DiaNet v2 deep learning based method for diabetes diagnosis using retinal images.

Diabetes mellitus (DM) is a prevalent chronic metabolic disorder linked to increased morbidity and mortality. With a significant portion of cases remaining undiagnosed, particularly in the Middle East North Africa (MENA) region, more accurate and accessible diagnostic methods are essential. Current diagnostic tests like fasting plasma glucose (FPG), oral glucose tolerance tests (OGTT), random plasma glucose (RPG), and hemoglobin A1c (HbA1c) have limitations, leading to misclassifications and discomfort for patients. The aim of this study is to enhance diabetes diagnosis accuracy by developing an improved predictive model using retinal images from the Qatari population, addressing the limitations of current diagnostic methods. This study explores an alternative approach involving retinal images, building upon the DiaNet model, the first deep learning model for diabetes detection based solely on retinal images. The newly proposed DiaNet v2 model is developed using a large dataset from Qatar Biobank (QBB) and Hamad Medical Corporation (HMC) covering wide range of pathologies in the the retinal images. Utilizing the most extensive collection of retinal images from the 5545 participants (2540 diabetic patients and 3005 control), DiaNet v2 is developed for diabetes diagnosis. DiaNet v2 achieves an impressive accuracy of over 92%, 93% sensitivity, and 91% specificity in distinguishing diabetic patients from the control group. Given the high prevalence of diabetes and the limitations of existing diagnostic methods in clinical setup, this study proposes an innovative solution. By leveraging a comprehensive retinal image dataset and applying advanced deep learning techniques, DiaNet v2 demonstrates a remarkable accuracy in diabetes diagnosis. This approach has the potential to revolutionize diabetes detection, providing a more accessible, non-invasive and accurate method for early intervention and treatment planning, particularly in regions with high diabetes rates like MENA.

Performance evaluation of various techniques in estimating precipitation record of a sparsely gauged mountainous watershed.

Comprehensive precipitation data is essential for hydrological, agricultural, and climatological studies. Yet, gaps and sparse rain gauge distribution pose challenges, requiring imputation algorithms to fill data gaps. The aim of this research is to evaluate the performance of several approaches for estimating incomplete precipitation data in the Upper Indus Basin (UIB). Eight various imputation approaches were used on sparsely gauged mountainous UIB on a monthly time series of twenty-four meteorological observatories. Following that, the estimation approaches were evaluated using a rank-based approach comprising four different statistical indicators. The results indicate that multiple linear regression is the best-performing strategy for most of the stations regardless of season or orography, followed by the arithmetic average method and inverse distance weighing method.

Future climate projections using the LARS-WG6 downscaling model over Upper Indus Basin, Pakistan.

This study investigates the projections of precipitation and temperature at the local scale in the Upper Indus Basin (UIB) in Pakistan using six Regional Climate Models (RCMs) from CORDEX under two Representative Concentration Pathways (RCP 4.5 and RCP 8.5). For twenty-four stations spread across the study area, the Long Ashton Research Station Weather Generator, version six (LARS-WG6), was used to downscale the daily data from the six different RCMs for maximum temperature (Tmax), minimum temperature (Tmin), and precipitation (pr) at a spatial resolution of 0.44°. Investigations were made to predict changes in mean annual values of Tmax, Tmin, and precipitation during two future periods, i.e., the mid-century (2041-2070) and end-century (2071-2100). The model results from statistical and graphical comparison validated that the LARS-WG6 can simulate the temperature and the precipitation in the UIB. Each of the six RCMs and their ensemble revealed a continuously increased temperature projection in the basin; nevertheless, there is variation in projected magnitude across RCMs and between RCPs. The rise in average Tmax and Tmin was more significant under RCP 8.5 than RCP 4.5, possibly due to unmitigated greenhouse gas emissions (GHGs). The precipitation projections follow the non-uniform trend, i.e., not all RCMs agree on whether the precipitation will increase or decrease in the basin, and no orderly variations were detected during any future periods under any RCP. However, an overall increase in precipitation is projected by the ensemble of RCMs.

Valorization of mustard and sesame oilseed cakes for food application through eco-innovative technologies.

