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Controlling energy transfer through vibronic resonance is an interesting possibility. Exact treatment of non-adiabatic vibronic coupling is necessary to fully capture its role in driving energy transfer. However, the exact treatment of vibrations in extended systems is expensive, sometimes requiring oversimplifying approximations to reduce vibrational dimensionality, and do not provide physical insights into which specific vibrational motions promote energy transfer. In this communication, we derive effective normal modes for understanding vibronically enhanced energy transfer in excitonically coupled aggregates. We show that the dynamics of the overall high-dimensional vibronic Hamiltonian can be better understood through one-dimensional Hamiltonians separable along these effective modes. We demonstrate this approach on a trimer toy model to analyze the role of an intermediate “trap” site in mediating energy transfer between electronically uncoupled sites. Bringing uncoupled sites into vibronic resonance converts the “trap” into a “shuttle” for energy transfer. By deconvolving the dynamics along the aggregate normal modes, our approach identifies the specific vibrational motions, which maximally promote energy transfer, against spectator modes, which do not participate in vibronic mixing.

We recently proposed effective normal modes for excitonically coupled aggregates that exactly transform the energy transfer Hamiltonian into a sum of one-dimensional Hamiltonians along the effective normal modes. Identifying physically meaningful vibrational motions that maximally promote vibronic mixing suggested an interesting possibility of leveraging vibrational-electronic resonance for mediating selective energy transfer. Here, we expand on the effective mode approach, elucidating its iterative nature for successively larger aggregates, and extend the idea of mediated energy transfer to larger aggregates. We show that energy transfer between electronically uncoupled but vibronically resonant donor–acceptor sites does not depend on the intermediate site energy or the number of intermediate sites. The intermediate sites simply mediate electronic coupling such that vibronic coupling along specific promoter modes leads to direct donor–acceptor energy transfer, bypassing any intermediate uphill energy transfer steps. We show that the interplay between the electronic Hamiltonian and the effective mode transformation partitions the linear vibronic coupling along specific promoter modes to dictate the selectivity of mediated energy transfer with a vital role of interference between vibronic couplings and multi-particle basis states. Our results suggest a general design principle for enhancing energy transfer through synergistic effects of vibronic resonance and weak mediated electronic coupling, where both effects individually do not promote efficient energy transfer. The effective mode approach proposed here paves a facile route toward four-wavemixing spectroscopy simulations of larger aggregates without severely approximating resonant vibronic coupling.

The secured authentication in mobile devices and individual consumer products based on iris patterns is a vital challenge. An adversary may deceive the IR system through artifacts such as printed iris, synthetic eyeballs, textured contact lenses, etc. This paper introduces an approach to discriminate between the real and forged iris, through the pooling of multi-scale BSIF and Fine-tuned DenseNet features extracted from raw and normalized iris. The paper also validates the generalizability of the proposed approach across several attack variants, iris sensors, and datasets. Besides, the experiments performed on the publicly available LivDet-2017 datasets endorse the efficacy of the proposed method.

Forgery of iris patterns to obfuscate an iris recognition system has been a major obstacle in the widescale deployment of iris biometrics. In general, this is termed as an iris presentation attack on the system, which has now become a key challenge in mobile devices as well. The iris scanner in mobile devices is not intelligent to discriminate between real iris patterns and presentation attacks. Therefore, a presentation attack detection mechanism needs to be deployed along with the scanner. This paper proposes a learning-based PAD method to identify the attack patterns by observing their deviation from the real iris. There are two feature extraction methods employed to constitute features individually, from the raw and normalized iris images. Both types of features are combined through feature-level fusion (or concatenation) and an SVM classifier is incorporated to learn the feature representation from those features. The proposed method is evaluated across various attacks, iris scanners, and datasets using the well-known LivDet-2017 dataset to ensure the efficiency and robustness of the approach.

One of the most challenging aspects of crop protection will always be flying, crawling, and chomping insects. With time, insects become susceptible to some insecticides, and hence, the right solutions (newly available insecticides) should reach the farmers at the right time. In this view, the study is aimed to provide a lightweight Artificial Intelligence (AI) driven system (can load in smartphone), which helps the farmer to identify, classify in real-time to control the target insects on chosen crops (soybean). The dataset (3809 images) was developed under MoU between IIIT-Naya Raipur (C.G.) and Indira Gandhi Krishi Vishwavidyalaya, Raipur, which consists of Eocanthecona Bug, Tobacco Caterpillar, Red Hairy Caterpillar, and Larva Spodoptera. The VGG16 and GoogLeNet deep learning models have been developed with the dataset and found decent performance as with VGG16 (validation accuracy: 97.78% and validation loss: 0.0852) and GoogLeNet (validation accuracy: 99.03% and validation loss: 69.5098). Finally, an Android-based app has been developed to facilitate real-time working.

