Evading Musculoskeletal Conditions Using Qigong as a Rescue Technique.

Classically, Qigong is a Chinese technique that has been practiced in China for the past 3,000 years for healing the inner self. Qigong, wherein "Qi" means body energy and "Gong" denotes cultivation, regulates the energy flow in the body. The Qigong technique comprises a package of deep breathing training, gentle and rhythmic movement, and muscle-strengthening exercises that heal the body to activate one's internal soul energy. It has demonstrated its efficacy by inducing relaxation, building up stamina, strengthening immunity, appreciating muscle conditioning, and minimizing anxiety and depression. Furthermore, it has been beneficial in improving awareness of joint and movement senses. Specifically, Qigong brings healing by regulating energy flow in the whole-body systems. Moreover, it has exhibited a variety of regenerating effects by inducing emotional and mental relaxation. In today's world, Qigong exercises are being used for treating musculoskeletal disorders that are work- and stress-related by nature. Qigong is practiced globally as deep breathing exercises, and meditation is practiced for peace of mind and spirituality, whereas vigorous practice includes martial arts.

Understanding Female and Male Insights in Psychology: Who Thinks What?

Evolutionary psychology is the study of human psychological behavior. During childhood, men and women behave similarly; however, as a child approaches puberty, new physical and behavioral changes emerge. Behavioral psychology focuses on understanding the functioning and thought processes of the human mind. The general population lacks knowledge of basic behavioral differences between men and women, leaving them unaware of their role, limitations, societal responsibilities, resulting in an underestimation of their own natural talents and biology. Thus, people tend to follow societal norms rather than exploring and utilizing their natural talents. The current review was designed and conducted to enforce compression on behavioral psychology in both genders as well as to identify variations in hormonal activity and sexual preferences.

Highly efficient photonic radar by incorporating MDM-WDM and machine learning classifiers under adverse weather conditions.

Photonic radar, a cornerstone in the innovative applications of microwave photonics, emerges as a pivotal technology for future Intelligent Transportation Systems (ITS). Offering enhanced accuracy and reliability, it stands at the forefront of target detection and recognition across varying weather conditions. Recent advancements have concentrated on augmenting radar performance through high-speed, wide-band signal processing-a direct benefit of modern photonics' attributes such as EMI immunity, minimal transmission loss, and wide bandwidth. Our work introduces a cutting-edge photonic radar system that employs Frequency Modulated Continuous Wave (FMCW) signals, synergized with Mode Division and Wavelength Division Multiplexing (MDM-WDM). This fusion not only enhances target detection and recognition capabilities across diverse weather scenarios, including various intensities of fog and solar scintillations, but also demonstrates substantial resilience against solar noise. Furthermore, we have integrated machine learning techniques, including Decision Tree, Extremely Randomized Trees (ERT), and Random Forest classifiers, to substantially enhance target recognition accuracy. The results are telling: an accuracy of 91.51%, high sensitivity (91.47%), specificity (97.17%), and an F1 Score of 91.46%. These metrics underscore the efficacy of our approach in refining ITS radar systems, illustrating how advancements in microwave photonics can revolutionize traditional methodologies and systems.

Reconstruction of Partial Defect of Ear in a Tertiary Care Institute.

Auricle is the outward visible part of ear and composed of skin and cartilage. Auricle due to its standout and projected position is more vulnerable to get injured and cause distortion of the facial aesthetics. Reconstruction of the ear defect should be individualized depending on the defect size, location, nearby skin, patient requirement and surgeon experience. To present the results of various reconstructive options for partial ear defect which will aid in decision making among reconstructive options available. Reconstruction was individualized considering the defect size, depth, location, surrounding skin. In upper 1/3 defect reconstructive options include Antia-Buch chondrocutaneous advancement flap, autogenous cartilage with temporoparietal fascial flap, for middle 1/3 defect options include retroauricular soft tissue tube flap, diefenbach procedure, Autogenous cartilage graft and temporoparietal fascial flap, for lower 1/3 defect reconstructive options include pre auricular flap, triangular repair method, Zenteno Alanis technique. Reconstruction with various techniques results in aesthetically good outcomes. There is no major complication seen in any patient. Reconstruction of ear defect with various options available has good outcome. Planning is important part in reconstruction process. Reconstructive option chosen for a ear defect should be individualized depending on patient characteristics, surgeon experience.

Chest wall perforator flap partial breast reconstruction: a retrospective analysis of surgical, cosmetic and survival outcome.