Agricultural waste valorization is currently getting attention across the world owing to its environmental impact and rich phytochemistry. The mandate of the current investigation was the extraction and characterization of bioactive moieties from the mustard oilseed cake/meal MOC and sesame oilseed cake/meal SOC through ultrasound extraction (UE) techniques due to its higher yield and less burden on the environment as compared to conventional extraction (CE). Purposely, the MOC and SOC were initially subjected to compositional analysis. Thereafter, bioactive moieties were extracted by using different solvents, that is, ethanol and distilled water, and by applying conventional and ultrasonic extraction techniques. The outcomes indicated that among the techniques, ultrasound exhibited the highest results, and in solvents, ethanol performed better. The treatment extracted with ethanol with UE at 10 min showed the best result for total phenolic contents (TPC) as (6.07 ± 0.03 09 g GAE/100 g MOC) and (7.09 ± 0.04 g GAE/100 g SOC), DPPH radical scavenging activity (67.3 ± 1.9 TE/100 g MOC) & (72.68 ± 1.9 TE/100 g SOC), and FRAP was recorded as (2.83 ± 0.02 g TE/100 g MOC) & (3.56 ± 0.03 g TE/100 g SOC). The higher antioxidant potential showed that the mustard and sesame waste holds significant therapeutic potential owing to its rich antioxidant profile and thus should be utilized for the development of functional products against lifestyle-related disorders. In conclusion, ultrasound is a better technique for maximum as well as accurate extraction, with ethanol exhibiting as a better solvent for this process with more yields as compared to distilled water.

First observation on emergence of strong room-temperature ferroelectricity and multiferroicity in 2D-Ti3C2T x free-standing MXene film.

Two-dimensional (2D) multiferroics are key candidate materials towards advancement of smart technology. Here, we employed a simple synthesis approach to address the long-awaited dream of developing ferroelectric and multiferroic 2D materials, especially in the new class of materials called MXenes. The etched Ti3C2T x MXene was first synthesized after HF-treatment followed by a delamination process for successful synthesis of free-standing Ti3C2T x film. The free-standing film was then exposed to air at room-temperature and heated at different temperatures to form a TiO2 layer derived from the Ti3C2T x MXene itself. The ferroelectric measurement showed a clear polarization hysteresis loop at room-temperature. Also, due to the reported ferromagnetic behavior of Ti3C2T x MXene, our composite could show multiferroic properties at room-temperature. The magnetoelectric coupling test was also performed that showed a clear, switchable spontaneous polarization under applied magnetic field. TiO2 is reported to be an incipient ferroelectric that assumes a ferroelectric phase in composite form. The structural and morphological analysis confirmed successful synthesis of free-standing film and the Raman spectroscopy revealed the formation of different phases of TiO2 and the observed ferroelectricity could be due to structural deformation as a result of the formation of this new phase. The measured value of remanent polarization is 0.5 µC cm-2. This is the first report on the existence of a ferroelectric phase and multiferroic coupling in 2D free-standing MXene film at room-temperature which opens-up the possibility of 2D material-based electric and magnetic data storage applications at room-temperature.

Authors' response: Proliferative retinopathy in chronic myeloid leukemia and diabetes: A "double whammy".

This editorial discusses that the diabetic proliferative retinopathy progresses as a result of ischemia angiogenic stimuli, which may be exacerbated by concomitant CML retinopathy generating increased blood viscosity and vascular endothelial growth factor levels.

Ophthalmologic manifestations as the initial presentation of chronic myeloid leukemia: A review.

The presentation of chronic myeloid leukemia (CML) can be variable and related to the phase of the disease. It can manifest a wide range of symptoms and signs; ocular involvement is reported in patients with leukemia at the time of diagnosis. We describe ophthalmic manifestations as an initial presentation in patients with CML. We identified 38 publications between 1971 and 2020 describing ocular manifestations in CML. Ophthalmic problems occur either from direct or indirect infiltration of neoplastic cells or from secondary causes. Although nearly all ocular structures may be affected, leukemic retinopathy is the most frequent clinical manifestation. Others include iris infiltration, anterior uveitis, hypopyon, exudative/serous retinal detachment, and optic nerve infiltration.

Effects of transfusion of stored blood in patients with transfusion-dependent thalassemia.

OBJECTIVES: The aim of this study was to investigate the hematological and biochemical effects of stored blood transfusion on patients with transfusion-dependent thalassemia (TDT). METHODS: In this quasi-experimental study, 20-patients with TDT were enrolled. Each participant received on first visit, freshly collected red cell concentrate (RCC) (<2-days storage) and 15-days later on second visit, 7-days stored blood. Blood samples were obtained immediately before and 24-hours after each transfusion. Differences in the Complete blood counts, bilirubin, LDH, C-Reactive protein, ferritin, and iron levels in the pre- and post-transfusion samples were compared between the first and second transfusion. RESULTS: Fresh blood transfusion resulted in a higher (but non-significant) increase in hemoglobin and other red cell parameters. Notably, a significant increase in white cell counts (WCC) was seen in 7-days stored blood vs fresh blood (1.82×109/l vs 1.01×109/l, P=0.002). No statistically significant difference was found in LDH, direct and indirect bilirubin, creatinine, blood glucose, serum uric acid, serum ferritin, and serum Iron levels. There was a statistically significant rise in C-reactive protein levels in stored (6.43±7.46 mg/dl) versus fresh RCC (1.89±2.38 mg/dl), p-value =0.012. CONCLUSIONS: We show that in patients with chronic TDT, an increase in inflammation-associated markers (WCC and CRP) is observed. Further studies to assess the extent and duration of this increase are needed.