Crop diseases are a significant danger to food security, yet their quick identification remains difficult and sometimes, unachievable in various regions because of the absence of necessary infrastructure. Distinguishing a malady effectively when it initially shows up is a critical advance for constructive disease management. Existing methods to identify diseases include local plant clinics, agricultural organizations and institutions and online platforms, which prove to be quite tedious and time-consuming. New techniques have been emerging in the domain of leaf-based image detection which have produced outstanding outcomes through machine learning algorithms. In any image processing machine learning model, the feature extraction methods used can adversely affect the overall performance of the model. So, this project aims at comparing different feature extraction techniques using the SVM classifier.

In the past few years, some fusion-based approaches have been proposed to constitute discriminatory features for iris liveness detection. However, several methods exist in the literature for iris feature extraction and, thus, identifying an optimal composite of such features is still a vital challenge. This article also proposes a score-level fusion of two distinct domain-specific features, i.e., multiple binarized statistical image feature (BSIF) and DenseNet-based features. However, instead of randomly scrutinizing such features, statistical tests are executed on six predominant iris features to identify the optimal feature set to combine. Particularly, this work emphasizes textured-lens-based presentation attacks and aims to identify the type of contact lenses within the iris samples. The experimental analysis depicts that the domain-specific features substantially outperform the generic features while discriminating live iris from the artifacts. Furthermore, the proposed fusion-based approach is assessed on three iris datasets and the outcomes are compared with various state of the arts using three validation protocols in terms of equal error rate (EER). The comparative analysis perceived that the proposed method obtains a significant performance gain over the existing approaches and offers an improved benchmark for both, iris liveness detection and contact lens identification.

BackgroundHigh-grade gliomas likely remodel the metabolic machinery to meet the increased demands for amino acids and nucleotides during rapid cell proliferation. Glycine, a non-essential amino acid and intermediate of nucleotide biosynthesis, may increase with proliferation. Non-invasive measurement of glycine by magnetic resonance spectroscopy (MRS) was evaluated as an imaging biomarker for assessment of tumor aggressiveness.MethodsWe measured glycine, 2-hydroxyglutarate (2HG), and other tumor-related metabolites in 35 glioma patients using an MRS sequence tailored for co-detection of glycine and 2HG in gadolinium-enhancing and non-enhancing tumor regions on 3T MRI. Glycine and 2HG concentrations as measured by MRS were correlated with tumor cell proliferation (MIB-1 labeling index), expression of mitochondrial serine hydroxymethyltransferase (SHMT2), and glycine decarboxylase (GLDC) enzymes, and patient overall survival.ResultsElevated glycine was strongly associated with presence of gadolinium enhancement, indicating more rapidly proliferative disease. Glycine concentration was positively correlated with MIB-1, and levels higher than 2.5 mM showed significant association with shorter patient survival, irrespective of isocitrate dehydrogenase status. Concentration of 2HG did not correlate with MIB-1 index. A high glycine/2HG concentration ratio, >2.5, was strongly associated with shorter survival (P ConclusionsThe data suggest that aggressive gliomas reprogram glycine-mediated one-carbon metabolism to meet the biosynthetic demands for rapid cell proliferation. MRS evaluation of glycine provides a non-invasive metabolic imaging biomarker that is predictive of tumor progression and clinical outcome.Key Points1. Glycine and 2-hydroxyglutarate in glioma patients are precisely co-detected using MRS at 3T.2. Tumors with elevated glycine proliferate and progress rapidly.3. A high glycine/2HG ratio is predictive of shortened patient survival.

Health-related limitations prohibit a human from working in hazardous environments, due to which cognitive robots are needed to work there. A robot cannot learn the spatial semantics of the environment or object, which hinders the robot from interacting with the working environment. To overcome this problem, in this work, an agent is computationally devised that mimics the grid and place neuron functionality to learn cognitive maps from the input spatial data of an environment or an object. A novel quadrant-based approach is proposed to model the behavior of the grid neuron, which, like the real grid neuron, is capable of generating periodic hexagonal grid-like output patterns from the input body movement. Furthermore, a cognitive map formation and their learning mechanism are proposed using the place&ndash, grid neuron interaction system, which is meant for making predictions of environmental sensations from the body movement. A place sequence learning system is also introduced, which is like an episodic memory of a trip that is forgettable based on their usage frequency and helps in reducing the accumulation of error during avisit todistant places. The model has been deployed and validated in two different spatial data learning applications, one being the 2D object detection by touch, and another is the navigation in an environment. The result analysis shows that the proposed model is significantly associated with the expected outcomes.

