is analyzed in this article. The proposed methodology is inspired by the human immune system. In this methodology clonal selection principle of immune system is combined with particle swarm optimization. For checking the validity of the proposed method two test systems, IEEE 33-node radial distribution system and IEEE 14-node loop distribution system, are considered. Results show the validity of the proposed algorithm in radial as well as in loop distribution system.

Central neurocytomas are benign tumors accounting for0.5% of all intracranial tumors. They are usually intraventricular, the most common site being the lateral ventricles, and are associated with good prognosis if they are completely resected surgically.We report the case of a middle-aged woman who was evaluated for recent-onset headache and for whom magnetic resonance imaging of the brain was suggestive of a solid cystic intraventricular mass spanning all the ventricles. The patient underwent subtotal excision of the mass, with intraoperative neuromonitoring. The result of Histopathologic examination was suggestive of atypical neurocytoma. The patient had complete neurologic recovery in spite of immediate postoperative deficits.Gross total resection should be the goal in all patients with central neurocytoma, but it may be limited because of proximity of the tumor to eloquent areas, especially in large tumors. Intraoperative neuromonitoring plays a pivotal role in maximal safe resection of such large tumors. Tetraventricular atypical central neurocytoma is a very rare entity; and this case could be, to the best of our knowledge, only the second reported case.

Recent results in coupled or temporal graphical models offer schemes for estimating the relationship structure between features when the data come from related (but distinct) longitudinal sources. A novel application of these ideas is for analyzing group-level differences, i.e., in identifying if trends of estimated objects (e.g., covariance or precision matrices) are different across disparate conditions (e.g., gender or disease). Often, poor effect sizes make detecting the differential signal over the full set of features difficult: for example, dependencies between only a subset of features may manifest differently across groups. In this work, we first give a parametric model for estimating trends in the space of SPD matrices as a function of one or more covariates. We then generalize scan statistics to graph structures, to search over distinct subsets of features (graph partitions) whose temporal dependency structure may show statistically significant group-wise differences. We theoretically analyze the Family Wise Error Rate (FWER) and bounds on Type 1 and Type 2 error. Evaluating on US census data, we identify groups of states with cultural and legal overlap related to baby name trends and drug usage. On a cohort of individuals with risk factors for Alzheimer’s disease (but otherwise cognitively healthy), we find scientifically interesting group differences where the default analysis, i.e., models estimated on the full graph, do not survive reasonable significance thresholds.

Quantum communication with terahertz (THz) frequency signals has many advantages like reduced attenuation and scintillation effects in certain atmospheric conditions along with very high level of data security. In this work, we propose a scheme to realize Quantum Memory (QM) for efficient storage of terahertz (THz) frequency signals using Electromagnetically Induced Transparency (EIT) in an ultracold atomic medium of 87Rb Rydberg atoms prepared in a Two Dimensional Magneto Optical Trap (2D-MOT). The uniqueness of our scheme lies in the choice of the energy levels involved in the EIT process, all three of which have been chosen to be the Rydberg levels (enabling signal beam to be in THz) in a lambda type arrangement. This first of its kind proposal reveals that atomic media are a potential candidate for devising QMs which can store THz frequency signals. We have estimated that the Optical Depth (OD) in our scheme can reach a very high value of 690, very high maximum obtainable storage efficiency (η) of ∼99%, the group velocity ( v g ) can be as low as 5.07 × 103 m/s, and the Delay Bandwidth Product (DBP) can be as high as 9.5. All of these estimates emphasize the feasibility of our scheme as a QM device for efficient storage of THz pulses.

