Technology-assisted white cane: evaluation and future directions

Background Several technology-assisted aids are available to help blind and visually impaired people perform their daily activities. The current research uses the state-of-the-art technology to enhance the utility of traditional navigational aids to produce solutions that are more reliable. In this regard, a white cane is no exception, which is supplemented with the existing technologies to design Electronic Travel Aids (ETAs), Electronic Orientation Aids (EOAs), and Position Locator Devices (PLDs). Although several review articles uncover the strengths and limitations of research contributions that extend traditional navigational aids, we find no review article that covers research contributions on a technology-assisted white cane. The authors attempt to fill this literature gap by reviewing the most relevant research articles published during 2010–2017 with the common objective of enhancing the utility of white cane with the existing technology. Methods The authors have collected the relevant literature published during 2010–17 by searching and browsing all the major digital libraries and publishers’ websites. The inclusion/exclusion criteria were applied to select the research articles that are relevant to the topic of this review article, and all other irrelevant papers were excluded. Among the 577 (534 through database searching and 43 through other sources) initially screened papers, the authors collected 228 full-text articles, which after applying exclusion/inclusion criteria resulted in 36 papers that were included in the evaluation, comparison, and discussion. This also includes research articles of commercially available aids published before the specified range. Results The findings show that the research trend is shifting towards developing a technology-assisted white cane solution that is applicable in both indoor and outdoor environments to aid blind users in navigation. In this regard, exploiting smartphones to develop low-cost and user-friendly navigation solution is among the best research opportunities to explore. In addition, the authors contribute a theoretical evaluation framework to compare and evaluate the state-of-the-art solutions, identify research trends and future directions. Discussion Researchers have been in the quest to find out ways of enhancing the utility of white cane using existing technology. However, for a more reliable enhancement, the design should have user-centric characteristics. It should be portable, reliable, trust-worthy, lightweight, less costly, less power hungry, and require minimal training with special emphasis on its ergonomics and social acceptance. Smartphones, which are the ubiquitous and general-purpose portable devices, should be considered to exploit its capabilities in making technology-assisted white cane smarter and reliable

Mandibular Reconstruction with Free Fibula Flap: Experience at Hayatabad Medical Complex, Peshawar

Background: Mandibular defects may result from trauma, infections, cancer ablation or radiation necrosis. These defects may vary according to the content and nature of the tissues that require reconstruction. The objective of this study was to evaluate the outcome of vascularised free fibula flap for mandibular reconstruction in terms of flap success rate and complications.Material and Methods: This prospective clinical study was carried out at Department of Plastic Surgery, Hayatabad Medical Complex, Peshawar from January 2014 to December 2018. The study included patients of either gender who underwent mandibular reconstruction with free fibula oseteocutaneous flap during the study period. Diabetic patients with underlying vascular pathologies and cachectic patients were excluded from the study.Results: There were 56 patients with 38 males and 18 females. Their age ranged from 24-66 years with a mean age of 36 years. The mandibular defects resulted from various etiologies and included: Squamous cell carcinoma (n=27, 48.21%), Giant cell granuloma (n=3; 5.35%), Ameloblastoma (n=2; 3.57%), Road traffic accidents (n=10; 17.85%), Firearm injury (n=9; 16%), Bomb blast injury (n=3; 5.35%) and osteoradionecrosis (n=2; 3.57%). Primary reconstruction of the mandibular defects was performed in 44 patients, whereas delayed reconstruction was performed in 12 patients. Out of the 56 flaps, 49 flaps survived completely. Our share of complications was as follows: Wound infections (n=13; 23.21%), Skin graft loss at donor site (n=5; 8.95%), Complete flap loss (n=4; 7.14%), Orocutaneous fistulae (n=3; 5.35%), Ankle instability (n=2; 3.57%), Skin paddle necrosis (n=1; 1.78%) and sensory deficit distal to donor site (n=1; 1.78%).Conclusions: Microvascular free fibula is a reliable tool for mandibular reconstruction following tumor resection or trauma. The flap has a high success rate and relatively fewer complications