Graphene oxide (GO) serves as a versatile platform for various applications, with the oxygen content of GO playing an important role in governing its properties. In the present study, different GO types covering a wide range of oxidation degree were prepared using our newly developed two-step method involving ball milling of graphite followed by its oxidation to GO. In addition to the variations in their physicochemical properties, the different GO types exhibited differences in proton relaxivity due to their paramagnetic nature. Nuclear magnetic resonance spectroscopy studies showed that the degree of oxidation of GO perturbs its nuclear relaxation properties and, together with intercalated Mn2+ ions, provides large contrast variation in magnetic resonance imaging (MRI). The study for the first time reveals that the surface chemistry of GO affects its relaxivity and opens up new avenues for developing tunable GO-based contrast agents in magnetic resonance imaging for diagnostics and therapies.

Groundwater quality plays a very important role in groundwater protection as well as demarcation of the groundwater depleted area which may be attempted for its improvement and conservation. An effort has been made to comprehend the water quality of Allahabad city with the help of groundwater sampling, their chemical analysis, and synthesis of results in GIS framework. The assessment of physiochemical parameters of groundwater samples for drinking purpose has been made using Water Quality Index and Geographic Information System. Spatial distribution of pH, electrical conductivity, total dissolved solids, fluoride, iron, total alkalinity, total hardness, chloride, sulphate, sodium, potassium, calcium, magnesium, bicarbonate, and nitrate content of groundwater samples collected from 12 locations and studied for pre-monsoon (May 2016) and post monsoon (Nov 2017) periods has been assessed using Arc-GIS. Water quality maps of pre-monsoon period reveal that 4.23% area is falling under good, 74.82% under moderate, and 12.12% under poor and 0.66% under very poor category while water quality maps for post monsoon period reveal that the 40.33% of area falls under good, 58.89% area under moderate and 0.77% under poor water quality. The observed values of various physiochemical parameters of water samples were also compared with standard values recommended by IS 10,500:2012. It is observed that depth to water has positive correlation with TDS, electrical conductivity, and hardness. The extent of pollution occurred in the city is due to over exploitation of groundwater, urbanization, and anthropogenic activities.

Drain removal after TKA can be painful. Prior research suggests that the "cough trick," in which a patient coughs at the same time she or he receives an injection, effectively decreases pain. To our knowledge, this intervention has not been evaluated as a way to reduce pain during other brief but painful interventions, such as removal of closed-suction drains after orthopaedic surgery.Does the cough trick reduce pain while a surgeon is removing a closed-suction drain after TKA?Fifty-six patients with primary osteoarthritis who underwent primary TKA were randomized into two groups: drain removal as the patient coughed (n = 28 patients; three men, 25 women) or drain removal using the usual process, without the cough trick (n = 28 patients; three men, 25 women). The study groups were not different in terms of gender, BMI, surgical time, or other baseline variables, and other than the addition of the cough trick, there were no differences in surgical treatment or other elements of aftercare. Likewise, at baseline, the verbal numeric rating scale (VNRS) score for pain before the drain was removed was not different between the groups (3.1 ± 1.7 versus 3.3 ± 1.3; p = 0.72). The level of pain before and during drain removal was recorded using a VNRS by an orthopaedic surgeon who was not involved in the care of the study patients. We considered the minimum clinically important difference on the 10-point scale to be 2 points, based on prior evidence.The mean ± SD VNRS for the pain level during drain removal was lower in the cough trick group than that in the control group (1.6 ± 1.0 versus 3.7 ± 1.9, mean difference 2.1; 95% CI, 1.3-2.9; p0.001).The cough trick during removal of a closed-suction drain tube in patients undergoing TKA reduced the level of pain in this small randomized trial. We suggest that surgeons consider this technique when removing drains after TKA because it is a noninvasive technique and it is easy to perform. Because the cough trick has been shown by others to be effective at reducing pain during venipuncture and parenteral injections, and we found it was effective for that purpose during drain removal after TKA, we believe this finding probably generalizes well to most minor procedures that cause transient, sharp pain. We suggest that it could be used to make such procedures more comfortable for patients, as well as for drain removal in other types of surgery where drains still are commonly used (including spine surgery and tumor surgery).Level I, therapeutic study.

