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Introduction: Diabetes distress is the emotional burden of diabetics and it may have a devastating impact on the health and well-being of people with diabetes. This study aims to estimate the prevalence of diabetes distress among adults with diabetes mellitus registered in the National Programme for Prevention and Control of Non-Communicable Diseases (NP-NCD) register in a rural area of West Bengal and to identify its distribution across different sociodemographic and treatment-related variables. Materials and Methods: This community-based descriptive, cross-sectional study was conducted in Barrackpore II block of North 24 Parganas district between July 2023 and September 2023. The study population consisted of diabetics registered under the NP-NCD register. The minimum required sample size of 155 was selected through a multistage sampling technique. Socioeconomic and sociodemographic data were collected using standardized questionnaire. Problem Areas in Diabetes questionnaire was used for assessing diabetes distress. Medication Adherence Report Scale questionnaire was used to check for medication adherence. Data were collected by house-to-house visits. Data were analyzed using jamovi (v2.4.8). Results: Out of the 142 participants, 52 (36.6%) had diabetes distress. Odds of diabetes distress were higher among

Denoising of interferograms is a vital step in the processing of synthetic aperture radar (InSAR) data. The primary goal is to filter the noise to the extent possible while retaining the fringes of the interferograms. Among the widely available classes of filters, the frequency-domain filters are still being used, owing to their robustness and generalizability to varying phase noise characteristics. This article deals with an enhancement to the well-known frequency-domain filter, i.e., the Goldstein filter, which is basically a phase filtering algorithm for interferometric products. The proposed extension to the Goldstein filter deals with deriving the tuning parameter based on the spatial frequency modes. This is achieved by using the mode-level characteristics rendered by the 2-D version of variational mode decomposition (2D-VMD) on the interferograms under test. The results of simulation and real interferogram data show that the proposed approach reduces the noise levels while minimizing the loss of signal.

The high precision (centimetre accuracy) positioning systems are set to play a key role in revolutionising smart farming, self-driving cars, drone deliveries, heavy machine navigation, etc. With so much at stake the technology also needs protection from an intentional sabotage or denial of service. It is very easy with current satellite-based navigation jammers to disrupt a navigation service. Our proposed technology solves this challenge in a compact and cost-effective way. Compared to normal navigation patch antennas our proposed dual ring antenna offers over 30 dB of protection. Thus, if a patch antenna-based navigation system is disturbed at 1 watt of interference power, it will take 1000 watts to disrupt navigation system working on our proposed system. With the size of only 130 mm × 130 mm and cheap large-scale manufacturing, our proposed antenna is perfectly suitable for applications for safety and prosperity of the smart nation-based living.

Smoking causes unalterable physiological abnormalities in the pulmonary system. This is emerging as a serious threat worldwide. Unlike spirometry, tidal breathing does not require subjects to undergo forceful breathing maneuvers and is progressing as a new direction towards pulmonary health assessment. The aim of the paper is to evaluate whether tidal breathing signatures can indicate deteriorating adult lung condition in an otherwise healthy person. If successful, such a system can be used as a pre-screening tool for all people before some of them need to undergo a thorough clinical checkup. This work presents a novel systematic approach to identify compromised pulmonary systems in smokers from acquired tidal breathing patterns. Tidal breathing patterns are acquired during restful breathing of adult participants. Thereafter, physiological attributes are extracted from the acquired tidal breathing signals. Finally, a unique classification approach of locally weighted learning with ridge regression (LWL-ridge) is implemented, which handles the subjective variations in tidal breathing data without performing feature normalization. The LWL-ridge classifier recognized compromised pulmonary systems in smokers with an average classification accuracy of 86.17% along with a sensitivity of 80% and a specificity of 92%. The implemented approach outperformed other variants of LWL as well as other standard classifiers and generated comparable results when applied on an external cohort. This end-to-end automated system is suitable for pre-screening people routinely for early detection of lung ailments as a preventive measure in an infrastructure-agnostic way.

Pulmonary ailments are conventionally diagnosed by spirometry. The complex forceful breathing maneuver as well as the extreme cost of spirometry renders it unsuitable in many situations. This work is aimed to facilitate an emerging direction of tidal breathing-based pulmonary evaluation by designing a novel, equitable, precise and portable device for acquisition and analysis of directional tidal breathing patterns, in real time. The proposed system primarily uses an in-house designed blow pipe, 40-kHz air-coupled ultrasound transreceivers, and a radio frequency (RF) phase-gain integrated circuit (IC). Moreover, in order to achieve high sensitivity in a cost-effective design philosophy, we have exploited the phase measurement technique, instead of selecting the contemporary time-of-flight (TOF) measurement; since application of the TOF principle in tidal breathing assessments requires sub-micro to nanosecond time resolution. This approach, which depends on accurate phase measurement, contributed to enhanced sensitivity using a simple electronics design. The developed system has been calibrated using a standard 3-L calibration syringe. The parameters of this system are validated against a standard spirometer, with maximum percentage error below 16%. Further, the extracted respiratory parameters related to tidal breathing have been found to be comparable with relevant prior works. The error in detecting respiration rate only is 3.9% compared to manual evaluation. These encouraging insights reveal the definite potential of our tidal breathing pattern (TBP) prototype for measuring tidal breathing parameters in order to extend the reach of affordable healthcare in rural regions and developing areas.