Introduction: Oncoplastic breast surgery includes volume replacement as well as volume displacement. Autologous tissue is the preferred approach for volume replacement and includes chest wall perforator flaps (CWPF). Although described more than a decade ago, CWPFs have not been adopted widely in clinical practice till recently. We report the largest single-centre institutional data on CWPFs. Patients and methods: The study includes all patients who underwent breast conservation surgery (BCS) using CWPFs from January 2015 to December 2022. Data were retrieved from the institutional electronic record and Redcap database. The analysis was done using SPSS 23 and STATA 14. Results: 150 patients were included in the study. The mean age was 48.8 years (SD 10.4), and the body mass index was (26.6 kg/m2, SD 4.3). >50% of patients had breasts with small cup sizes (A&B) and mild ptosis (Non-ptotic and Grade 1 ptosis). 44.7% of patients underwent lateral intercostal artery perforator flap (LICAP), anterior intercostal artery perforator flap in 31.3%, lateral thoracic perforator flap (LTAP) in 12%, LICAP + LTAP in 11.3% and thoracodorsal artery perforator flap in 1%. Post-operatively, haematoma was seen in 1.3%, complete flap necrosis in 1.3%, seroma in 7%, wound dehiscence in 12%, and positive margin in 6.7%. 92 patients responded to the satisfaction assessment, of which >90% were happy with the surgical scars, comfortable going out in a public place, satisfied with the symmetry of the breast, and no one chose mastectomy in hindsight. The 5-year predicted disease free survival and overall survival were 86.4% and 94.7%, respectively. Conclusion: BCS with CWPF is an excellent option for reconstruction in small to medium-sized breasts. It is associated with minimal morbidity and comparable patient-reported cosmetic and survival outcomes.

Calcium signaling induces partial EMT and renal fibrosis in a Wnt4mCherry knock-in mouse model.

The renal tubular epithelial cells (TEC) have a strong capacity for repair after acute injury, but when this mechanism becomes uncontrollable, it leads to chronic kidney diseases (CKD). Indeed, in progress toward CKDs, the TECs may dedifferentiate, undergo epithelial-to-mesenchyme transition (EMT), and promote inflammation and fibrosis. Given the critical role of Wnt4 signaling in kidney ontogenesis, we addressed whether changes in this signaling are connected to renal inflammation and fibrosis by taking advantage of a knock-in Wnt4mCh/mCh mouse. While the Wnt4mCh/mCh embryos appeared normal, the corresponding mice, within one month, developed CKD-related phenotypes, such as pro-inflammatory responses including T-cell/macrophage influx, expression of fibrotic markers, and epithelial cell damage with a partial EMT. The Wnt signal transduction component ß-catenin remained unchanged, while calcium signaling is induced in the injured TECs involving Nfat and Tfeb transcription factors. We propose that the Wnt4 signaling pathway is involved in repairing the renal injury, and when the signal is overdriven, CKD is established.

Dengue dynamics: Prognostic and disease monitoring through molecular and serological profiling of clinical isolates.

BACKGROUND OBJECTIVES: Dengue fever is a mosquito-borne illness that affects millions of people worldwide every year. With no vaccination available, early detection and treatment is critical. One-hundred-twelve countries in the world pose a risk to travelers, particularly in metropolitan areas. Laboratory diagnoses vary according to objectives, resources, and schedule, with sensitivity and specificity must be balanced for effective testing. METHODS: The current work is a cross-sectional diagnostic study and samples from suspected patients of dengue was collected from May 15 to November 15 2023 and transported to laboratory, and RT-PCR and Dengue Duo Rapid test diagnosis techniques were used on 48 clinical samples included in this study. RESULTS: Blood was collected from suspected cases of dengue and subjected further to different molecular and serological parameters. Serum was separated from all 48 blood samples. RNA was isolated by silica column extraction method which is further utilized as a template for amplification and detection of dengue serotyping. Master Mix was prepared for the amplification and detection of dengue virus by Rotor-Gene Q Real-Time PCR Machine and further serological profiling of positive dengue cases was studied by conventional PCR. INTERPRETATION CONCLUSION: Our laboratory effectively standardized an RT-PCR-based approach for molecular identification of dengue virus in clinical specimens. This adaptive technique which used numerous primer sets displayed good specificity and sensitivity in serotype detection. The technology provides for quick and reliable identification of dengue virus infections, allowing for targeted treatment and preventative actions for successful disease management in highly populated regions.