Smartphone Based Human Breath Analysis from Respiratory Sounds.

Human breath analysis plays important role for diagnosis and management of pulmonary diseases to guarantee normal health. The critical task is to distinguish normal and abnormal lung sounds. This research work presents a scheme for breath analysis used to detect irregular patterns occurred in respiratory cycles due to respiratory diseases. After de-noising breath segments using wavelet de-noising method, intrinsic mode functions are extracted with complete ensemble empirical mode decomposition (CEEMD). Instantaneous frequency (IF) and instantaneous envelope are extracted to get robust features for classification. The study contains breath samples captured using smartphone under natural setting. The data set contains 255 breath cycles. For cycle classification, Bag-of-word was applied to group segments based features. The support vector machine (SVM) was applied on randomly partitioned data samples. Experiments resulted with performance accuracy of (75.21%±2) for asthmatic inspiratory cycles and (75.5%±3%) for complete Respiratory Sounds (RS) cycle with diagnostic odds ratio (DOR) of 20.61% and 13.S7% respectively.

Performance evaluation of 1-D numerical model HEC-RAS towards modeling sediment depositions and sediment flushing operations for the reservoirs.

Sediment inflow to the reservoir is a key factor to calculate life of the reservoir. Flushing is a very useful technique in order to enhance the life of reservoir. From the literature review, 14 reservoirs were considered where flushing has already been practiced and only 6 reservoirs were found successful in flushing. The others were found partially flushed. In this research, data of three successfully flushed reservoirs namely Baira reservoir (India), Gebidem reservoir (Switzerland), and Gmund reservoir (Austria) were used to run 1-D numerical model HEC-RAS. In the first phase, the longitudinal profiles of delta were modeled and calibrated with observed sediment depositions. In the presence of available data of discharges and respective reservoir levels, the modeled deltas were used for flushing the deltas. With the help of modeled delta and corresponding flushing discharges, sediment deposition and flushing durations were computed. The simulated flushed durations were 31, 102, and 180 h for Baira, Gebidem, and Gmund reservoirs, respectively. The simulated flushed durations were found close to observed durations. Hence, the use of 1-D numerical model HEC-RAS is encouraged for modeling of sediment deposits and flushing operations.

Neural predictors of gait stability when walking freely in the real-world.

BACKGROUND: Gait impairments during real-world locomotion are common in neurological diseases. However, very little is currently known about the neural correlates of walking in the real world and on which regions of the brain are involved in regulating gait stability and performance. As a first step to understanding how neural control of gait may be impaired in neurological conditions such as Parkinson's disease, we investigated how regional brain activation might predict walking performance in the urban environment and whilst engaging with secondary tasks in healthy subjects. METHODS: We recorded gait characteristics including trunk acceleration and brain activation in 14 healthy young subjects whilst they walked around the university campus freely (single task), while conversing with the experimenter and while texting with their smartphone. Neural spectral power density (PSD) was evaluated in three brain regions of interest, namely the pre-frontal cortex (PFC) and bilateral posterior parietal cortex (right/left PPC). We hypothesized that specific regional neural activation would predict trunk acceleration data obtained during the different walking conditions. RESULTS: Vertical trunk acceleration was predicted by gait velocity and left PPC theta (4-7 Hz) band PSD in single-task walking (R-squared = 0.725, p = 0.001) and by gait velocity and left PPC alpha (8-12 Hz) band PSD in walking while conversing (R-squared = 0.727, p = 0.001). Medio-lateral trunk acceleration was predicted by left PPC beta (15-25 Hz) band PSD when walking while texting (R-squared = 0.434, p = 0.010). CONCLUSIONS: We suggest that the left PPC may be involved in the processes of sensorimotor integration and gait control during walking in real-world conditions. Frequency-specific coding was operative in different dual tasks and may be developed as biomarkers of gait deficits in neurological conditions during performance of these types of, now commonly undertaken, dual tasks.

Possible options to slow down the advancement rate of Tarbela delta.

The pivot point of delta in Tarbela dam has reached at about 10.6 km from the dam face which may result in blocking of tunnels. Tarbela delta was modeled from 1979 to 2060 using hec-6 model. Initially, the model was calibrated for year 1999 and validated for years 2000, 2001, 2002, and 2006 by involving the data of sediment concentration, reservoir cross sections (73 range lines), elevation-area capacity curves, and inflows and outflows from the reservoir. Then, the model was used to generate future scenarios, i.e., run-1, run-2, and run-3 with pool levels; 428, 442, and 457 m, respectively, till 2060. Results of run-1 and run-2 showed advancement to choke the tunnels by 2010 and 2030, respectively. Finally, in run-3, the advancement was further delayed showing that tunnels 1 and 2 will be choked by year 2050 and pivot point will reach at 6.4 km from the dam face.