This article describes how electronic healthcare has been the key application of pervasive computing innovations to enhance healthcare quality and protect human lives. Specific patients of constant sicknesses and elderly individuals, by and large, may oblige continuous observing of their wellbeing status wherever they are. In this regard, remote patient monitoring technology plays the various important role through wearable devices to monitor patient's physiological figures. But, this must ensure some broad issues like, wearability, adaptability, interoperability, integration, security, and network efficiency. This article proposes a data-driven multi-layer architecture for pervasively remote patient monitoring that incorporates aforesaid issues. It enables the patient's care at the real time and supports anywhere and anytime requirement with using network infrastructure efficiently.

Purpose: To compare extended care facility (ECF) and home as discharge destination after total knee arthroplasty (TKA) at a single high-volume tertiary center in South Korea. Materials and Methods: We retrospectively analyzed 1,120 primary TKAs (614 patients) performed between January 2012 and December 2013. A telephonic survey was conducted to determine discharge destination. The data reviewed included demographic and surgical data, functional outcome at 2 years and complications within 3 months. Results: ECF and home received 316 patients (51%) and 298 patients (49%), respectively. The ECF group had more bilateral TKA patients than the home group (272 vs. 234; p=0.014) and more patients with additional hospital stay (44 vs. 22; p=0.009). A higher tendency of complications was seen at home (n=8, 2.7%) than the ECF (n=2, 0.6%) (p=0.057). No significant differences were found in any functional outcome measure. Home patients had better patient satisfaction than ECF patients (81.9% vs. 54.3%; p

Just about 70% of the organizations are right now utilizing or wanting to utilize Cloud Computing, being the capacity to convey more adaptability to the business by means of cloud offerings and diminished equipment and staffing expenses, the principle motivations to embrace Cloud Computing. Data sharing along with the resources can be easy to handle and adopt in the cloud. But this adaptability also alarm the security breaches “Is the data safe”. So security is a noteworthy concern now days. In this paper we have concentrated on data security based on data centric approach. For this reason we have studies and suggest the analysis. The analysis is also supported by the previous outcomes.

Purpose To develop 1 H MR spectroscopy that provides distinction of γ-aminobutyric acid (GABA) signal at 3 T in vivo. Methods Triple-refocusing was tailored at 3 T, with numerical simulations and phantom validation, for distinction of the GABA 2.29-ppm resonance from the neighboring glutamate resonance. The optimization was performed on the inter-RF pulse time delays and the duration and carrier frequency of a non-slice-selective RF pulse. The optimized triple refocusing was tested in multiple regions in 6 healthy subjects, including hippocampus. The in vivo spectra were analyzed with the LCModel using in-house basis spectra. After normalization of the metabolite signal estimates to water, the metabolite concentrations were quantified with reference to medial-occipital creatine at 8 mM. Results A triple-refocusing scheme with optimized inter-RF pulse time delays (TE = 74 ms) was obtained for GABA detection. With optimized duration (14 ms) and carrier frequency (4.5 ppm) of the non-slice-selective RF pulse, the triple refocusing gave rise to distinction between the GABA 2.29-ppm and glutamate 2.35-ppm signals. The GABA 2.29-ppm signal was clearly discernible in spectra in vivo (voxel size 4 to 12 mL; scan times 4.3 to 17 minutes). With a total of 24 spectra from 6 gray or white matter-dominant regions, the GABA concentration was measured to be 0.62 to 1.15 mM (Cramer-Rao lower bound of 8 to 14%), and the glutamate level 5.8 to 11.2 mM (Cramer-Rao lower bound of 3 to 6%). Conclusion The optimized triple refocusing provided distinction between GABA and glutamate signals and permitted direct codetection of these metabolites in the human brain at 3 T in vivo.

Textual dissection can be a very useful aspect for the extraction of useful information from text documents. The ideology of textual dissection is the way people think about a particular text. It is the process where given reviews are classified as positive or negative. A huge amount of data (reviews) is present on the web which can be analyzed to make it useful. It can prove to be useful specifically for marketing, business, polity as it allow us to do easy analysis of the subject under consideration. In today’s era of internet, lots and lots of people can connect with each other. Internet has made it possible for us to connect and find out the opinions dissection. Internet has provided a lot of platform through which opinions from different people can be taken through Forums, Blogs, and Social networking sites. This paper proposes the use of Tweepy and TextBlob as a python library to access and classify Tweets using Naive Bayes, a Machine Learning technique. Our Technique is meant to ease out the process of analysis, summarization and classification.