Fine-tuning covalent organic frameworks for structure-activity correlation via adsorption and catalytic studies.

In applications utilizing Covalent Organic Frameworks (COFs) for adsorption, the interplay between crystallinity (vis-à-vis surface area) and active sites still remains ambiguous. To address this, the present study introduces three isoreticular COFs-COP-N18 (covalent organic polymer with short-range order), COF-N18 (COF having long-range order), and COF-N27 (semicrystalline COF with pyridyl heteroatoms)-to explore this duality. Through systematic variations in structural order, pore volume, and pore-wall nitrogen content, we aim to establish a structure-activity relationship (SAR) for these COFs via adsorption and catalysis, using CO2 and I2 as probes. Our investigation highlights the positive influence of crystallinity, surface area, and pore volume in adsorption as well as catalysis. However, the presence of heteroatoms manifests complex behavior in CO2 adsorption and CO2 cycloaddition reactions with epoxides. COF-N18 and COF-N27 showed comparable CO2 uptake capacities at different temperatures (273, 293, and 313 K) and ∼1 bar pressure. Additionally, CO2 cycloaddition reactions were performed with substrates possessing different polarities (epichlorohydrin, 1,2-epoxydodecane) to elucidate the role of COF surface polarity. Further investigation into iodine adsorption was performed to understand the impact of COF structural features on the modes of adsorption and adsorption kinetics. Improvements in COF-crystallinity results in faster average iodine uptake rate at 80% (K80% = 1.79 g/h) by COF-N18. Whereas, heteroatom doping slows down iodine adsorption kinetics (0.35 g/h) by prolonging the adsorption process up to 72 h. Overall, this study advances our understanding of COFs as adsorbents and catalysts, providing key insights into their SAR while emphasizing structural fine-tuning as a key factor for impactful environmental applications.

Identifying data-driven subtypes of major depressive disorder with electronic health records.

BACKGROUND: Efforts to reduce the heterogeneity of major depressive disorder (MDD) by identifying subtypes have not yet facilitated treatment personalization or investigation of biology, so novel approaches merit consideration. METHODS: We utilized electronic health records drawn from 2 academic medical centers and affiliated health systems in Massachusetts to identify data-driven subtypes of MDD, characterizing sociodemographic features, comorbid diagnoses, and treatment patterns. We applied Latent Dirichlet Allocation (LDA) to summarize diagnostic codes followed by agglomerative clustering to define patient subgroups. RESULTS: Among 136,371 patients (95,034 women [70 %]; 41,337 men [30 %]; mean [SD] age, 47.0 [14.0] years), the 15 putative MDD subtypes were characterized by comorbidities and distinct patterns in medication use. There was substantial variation in rates of selective serotonin reuptake inhibitor (SSRI) use (from a low of 62 % to a high of 78 %) and selective norepinephrine reuptake inhibitor (SNRI) use (from 4 % to 21 %). LIMITATIONS: Electronic health records lack reliable symptom-level data, so we cannot examine the extent to which subtypes might differ in clinical presentation or symptom dimensions. CONCLUSION: These data-driven subtypes, drawing on representative clinical cohorts, merit further investigation for their utility in identifying more homogeneous patient populations for basic as well as clinical investigation.

Synergistic Influence of Melatonin-Hydrocolloid Coating on Decay and Senescence of Nectarine (Prunus persica var. nucipersica) during Supermarket Storage Conditions.

Nectarines have remarkable nutritional value, low caloric content, and are rich in antioxidants. However, despite substantial local and global demand, their susceptibility to rapid spoilage during peak summer harvest is limited. To address this issue, the current study investigated the potential benefits of using melatonin (MLT), an antioxidant biomolecule, in combination with edible hydrocolloid coatings like carboxymethylcellulose (CMC) and gum Arabic (G.A.) on 'Snow Queen' nectarine fruits. The nectarines were treated with various combinations of coatings, including 1% and 1.5% CMC, 8% and 10% G.A., and 0.1 mM melatonin. These coated and non-coated samples were stored under standard supermarket conditions (18 ± 1 °C, 85-90% R.H.) for 16 days. The outcomes demonstrated that the most effective treatment was the combination of 1% CMC with 0.1 mM melatonin. This treatment significantly (p ≤ 0.05) reduced the rate of respiration, curbed fruit decay by approximately 95%, minimized weight loss by around 42%, and maintained approximately 39% higher levels of total phenol content and roughly 30% greater antioxidant (AOX) activity. These positive effects were accompanied by preserved firmness and overall quality attributes. Moreover, the treatment extended the shelf life to 16 days through retarding senescence and suppressing the activities of lipoxygenase (LOX) and pectin methylesterase (PME), all without compromising the functional qualities of the nectarine.