Authentication of Smartphone Users Based on Activity Recognition and Mobile Sensing.

Smartphones are context-aware devices that provide a compelling platform for ubiquitous computing and assist users in accomplishing many of their routine tasks anytime and anywhere, such as sending and receiving emails. The nature of tasks conducted with these devices has evolved with the exponential increase in the sensing and computing capabilities of a smartphone. Due to the ease of use and convenience, many users tend to store their private data, such as personal identifiers and bank account details, on their smartphone. However, this sensitive data can be vulnerable if the device gets stolen or lost. A traditional approach for protecting this type of data on mobile devices is to authenticate users with mechanisms such as PINs, passwords, and fingerprint recognition. However, these techniques are vulnerable to user compliance and a plethora of attacks, such as smudge attacks. The work in this paper addresses these challenges by proposing a novel authentication framework, which is based on recognizing the behavioral traits of smartphone users using the embedded sensors of smartphone, such as Accelerometer, Gyroscope and Magnetometer. The proposed framework also provides a platform for carrying out multi-class smart user authentication, which provides different levels of access to a wide range of smartphone users. This work has been validated with a series of experiments, which demonstrate the effectiveness of the proposed framework.

Neural Correlates of Single- and Dual-Task Walking in the Real World.

Recent developments in mobile brain-body imaging (MoBI) technologies have enabled studies of human locomotion where subjects are able to move freely in more ecologically valid scenarios. In this study, MoBI was employed to describe the behavioral and neurophysiological aspects of three different commonly occurring walking conditions in healthy adults. The experimental conditions were self-paced walking, walking while conversing with a friend and lastly walking while texting with a smartphone. We hypothesized that gait performance would decrease with increased cognitive demands and that condition-specific neural activation would involve condition-specific brain areas. Gait kinematics and high density electroencephalography (EEG) were recorded whilst walking around a university campus. Conditions with dual tasks were accompanied by decreased gait performance. Walking while conversing was associated with an increase of theta (θ) and beta (ß) neural power in electrodes located over left-frontal and right parietal regions, whereas walking while texting was associated with a decrease of ß neural power in a cluster of electrodes over the frontal-premotor and sensorimotor cortices when compared to walking whilst conversing. In conclusion, the behavioral "signatures" of common real-life activities performed outside the laboratory environment were accompanied by differing frequency-specific neural "biomarkers". The current findings encourage the study of the neural biomarkers of disrupted gait control in neurologically impaired patients.

High-Frequency Intermuscular Coherence between Arm Muscles during Robot-Mediated Motor Adaptation.

Adaptation of arm reaching in a novel force field involves co-contraction of upper limb muscles, but it is not known how the co-ordination of multiple muscle activation is orchestrated. We have used intermuscular coherence (IMC) to test whether a coherent intermuscular coupling between muscle pairs is responsible for novel patterns of activation during adaptation of reaching in a force field. Subjects (N = 16) performed reaching trials during a null force field, then during a velocity-dependent force field and then again during a null force field. Reaching trajectory error increased during early adaptation to the force-field and subsequently decreased during later adaptation. Co-contraction in the majority of all possible muscle pairs also increased during early adaptation and decreased during later adaptation. In contrast, IMC increased during later adaptation and only in a subset of muscle pairs. IMC consistently occurred in frequencies between ~40-100 Hz and during the period of arm movement, suggesting that a coherent intermuscular coupling between those muscles contributing to adaptation enable a reduction in wasteful co-contraction and energetic cost during reaching.

Investigation of temporal change in glacial extent of Chitral watershed using Landsat data.

Glaciers are also known as solid reservoirs, and in this regard, Pakistan is a blessed country to have enriched glaciers. The change in glacial extent becomes very crucial for rivers whose discharges are associated with glacier melt. Even a little change in the glacial extent may bring a significant change in the resulting river flows. Considering climate change scenarios, many researchers have predicted future flows in such catchments. But in almost all such studies, the reduction in the glaciers is not normally based on any rational. Therefore, research is needed in order to estimate how glaciers are actually behaving under the change of temperature and precipitations to better estimate the future flows. For this purpose, Chitral watershed was considered as the study area. The seasonal change in the snow extent was estimated by using MODIS data for various years that helped to identify the month with minimum glacial extent. With the help of remote sensing, unsupervised classification was performed to estimate the glacier area in Chitral watershed. The results show a definite receding trend with respect to time in the glaciers of the region for the past decade.