Graphene as Infrared Light Sensor Material

The infrared (IR) photoresponse of graphene synthesized by an atmospheric chemical vapor deposition (CVD) system using a mixture of hydrogen and methane gases was studied. The IR sensor devices were fabricated using graphene films transferred onto a SiO2 substrate by a lift-off process. The quality of graphene was investigated with Raman spectroscopy and optical microscopy. The photoresponse was recorded under the illumination of IR light of wavelength 850 nm and intensity of around 0.216 mW/cm^2. The effects of temperature and hydrogenation on photoconductivity were also studied. It was found that the transient response and recovery times decreased with the temperature increase. The hydrogenation effect also caused a significant decrease in the photoresponse of the device. Although the net change in the photoresponse for IR light was lower at low illumination intensity levels, the transient responses were observed around 100 times faster than the recently reported CNT-based IR sensors.Comment: 8 pages, 8 pictures, and 1 table

Visual Inspection Algorithms for Printed Circuit Board Patterns A SURVEY

The importance of the inspection process has been magnified by the requirements of the modern manufacturing environment. In electronics mass-production manufacturing facilities, an attempt is often made to achieve 100 % quality assurance of all parts, subassemblies, and finished goods. A variety of approaches for automated visual inspection of printed circuits have been reported over the last two decades. In this survey, algorithms and techniques for the automated inspection of printed circuit boards are examined. A classification tree for these algorithms is presented and the algorithms are grouped according to this classification. This survey concentrates mainly on image analysis and fault detection strategies, these also include the state-of-the-art techniques. Finally, limitations of current inspection systems are summarized

Pharmaceutico Analytical Study of Mukta Shukti Bhasma

Background: Mukta Shukti is an aquamarine calcium carbonate compound. Mukta Shukti Bhasma is a classical ethical economical medicament, effective in general practice, pharmaceutical processing as per texts with systematic observation and technological updating is carried out in the present work. Objectives: To prepare Mukta Shukti Bhasma by different Pharmaceutical processes and carry out the analytical study. Materials and Methods: Grahya Ashodhita Mukta Shukti was subjected to Shodhana by Kanji Swedana for 3 hours and then divided into two parts. The first part of Shodhita Mukata Shukti was incinerated totally and after 1st Puta it was divided into two portions, first portion was subjected to Jala Bhavana and incinerated. The second portion was subjected to Kumari Swarasa Bhavana and incinerated. The second part of Shodhita Mukata Shukti was incinerated in Kumari Samputa and subjected to Kumari Swarasa Bhavana and incinerated until they attain Bhasma Siddhi Lakshanas and later all the three samples were subjected to analytical studies. Results: Mukta Shukti Bhasma by Jala Bhavana method, Kumari Bhavana method, and Kumari Samputa method requires 7, 6 and 3 Gajaputas respectively with an average of 324 cow dungs in each and at 793°C temperature. Conclusion: Kumari Bhavita Marana to Mukta Shukti leads to calcite form and Jala Bhavita Marana leads to calcium oxide hydrate form. Chemically Mukta Shukti Bhasma may be in both calcite and calcium oxide hydrate form, and XRD is a method in Standardization of Mukta Shukti Bhasma

Prospective study on vacuum assisted closure therapy in treatment of soft tissue injuries associated with Gustilo Anderson compound Grade IIIB fractures

BACK GROUND: The Primary objective of this prospective study is to study the rate of infection, number of days required for formation of healthy granulation tissue, healing of soft tissue injury and number of days of hospital stay and cost effectiveness associated with Gustilo Anderson compound grade IIIb fractures treated by Vacuum Assisted closure therapy. METHODS: Seventeen patients with Type IIIb open fractures were included in this study..All these patients had undergone wound debridement and fracture fixation. This wss followed by application of Vacuum Assisted Closure (VAC) The infection rate analysed by clinical findings and investigations. RESULTS: The infection rate was low when compared to literature study of conventional dressings. The primary wound coverage can be done earlier wound healing was also faster in patients. CONCLUSION: This is a simple and low cost method for treating soft tissue injury associated with severe open fractures. It can be done even in peripheral hospitals with low resources

Biotic responses to climate extremes in terrestrial ecosystems

Anthropogenic climate change is increasing the incidence of climate extremes. Consequences of climate extremes on biodiversity can be highly detrimental, yet few studies also suggest beneficial effects of climate extremes on certain organisms. To obtain a general understanding of ecological responses to climate extremes, we present a review of how 16 major taxonomic/functional groups (including microorganisms, plants, invertebrates, and vertebrates) respond during extreme drought, precipitation, and temperature.Most taxonomic/functional groups respond negatively to extreme events, whereas groups such as mosses, legumes, trees, and vertebrate predators respond most negatively to climate extremes. We further highlight that ecological recovery after climate extremes is challenging to predict purely based on ecological responses during or immediately after climate extremes. By accounting for the characteristics of the recovering species, resource availability, and species interactions with neighboring competitors or facilitators, mutualists, and enemies, we outline a conceptual framework to better predict ecological recovery in terrestrial ecosystems