We introduce a unified framework to jointly model images, text, and human attention traces. Our work is built on top of the recent Localized Narratives annotation frame-work [31], where each word of a given caption is paired with a mouse trace segment. We propose two novel tasks: (1) predict a trace given an image and caption (i.e., visual grounding), and (2) predict a caption and a trace given only an image. Learning the grounding of each word is challenging, due to noise in the human-provided traces and the presence of words that cannot be meaningfully visually grounded. We present a novel model architecture that is jointly trained on dual tasks (controlled trace generation and controlled caption generation). To evaluate the quality of the generated traces, we propose a local bipartite matching (LBM) distance metric which allows the comparison of two traces of different lengths. Extensive experiments show our model is robust to the imperfect training data and outperforms the baselines by a clear margin. More-over, we demonstrate that our model pre-trained on the pro-posed tasks can be also beneficial to the downstream task of COCO’s guided image captioning. Our code1 and project page2 are publicly available.

AIMS The current opioid crisis in the USA is a formidable challenge for the healthcare system, and the general population. Our objective is to characterize the burden of opioid-related disorders in an inpatient setting in the USA for the years 2016, 2017 and 2018 using the National Inpatient Sample (NIS). METHODS A cross-sectional analysis of the NIS was performed to identify and analyse hospitalizations with an opioid-related diagnosis in 2016, 2017 and 2018. Descriptive statistics and regression models were utilized to define the demographics of the population of interest and measure the outcomes. RESULTS We identified 962 900 discharges with opioid-related diagnosis in 2016, 982 710 in 2017 and 942 110 in 2018. The majority were age

The unprecedented penetration of distributed energy resources (DERs) such as wind power generations (WPGs) poses tremendous challenges for for the planning and maintenance of power systems due to their intermittent and uncertain nature. This paper mainly focuses on comparing basic probabilistic load flow (PLF) techniques when WPGs are integrated into the existing power grid. Considering loads and WPGs as random inputs, the performance of the cumulant method (CM) and point estimation method (PEM) are analyzed with respect to Monte-Carlo method for higher precision and less computational time. Case-studies are carried out on sample 10-bus and SR 72-bus equivalent systems. Simulation results demonstrated that $2n+1$ PEM provides the best performance when dealing with high level of uncertainty associated with input variables.

INTRODUCTION Intraoperative ultrasound (iUS) is a promising tool for glioma surgery. Navigated 3-D (n3D) iUS has many benefits over standard 2-D iUS. METHODS This was a retrospective comparative cohort study using propensity score matching (PSM). 500 consecutive histologically confirmed gliomas were divided into 2 cohorts – 2DiUS - Cohort A; and n3DiUS -Cohort B. PSM was used to account for known confounders (250 in each group; 1:1 matching). Gross total resection rates (based on iUS findings as well as postoperative MR) and perioperative morbidity were analyzed across the groups as were factors influencing these outcomes (using univariate as well as multivariate regression models). RESULTS Overall, the majority of the patients were adults (94%), males (71%) with hemispheric tumors (96%). 35% had tumors close to eloquent regions and 23% had received some prior treatment. The majority were high-grade gliomas (85%). 2D iUS was employed mainly for localization (80%) whereas n3D was used predominantly for resection control (84%) [p < 0.001]. GTR rate was higher in the n3D cohort (55.2% vs 38.4% in 2D; p = 0.001). The odds of having a complete resection in the n3D cohort was twice that of the 2D. Prior treatment, hemispheric location, and use of fluorescence were also significantly associated with higher GTR rates on univariate analysis. On multivariate analysis, all of these remained significant. There was no difference in the morbidity rates in the two cohorts. N3D iUS had a higher specificity and positive likelihood ratio in detecting tumor residue. CONCLUSION For hemispheric gliomas undergoing resective surgery, the use of navigated 3D ultrasound improves GTR rates, with no added morbidity. It is more likely to be used for resection control mode than is 2DUS and this is probably because n3DUS is more specific and likely to pick up tumor residues contributing to its better accuracy.

Achilles tendon rupture is a well-documented adverse effect of Fluoroquinolones; however, herein we present a case of complete iliopsoas and Achilles, and partial semimembranosus tendon rupture secondary to Levofloxacin.