SARS-CoV-2 virulence factor ORF3a blocks lysosome function by modulating TBC1D5-dependent Rab7 GTPase cycle.

SARS-CoV-2, the causative agent of COVID-19, uses the host endolysosomal system for entry, replication, and egress. Previous studies have shown that the SARS-CoV-2 virulence factor ORF3a interacts with the lysosomal tethering factor HOPS complex and blocks HOPS-mediated late endosome and autophagosome fusion with lysosomes. Here, we report that SARS-CoV-2 infection leads to hyperactivation of the late endosomal and lysosomal small GTP-binding protein Rab7, which is dependent on ORF3a expression. We also observed Rab7 hyperactivation in naturally occurring ORF3a variants encoded by distinct SARS-CoV-2 variants. We found that ORF3a, in complex with Vps39, sequesters the Rab7 GAP TBC1D5 and displaces Rab7 from this complex. Thus, ORF3a disrupts the GTP hydrolysis cycle of Rab7, which is beneficial for viral production, whereas the Rab7 GDP-locked mutant strongly reduces viral replication. Hyperactivation of Rab7 in ORF3a-expressing cells impaired CI-M6PR retrieval from late endosomes to the trans-Golgi network, disrupting the biosynthetic transport of newly synthesized hydrolases to lysosomes. Furthermore, the tethering of the Rab7- and Arl8b-positive compartments was strikingly reduced upon ORF3a expression. As SARS-CoV-2 egress requires Arl8b, these findings suggest that ORF3a-mediated hyperactivation of Rab7 serves a multitude of functions, including blocking endolysosome formation, interrupting the transport of lysosomal hydrolases, and promoting viral egress.

Biodiesel production and exploring properties of Datura stramonium L. oil with its optimization using combined approaches-Taguchi, grey relational analysis, and response surface methodology.

Biodiesel production through the synthesis of Datura stramonium L. oil is studied to explore the most efficient approaches to suggest an alternate feedstock for biodiesel production. The main objective of this work is to optimize the process variables of biodiesel synthesis by using some statistical approach (Taguchi method, grey relational analysis (GRA), and response surface methodology (RSM) analyzing three parameters, i.e., alcohol-to-oil molar ratio, catalyst (NaOH) concentration, and process temperature for achieving maximum biodiesel derived from Datura stramonium L. oil. The transesterification process is applied by using an ultrasonic-assisted technique. Grey relational analysis (GRA) was successfully applied with the Taguchi method resulting in the optimum combination of A2B1C1. Based on the findings, the best operating conditions for transesterifying are attained with the RSM approach consisting of a 5.697:1 molar ratio (level 2), 0.3 (wt.%) NaOH concentration (level 1), and 70 °C process temperature (level 1). With a value of 87.02%, these ideal operating conditions produce the maximum yield as compared to grey relational analysis (GRA) yields 83.99%. The obtained results have been verified through the characterization of oil and biodiesel as well. Also, the fuel qualities of DSL biodiesel were identified and assessed. DSL oil was found 137.6 degrees of unsaturation during fatty acid profile analysis. DSL biodiesel was found the best kinematic viscosity (4.2 mm2/s) and acid value (0.49) when compared to Karanja and palm biodiesel. D. stramonium L. was recognized as a suitable species for biodiesel feedstock according to the findings.

Production of biodiesel from waste fish fat through ultrasound-assisted transesterification using petro-diesel as cosolvent and optimization of process parameters using response surface methodology.

Biodiesel is a highly promising and viable alternative to fossil-based diesel that also addresses the urgent need for effective waste management. It can be synthesized by the chemical modification of triglycerides sourced from vegetable origin, animal fat, or algal oil. The transesterification reaction is the preferred method of producing biodiesel. However, the non-miscibility of alcohol and oil layer causes excessive utilization of alcohol, catalyst, and a substantial reacting time and temperature. In the current investigation, transesterification of waste fish oil was performed with petro-diesel as cosolvent, under the influence of ultrasound energy. The combination of both techniques is a unique and efficient way to minimize the mass transfer limitations considerably and hence reduces the parameters of the reaction. It is also a sincere effort to comply with the principles of green chemistry. The optimum reaction conditions were obtained using response surface methodology (RSM) that were as follows: molar ratio of methanol to oil 9.09:1, catalyst concentration of 0.97 wt%, cosolvent concentration of 29.1 wt%, temperature 60.1℃, and a reacting time 30 min. Under these listed conditions, 98.1% biodiesel was achievable, which was in close agreement with the expected result. In addition, the cosolvent removal step from the crude biodiesel was also eliminated as it could be employed as a blended fuel in CI engines.