Spiral Evolution in a Confined Geometry

Supported nanoscale lead crystallites with a step emerging from a non-centered screw dislocation on the circular top facet were prepared by rapid cooling from just above the melting temperature. STM observations of the top facet show a nonuniform rotation rate and shape of the spiral step as the crystallite relaxes. These features can be accurately modeled using curvature driven dynamics, as in classical models of spiral growth, with boundary conditions fixing the dislocation core and regions of the step lying along the outer facet edge.Comment: 4 pages, 3 figures, to be published in Physical Review Letter

Resilience of rhizosphere microbial predators and their prey communities after an extreme heat event

Climate change is known to disrupt above‐ground food chains when the various trophic layers respond differently to warming. However, little is known about below‐ground food chains involving microbial preys and their predators. Here, we study how climate warming‐induced heat shocks influence resistance (change immediately after a disturbance) and resilience (ability to recover back to pre‐disturbance levels) in rhizosphere microbial communities. We used three species of rhizosphere protists as microbial predators and six different rhizosphere bacterial communities as their prey. Protist species and bacterial communities were extracted from Centaurea stoebe—a range‐expanding plant species in the Northern Europe. We then examined the temporal dynamics of protists and bacterial communities after an extreme heat event for several generations with sufficient recovery periods. We hypothesized that bacterial community resistance and resilience after the extreme heat event would be higher particularly when extreme heat effects would negatively affect their predators. Our results show that prey community biomass was strongly reduced after the extreme heat event and persisted with lower biomass throughout the recovery period. Opposite to what was expected, predators showed negligible changes in their active density after the same heat event. However, abundances of the three predators varied markedly in their temporal dynamics independent of the extreme heat event. Extreme heat event further increased the inactive density of predators, whereas one of the predators showed a decline in its body size owing to extreme heat event. Bacterial community resistance and resilience after the extreme heat event were independent of predator presence, although species‐specific effects of predators on bacterial community resilience were different in the last week of recovery. Predator resilience (based on active predator density) also varied among the three predators but converged over time. Our results highlight that extreme heat events can be more detrimental to microbial prey communities than microbial predators when microbial predators can exhibit thermal acclimation (e.g. change in body size or become inactive) to overcome heat stress. Such thermal acclimation may promote predator resilience after extreme heat events

Gravitational Collapse of Inhomogeneous Dust in (2+1) Dimensions

We examine the gravitational collapse of spherically symmetric inhomogeneous dust in (2+1) dimensions, with cosmological constant. We obtain the analytical expressions for the interior metric. We match the solution to a vacuum exterior. We discuss the nature of the singularity formed by analyzing the outgoing radial null geodesics. We examine the formation of trapped surfaces during the collapse.Comment: Accepted for publication in CQ

Machine Learning Based Analytics for the Significance of Gait Analysis in Monitoring and Managing Lower Extremity Injuries

This study explored the potential of gait analysis as a tool for assessing post-injury complications, e.g., infection, malunion, or hardware irritation, in patients with lower extremity fractures. The research focused on the proficiency of supervised machine learning models predicting complications using consecutive gait datasets. We identified patients with lower extremity fractures at an academic center. Patients underwent gait analysis with a chest-mounted IMU device. Using software, raw gait data was preprocessed, emphasizing 12 essential gait variables. Machine learning models including XGBoost, Logistic Regression, SVM, LightGBM, and Random Forest were trained, tested, and evaluated. Attention was given to class imbalance, addressed using SMOTE. We introduced a methodology to compute the Rate of Change (ROC) for gait variables, independent of the time difference between gait analyses. XGBoost was the optimal model both before and after applying SMOTE. Prior to SMOTE, the model achieved an average test AUC of 0.90 (95% CI: [0.79, 1.00]) and test accuracy of 86% (95% CI: [75%, 97%]). Feature importance analysis attributed importance to the duration between injury and gait analysis. Data patterns showed early physiological compensations, followed by stabilization phases, emphasizing prompt gait analysis. This study underscores the potential of machine learning, particularly XGBoost, in gait analysis for orthopedic care. Predicting post-injury complications, early gait assessment becomes vital, revealing intervention points. The findings support a shift in orthopedics towards a data-informed approach, enhancing patient outcomes.Comment: 13 pages, 6 figure