Ethnomedicinal uses of the Ferns of Shishikoh Valley, District Chitral, Pakistan

The indigenous communities of Shishikoh valley are often using various ferns taxa regularly. The current research work was intended for documenting the ethnomedicinal knowledge of ferns. A total of 18 taxa were recorded that belonged to 9 genera and 6 families being used in the treatment of different ailments. Pteridaceae was the leading family with 6 taxa (33.33%), followed by Aspleniaceae with 4 taxa (22.22%), Athyriaceae and Equisetaceae each with 3 taxa (16.67%) followed by Dryopteridaceae and Marsileaceae each with 1 taxon (5.56%). The reported ferns taxa were used as anthelminthic, anti-rheumatic, astringent and wound healing agents and in the treatment of different ailments such as asthma, bronchitis, diarrhea, dysentery, gonorrhea, hepatitis, infertility, influenza, kidney disorders, measles, oral ulcer, oral thrush, pneumonia, pyelonephritis, pharyngitis, scorpion bite, sinusitis, tonsillitis and tuberculosis. Ethnomedicinal knowledge is a valuable source for the innovation of different allopathic, homeopathic and herbal drugs that are used for the treatment of different ailments. The fern species may be used commercially for medicinal purposes through sustainable way. Their proper cultivation and awareness about medicinal values among local community leads to discover new drugs

Deep learning for plant bioinformatics: an explainable gradient-based approach for disease detection

Emerging in the realm of bioinformatics, plant bioinformatics integrates computational and statistical methods to study plant genomes, transcriptomes, and proteomes. With the introduction of high-throughput sequencing technologies and other omics data, the demand for automated methods to analyze and interpret these data has increased. We propose a novel explainable gradient-based approach EG-CNN model for both omics data and hyperspectral images to predict the type of attack on plants in this study. We gathered gene expression, metabolite, and hyperspectral image data from plants afflicted with four prevalent diseases: powdery mildew, rust, leaf spot, and blight. Our proposed EG-CNN model employs a combination of these omics data to learn crucial plant disease detection characteristics. We trained our model with multiple hyperparameters, such as the learning rate, number of hidden layers, and dropout rate, and attained a test set accuracy of 95.5%. We also conducted a sensitivity analysis to determine the model’s resistance to hyperparameter variations. Our analysis revealed that our model exhibited a notable degree of resilience in the face of these variations, resulting in only marginal changes in performance. Furthermore, we conducted a comparative examination of the time efficiency of our EG-CNN model in relation to baseline models, including SVM, Random Forest, and Logistic Regression. Although our model necessitates additional time for training and validation due to its intricate architecture, it demonstrates a faster testing time per sample, offering potential advantages in real-world scenarios where speed is paramount. To gain insights into the internal representations of our EG-CNN model, we employed saliency maps for a qualitative analysis. This visualization approach allowed us to ascertain that our model effectively captures crucial aspects of plant disease, encompassing alterations in gene expression, metabolite levels, and spectral discrepancies within plant tissues. Leveraging omics data and hyperspectral images, this study underscores the potential of deep learning methods in the realm of plant disease detection. The proposed EG-CNN model exhibited impressive accuracy and displayed a remarkable degree of insensitivity to hyperparameter variations, which holds promise for future plant bioinformatics applications

Adaptive Backstepping Integral Sliding Mode Control for 5DOF Barge-Type OFWT under Output Constraint

This article presents a new control solution for a dynamical model of a translational oscillator with a rotational actuator (TORA) based on multi-body dynamics for a barge-type offshore floating wind turbine (OFWT). TORA has been employed as an active structural control strategy. The solution of bounding the output movements of platform pitch and tower bending angle to a certain limit, along with mitigating the OFWT vibrations due to environmental disturbances and uncertainties, is presented in this novel control framework. This new control algorithm consists of a high-gain observer (HGO)-based adaptive backstepping integral sliding mode control (ISMC) and a barrier Lyapunov function (BLF). This guarantees satisfying the constraints on the states and effectively resolves the problem of the unavailability of the system states. The proposed control law based on the BLF has been compared with an adaptive backstepping ISMC to show the efficiency of the output-constraint control scheme. Through MATLAB/SIMULINK numerical simulations and their numeric error table, the effectiveness of the proposed control scheme has been examined. The results confirm the validity and efficiency of the proposed control approaches

CHALLANGES AND PROSPECTS FOR TOMATO PRODUCTIVITY IN RESPONSE TO CLIMATIC VARIATIONS: EVIDNECES FROM KHYBER PAKHTUNKHWA-PAKISTAN

Climate change is the momentous and persisting change in the world’s temperature, precipitation, humidity, and other climatic variables. This study, therefore estimated the impact of climatic variations on tomato productivity across agro ecological zones of Khyber Pakhtunkhwa, Pakistan. Panel data for 28 years (1991-2018) across the six districts of the agro ecological was used due to availability of data on tomato productivity and climatic variables. Yield of tomato, area, maximum temperature and rainfall were included in the final estimated model. The results indicate that the average maximum temperature and average maximum temperature square have a significant impact on tomato yield. Average maximum temperature has positive coefficient while the average maximum temperature square has a negative coefficient. This demonstrates that, at first, the tomato yield increases as the temperature rises. It reaches the maximum at the critical temperature (34.95ºC) but shows a decline once the temperature rises from the critical value