Alzheimer's disease (AD) is the most common neurodegenerative disorder characterized by progressive loss of memory and cognitive function. The cerebral metabolic rate of glucose oxidation has been shown to be reduced in AD. The present study evaluated efficacy of dietary Amalaki Rasayana (AR), an Ayurvedic formulation used in Indian traditional system, in AbPP-PS1 mouse model of AD in ameliorating memory and neurometabolism, and compared with donepezil, a standard FDA approved drug for AD. The memory of mice was measured using Morris Water Maze analysis. The cerebral metabolism was followed by 13C labelling of brain amino acids in tissue extracts ex vivo using 1H-[13C]-NMR spectroscopy together with a short time infusion of [1,6-13C2]glucose to mice. The intervention with Amalaki Rasayana showed improved learning and memory in AbPP-PS1 mice. The 13C labelings of GluC4, GABAC2 and GlnC4 were reduced in AbPP-PS1 mice when compared with wild-type controls. Intervention of AR increased the 13C labelling of amino acids suggesting a significant enhancement in glutamatergic and GABAergic metabolic activity in AbPP-PS1 mice similar to that observed with donepezil treatment. These data suggest that AR has potential to improve memory and cognitive function in AD.

BACKGROUND AND OBJECTIVES Local control of disease is one of the main goals of osteosarcoma management. We conducted a retrospective evaluation of 95 operated cases of osteosarcoma over 7 years to know about the factors associated with local recurrence in resource-challenged environment of the developing world. METHODS The factors which were evaluated and compared between local recurrence and non-local recurrence groups included demographic profile, site of tumor, whether biopsy done outside, type of surgery (limb salvage or amputation), presence of pathological fracture, vicinity of neurovascular bundle, tumor volume, histological subtype, chemotherapy induced necrosis, surgical margins, and delay in surgery. The time to local recurrence after surgery was also noted in the local recurrence group. RESULTS At a mean follow-up of 2.8 years, biopsy done from outside the treating center and delay in surgery after completion of neo-adjuvant chemotherapy emerged as significant risk factors for local recurrence. Most of the local recurrences (80%) occurred within 12 months of the primary surgery. CONCLUSIONS Lack of financial resources and availability of few tertiary care centers dealing with musculoskeletal oncology in the developing countries, lead to overburden with a long waiting list for tumor surgery making the scenario different from the Western world.

Purpose To generate a preclinical model of isocitrate dehydrogenase (IDH) mutant gliomas from glioma patients and design a MRS method to test the compatibility of 2-hydroxyglutarate (2HG) production between the preclinical model and patients. Methods Five patient-derived xenograft (PDX) mice were generated from two glioma patients with IDH1 R132H mutation. A PRESS sequence was tailored at 9.4 T, with computer simulation and phantom analyses, for improving 2HG detection in mice. 2HG and other metabolites in the PDX mice were measured using the optimized MRS at 9.4 T and compared with 3 T MRS measurements of the metabolites in the parental-tumor patients. Spectral fitting was performed with LCModel using in-house basis spectra. Metabolite levels were quantified with reference to water. Results The PRESS TE was optimized to be 96 ms, at which the 2HG 2.25 ppm signal was narrow and inverted, thereby leading to unequivocal separation of the 2HG resonance from adjacent signals from other metabolites. The optimized MRS provided precise detection of 2HG in mice compared to short-TE MRS at 9.4 T. The 2HG estimates in PDX mice were in excellent agreement with the 2HG measurements in the patients. Conclusion The similarity of 2HG production between PDX models and parental-tumor patients indicates that PDX tumors retain the parental IDH metabolic fingerprint and can serve as a preclinical model for improving our understanding of the IDH-mutation associated metabolic reprogramming.

Several different approaches in recommender system have been suggested based on underlying rating history, but the majority of them suffer from the cold start problem (i.e., an inability to draw inferences to recommend items to new users. In this paper, a hybrid method has been proposed that combines personality traits using myPersonality application created by Facebook and the demographic characteristics into the traditional rating-based similarity computation. Majorly, personality information has been categorized into five personality traits: Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. Aforesaid personality characteristics can efficiently address the new user problem as it will accurately predict the similarity between users.

Aim: In this paper, we present a prospective observational study, which determines the incidence of bone metastases and its correlation with hormonal receptors (estrogen receptor [ER]/progesterone receptor [PR]) and human epidermal growth factor receptor 2 (HER2) in breast cancer. Materials and Methods: From October of 2015 to July 2017, 262 patients were eligible for the study, of which 98 patients presented/developed bone metastases. ER/PR and HER2 receptor status were determined, and bone scintigraphy with a technetium-99 m was carried out on each patient during the study. Results: The incidence rate of bone metastases as found in this study was 25.25%, and the mean and median age at diagnosis were 47.23 and 46, respectively (age range = 28–80). Bone metastases were more prevalent in ER-positive tumors (P = 0.043), tumors with lymph node positivity (P = 0.002), and lower grade tumors (P = 0.002), whereas visceral metastases were more common with ER-tumors (P = 0.005), tumors with higher grade (P = 0.012), and tumors with lymph node positivity (P = 0.034). In this study cohort, the spine and pelvis were the most commonly involved subsites of bone metastases (P < 0.001). Conclusion: This study demonstrates that the metastatic patterns in breast cancer strongly correlate with various breast cancer subtypes, mainly designated by ER, PR, and HER2. Hormone receptor-positive tumors show a predilection for bones as the first site of relapse compared to hormone-receptor-negative tumors which have a proclivity to develop as visceral metastases.

Visual object tracking is an important function in many real-time video surveillance applications, such as localization and spatio-temporal recognition of persons. In realworld applications, an object detector and tracker must interact on a periodic basis to discover new objects, and thereby to initiate tracks. Periodic interactions with the detector can also allow the tracker to validate and/or update its object template with new bounding boxes. However, bounding boxes provided by a state-of-the-art detector are noisy, due to changes in appearance, background and occlusion, which can cause the tracker to drift. Moreover, CNN-based detectors can provide a high level of accuracy at the expense of computational complexity, so interactions should be minimized for real-time applications. In this paper, a new approach is proposed to manage detector-tracker interactions for trackers from the Siamese-FC family. By integrating a change detection mechanism into a deep Siamese-FC tracker, its template can be adapted in response to changes in a target's appearance that lead to drifts during tracking. An abrupt change detection triggers an update of tracker template using the bounding box produced by the detector, while in the case of a gradual change, the detector is used to update an evolving set of templates for robust matching. Experiments were performed using state-of-the-art Siamese-FC trackers and the YOLOv3 detector on a subset of videos from the OTB-100 dataset that mimic video surveillance scenarios. Results highlight the importance for reliable VOT of using accurate detectors. They also indicate that our adaptive Siamese trackers are robust to noisy object detections, and can significantly improve the performance of Siamese-FC tracking.

Purpose: Ensuring compliance to treatment protocol, especially regular visit to treating facility, is an important aspect of clubfoot management. However, the factors affecting compliance to follow-up schedule are myriad. Methods: A cross-sectional study was undertaken among caregivers of clubfoot patients from a tertiary referral clubfoot clinic in a developing country. Hospital records were reviewed to collect demographic data and subjects were classified as either “regular” or “irregular” if they missed ≤3 and >3 scheduled hospital visits, respectively. Various factors that could affect compliance such as family size, number of children, literacy of caregiver, occupation of breadwinner, and time taken to travel to hospital were studied. Caregivers were probed regarding the reason for their irregularity. Results: A total of 238 patients were included, of which 138 formed the “regular” group and the rest 100 formed the “irregular” group. Patients in the regular group were significantly younger (mean age 43.8 months) compared to the irregular group (59.8 months; p = 0.001). The mean follow-up period in the regular group was 28.1 months and in the irregular group was 33.8 months. On univariate analysis, age, duration of follow-up, and transport duration were found to be significant between the two groups. However, multivariate analysis revealed that female children with clubfoot are more likely to be irregular as compared to males ( p = 0.038). Conclusion: In a developing country setting, higher age and being a female child are associated with irregularity to hospital visit protocol. At clubfoot clinics, identifying these children and counseling their caregivers might improve compliance.

Over the past two decades, coherent multidimensional spectroscopies have been implemented across the terahertz, infrared, visible, and ultraviolet regions of the electromagnetic spectrum. A combination of coherent excitation of several resonances with few-cycle pulses, and spectral decongestion along multiple spectral dimensions, has enabled new insights into wide ranging molecular scale phenomena, such as energy and charge delocalization in natural and artificial light-harvesting systems, hydrogen bonding dynamics in monolayers, and strong light-matter couplings in Fabry-Pérot cavities. However, measurements on ensembles have implied signal averaging over relevant details, such as morphological and energetic inhomogeneity, which are not rephased by the Fourier transform. Recent extension of these spectroscopies to provide diffraction-limited spatial resolution, while maintaining temporal and spectral information, has been exciting and has paved a way to address several challenging questions by going beyond ensemble averaging. The aim of this Perspective is to discuss the technological developments that have eventually enabled spatially resolved multidimensional electronic spectroscopies and highlight some of the very recent findings already made possible by introducing spatial resolution in a powerful spectroscopic tool.