Analyzing Nexus between Economic Complexity, Renewable Energy, and Environmental Quality in Japan: A New Evidence from QARDL Approach

The economic complexity index is an effective dimensionality reduction tool that is applied to forecast and predict future economic growth, income, and environmental quality. Renewable energy plays an important role in mitigation of carbon dioxide emissions. This study explores the nexus between economic complexity, renewable energy, FDI, trade, and environmental quality in Japan for the period 1970Q1-2019Q4. We use carbon dioxide (CO2) emissions as dependent variable while economic complexity index (ECI), foreign direct investment (FDI) inflow, renewable energy (RNE), and trade as explanatory variables. This study applies a quantile autoaggressive approach for analysis; the result of this study suggests a long-run implication of the ECI, FDI, GDP, RNE, and trade for the CO2 emissions. While only RNE and trade show mixed results in the short run, the rest of the variables do not have short-run implications. This implies that emissions mostly result in the industrial production activities only in the long run and in some quantiles only in the short run. The Japanese government may adopt different measures to reduce the CO2 emissions in the country, such as carbon tax and tax exemption on renewable energy investment. Furthermore, the government may adopt the renewal energy in production, which could achieve sustainable development goal

Validated RP-HPLC method for the simultaneous determination of glucosamine sulphate and curcumin in cream formulation: A novel stability-indicating study

Purpose: To develop and validate a stability-indicating reverse phase-high performance liquid chromatography (RP-HPLC) method for the simultaneous determination of glucosamine sulphate (GS) and curcumin (Cur) in drug solution and formulation.Methods: The optimized chromatographic conditions were achieved by passing various compositions of mobile phases over  different reverse phase chromatographic columns. Various validation parameters, including linearity, range, limit of detection (LOD), limit of quantification (LOQ), accuracy, precision, specificity and system suitability were performed and evaluated. Stability studies under stressed conditions were done to evaluate the effects of acid, alkali, oxidation, heat and degradation by UV light.Results: The validated method was linear over the concentration range of 0.094 to 1.5 mg/mL for GS and 0.125 to 1.5 mg/mL for Cur, with a correlation coefficient > 0.999. The Intra and inter-day precision were 1.9 % for GS and 0.5 % for Cur, while accuracy was 96 and 102 % for GS and Cur, respectively. Stability studies showed that GS was highly sensitive to acid, alkali and oxidation and less sensitive to heat and UV. Cur was stable against acid, heat and oxidation but sensitive to alkali and UV.Conclusion: The developed and validated method was precise and accurate for both GS and Cur and can potentially be utilized for their identification and quantification at industrial, research and quality control laboratories

Genetic characterization of human echinococcosis in Southern Punjab, Pakistan

IntroductionEchinococcosis is a neglected tropical zoonotic infection that affects both the human and livestock populations. In Pakistan, the infection is long-standing, but data on its molecular epidemiology and genotypic characterization in the southern Punjab region are limited. The aim of the current study was the molecular characterization of human echinococcosis in southern Punjab, Pakistan.MethodsEchinococcal cysts were obtained from a total of 28 surgically treated patients. Patients’ demographic characteristics were also recorded. The cyst samples were subjected to further processing to isolate DNA in order to probe the Nad1 and Cyt-b genes, followed by DNA sequencing and phylogenetic analysis for genotypic identification.ResultsThe majority of the echinococcal cysts were from male patients (60.7%). The liver was the most commonly infected organ (60.71%), followed by the lungs (25%), spleen (7.14%), and the mesentery (7.14%). Molecular and genotypic identification through sequencing and phylogenetic tree analysis showed that most of the cysts (24/28, 85.7%) were caused by the species Echinococcus granulosus sensu stricto (E. granulosus s.s.) (G1 and G3), followed by Echinococcus multilocularis (E. multilocularis) and Echinococcus canadensis (E. canadensis) (G6/G7) (3/28, 10.8%, and 1/28, 3.5%, respectively).ConclusionThe current study concluded that the majority of human infections were caused by E. granulosus s.s., followed by the E. multilocularis and E. canadensis species (G6/G7). Genotypic characterization among both human and livestock populations is needed to explore the genetic diversity of echinococcosis