The purpose of this randomized study was to compare clinical and surgical outcomes of total knee replacements (TKRs) in the early postoperative period using midvastus approach versus medial parapatellar approach in Asian population in a double blind manner. Forty-two knees each were operated using midvastus approach and the medial parapatellar approach. Clinical parameters that were evaluated included Knee Society score (KSS); knee pain using visual analogue scale (VAS) on day 1, 1 week, and 1 month; time required to straight leg raise (SLR); patellar tracking; mean extensor lag at 1 week and 1 month; and time of discharge from the hospital. Surgical parameters that were evaluated included tourniquet time, incidence of lateral retinacular release, estimated blood loss, and any complications during the surgery. KSS at 1 week and 1 month postoperatively were significantly higher in the midvastus group as compared with medial parapatellar group; though similar at 3 months, 6 months, and 1 year. The patients in midvastus group required fewer number of lateral retinacular releases; achieved SLR earlier; had less mean extensor lag at 1 week; had less mean VAS score at day 1, 1 week, and 1 month; and had shorter hospital stay. There was no significant difference in the mean tourniquet time and estimated blood loss. One patient had patellar maltracking in the medial parapatellar group as compared with none in midvastus group. Midvastus approach to TKR results in quicker functional recovery with early discharge and rehabilitation in the Asian population as compared with medial parapatellar approach.

Purpose To test the efficacy of triple-refocusing MR spectroscopy (MRS) for improved detection of 2-hydroxyglutarate (2HG) in brain tumors at 3T in vivo. Methods The triple-refocusing sequence parameters were tailored at 3T, with density-matrix simulations and phantom validation, for enhancing the 2HG 2.25-ppm signal selectivity with respect to the adjacent resonances of glutamate (Glu), glutamine (Gln), and gamma-aminobutyric acid (GABA). In vivo MRS data were acquired from 15 glioma patients and analyzed with LCModel using calculated basis spectra. Metabolites were quantified with reference to water. Results A triple-refocusing sequence (echo time = 137 ms) was obtained for 2HG detection. The 2HG 2.25-ppm signal was large and narrow while the Glu and Gln signals between 2.2 and 2.3 ppm were minimal. The optimized triple refocusing offered improved separation of 2HG from Glu, Gln and GABA when compared with published MRS methods. 2HG was detected in all 15 patients, the estimated 2HG concentrations ranging from 2.4 to 15.0 mM, with Cramer-Rao lower bounds of 2%–11%. The 2HG estimates did not show significant correlation with total choline. Conclusion The optimized triple refocusing provides excellent 2HG signal discrimination from adjacent resonances and may confer reliable in vivo measurement of 2HG at relatively low concentrations. Magn Reson Med 78:40–48, 2017. © 2016 International Society for Magnetic Resonance in Medicine

PURPOSE To test the efficacy of 7T MRS for in vivo detection of 2-hydroxyglutarate (2HG) in brain tumors. METHODS The subecho times of point-resolved spectroscopy (PRESS) were optimized at 7T with density-matrix simulations and phantom validation to improve the 2HG signal selectivity with respect to the neighboring resonances of γ-aminobutyric acid (GABA), glutamate (Glu), and glutamine (Gln). MRS data were acquired from 12 subjects with gliomas in vivo and analyzed with LCModel using calculated basis spectra. Metabolite levels were quantified using unsuppressed short echo time (TE) water as a reference. RESULTS The PRESS TE was optimized as TE = 78 ms (TE1 = 58 ms and TE2 = 20 ms), at which the 2HG 2.25 ppm resonance appeared as a temporally maximum inverted narrow peak and the GABA, Glu, and Gln resonances between 2.2 and 2.5 ppm were all positive peaks. The PRESS TE = 78 ms method offered improved discrimination of 2HG from Glu, Gln, and GABA when compared with short-TE MRS. 2HG was detected in all patients enrolled in the study, the estimated 2HG concentrations ranging from 1.0 to 6.2 mM, with percentage standard deviation of 2%-7%. CONCLUSION Data indicate that the optimized MRS provides good selectivity of 2HG from other metabolite signals and may confer reliable in vivo detection of 2HG at relatively low concentrations. Magn Reson Med 77:936-944, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Vibrational-electronic (vibronic) resonance and its possible role in energy and charge transfer have been experimentally and theoretically investigated in several photosynthetic proteins. Using a dimer modeled on a typical photosynthetic protein, we contrast the description of such excitons provided by an exact basis set description, as opposed to a basis set with reduced vibrational dimensionality. Using a reduced analytical description of the full Hamiltonian, we show that in the presence of vibrational excitation both on electronically excited as well as unexcited sites, constructive interference between such basis states causes vibronic coupling between excitons to become progressively stronger with increasing quanta of vibrational excitation. This effect leads to three distinguishing features of excitons coupled through a vibronic resonance, which are not captured in basis sets that restrict ground state vibrations: (1) the vibronic resonance criterion itself, (2) vibronically assisted perfect delocalization between sites even though purely electronic mixing between the sites is imperfect due to energetic disorder, and (3) the nuclear distortion accompanying vibronic excitons becoming increasingly larger for resonant vibronic coupling involving higher vibrational quanta. In terms of spectroscopically observable limitations of reduced basis set descriptions of vibronic resonance, several differences are seen in absorption and emission spectra but may be obscured on account of overwhelming line broadening. However, we show that several features such as vibronic exciton delocalization and vibrational distortions associated with electronic excitations, which ultimately dictate the excited state wavepacket motions and relaxation processes, are fundamentally not described by basis sets that restrict ground state vibrations.

In the past two decads, iris spoofing detection has occupied an ample space in the literature of iris biometics. The textured lens may be used to spoof the Iris Recognition (IR) system by exploiting its external texture. Besides, the soft lens may cause an upsurge in the false rejection rate as it blurs the iris texture. Therefore, it is foremost to identify contact lens in human eyes before accessing an IR system. This paper proposes a novel fusion-based approach to discriminate live iris from contact lens images that combines handcrafted and data-driven features. It also demonstrates a Densely-connected Contact-lens Classification Network (DCCNet) as a data-driven model that is basically a customized Densenet121 framework. The DCCNet features are -pooled with handcrafted counterparts to create a combined feature set. However, the optimal features are identified by top-k feature selection using the Friedman test and are fused through score-level fusion. The assessment of the proposed approach includes several experiments simulated on three iris databases, i.e. Notre Dame (ND) Contact Lens 2013, IIIT-Delhi Contact Lens (IIITD), and Clarkson Databases. The equal error rate (EER) and the detection error tradeoff (DET) curve are used as performance metrics. Further, the statistical analysis is performed using Nemenyi and Bonferroni-Dunn tests, where the proposed approach significantly improves the state of the arts.

The novel copper nanoparticles (CuNPs) were synthesized using aqueous leaf extract of Ageratum houstonianum Mill. (AHLE). The green synthesized AH-CuNPs have a useful dye degradation property in the existence of daylight. The photocatalytic activity of AH-CuNPs was evaluated against an azo dye congo red (CR), whereas, same NPs displayed no effect on other dyes. The CR was completely degraded within 2 h, and the reaction rate was followed by pseudo-first-order kinetics, and the rate constant was recorded 3.1 × 10−4 s−1, (R2 = 0.9359). Antibacterial activity of green synthesized AH-CuNPs was studied against gram-negative bacterium Escherichia coli (MTCC no. 40), and a significant growth inhibition was recorded with 12.43 ± 0.233 mm zone of inhibition. The AH-CuNPs were characterized through UV-visible spectroscopy, XRD, SEM, FT-IR, TEM, and zeta particle size analyzer. Ageratum houstonianum mediated green synthesized copper nanoparticles (AH-CuNPs) were cubic, hexagonal, and rectangular in shape, with average size of ∼80 nm. The optical band gap was 4.5 eV, which was investigated using UV-visible spectroscopy, and the band gap value revealed that AH-CuNPs were semiconductor materials.

We present a theory for modeling fluorescence-detected two-dimensional electronic spectroscopy of multichromophoric systems. The theory is tested by comparison of the predicted spectra of the light-harvesting complex LH2 with experimental data. A qualitative explanation of the strong cross-peaks as compared to conventional two-dimensional electronic spectra is given. The strong cross-peaks are attributed to the clean ground-state signal that is revealed when the annihilation of exciton pairs created on the same LH2 complex cancels oppositely signed signals from the doubly excited state. This annihilation process occurs much faster than the nonradiative relaxation. Furthermore, the line shape difference is attributed to slow dynamics, exciton delocalization within the bands, and intraband exciton-exciton annihilation. This is in line with existing theories presented for model systems. We further propose the use of time-resolved fluorescence-detected two-dimensional spectroscopy to study state-resolved exciton-exciton annihilation.