A programmable hybrid digital chemical information processor based on the Belousov-Zhabotinsky reaction.

The exponential growth of the power of modern digital computers is based upon the miniaturization of vast nanoscale arrays of electronic switches, but this will be eventually constrained by fabrication limits and power dissipation. Chemical processes have the potential to scale beyond these limits by performing computations through chemical reactions, yet the lack of well-defined programmability limits their scalability and performance. Here, we present a hybrid digitally programmable chemical array as a probabilistic computational machine that uses chemical oscillators using Belousov-Zhabotinsky reaction partitioned in interconnected cells as a computational substrate. This hybrid architecture performs efficient computation by distributing information between chemical and digital domains together with inbuilt error correction logic. The efficiency is gained by combining digital logic with probabilistic chemical logic based on nearest neighbour interactions and hysteresis effects. We demonstrated the computational capabilities of our hybrid processor by implementing one- and two-dimensional Chemical Cellular Automata demonstrating emergent dynamics of life-like entities called Chemits. Additionally, we demonstrate hybrid probabilistic logic as a viable logic for solving combinatorial optimization problems.

Hydroponics: Exploring innovative sustainable technologies and applications across crop production, with Emphasis on potato mini-tuber cultivation.

There is an urgent need to explore climate-resilient alternative agriculture production systems that focus on resilience, resource efficiency, and disease management. Hydroponics, a soilless cultivation system, gaining interest as it reduces the dependency on agricultural land, and pesticides, and can be implemented in areas with poor soil quality, thus mitigating the negative effects of extreme weather events. Potato is an essential dietary staple crop grown throughout the world and is a major source of food security in underdeveloped countries. However, due to the climatic changes, it is predicted that a significant loss in the suitability of land for potato production would occur, thus leading to potato yield loss. Recently, many case studies have emerged to highlight the advancement of agricultural hydroponic systems that provide a promising solution to the massive production of potato mini tuber at high efficiency. This review paper evaluates popular hydroponic methods and demonstrates how hydroponic has emerged as the go-to, long-term, sustainable answer to the perennial problem of insufficient access to high-quality potato seed stock. The paper discusses the research and innovation possibilities (such as artificial intelligence, nanoparticles, and plant growth-promoting rhizobacteria) that potentially increase tuber production per plant under optimal hydroponic growth circumstances. These approaches are examined considering new scientific discoveries and practical applications. Furthermore, it emphasizes that by enduring significant reforms in soilless food production systems (particularly for potatoes), the food supply of a rapidly growing population can be addressed. Since hydroponics systems are productive and easily automated without soil and optimal environmental conditions, future hydroponics farming is promising. In conclusion, the hydroponics system provides better yield and crop productivity by saving water, energy, and space. Henceforth, it can be the alternate choice for modern sustainable agriculture.

Explainable deep-neural-network supported scheme for tuberculosis detection from chest radiographs.

Chest radiographs are examined in typical clinical settings by competent physicians for tuberculosis diagnosis. However, this procedure is time consuming and subjective. Due to the growing usage of machine learning techniques in applied sciences, researchers have begun applying comparable concepts to medical diagnostics, such as tuberculosis screening. In the period of extremely deep neural nets which comprised of hundreds of convolution layers for feature extraction, we create a shallow-CNN for screening of TB condition from Chest X-rays so that the model is able to offer appropriate interpretation for right diagnosis. The suggested model consists of four convolution-maxpooling layers with various hyperparameters that were optimized for optimal performance using a Bayesian optimization technique. The model was reported with a peak classification accuracy, F1-score, sensitivity and specificity of 0.95. In addition, the receiver operating characteristic (ROC) curve for the proposed shallow-CNN showed a peak area under the curve value of 0.976. Moreover, we have employed class activation maps (CAM) and Local Interpretable Model-agnostic Explanations (LIME), explainer systems for assessing the transparency and explainability of the model in comparison to a state-of-the-art pre-trained neural net such as the DenseNet.

CIsense: an automated framework for early screening of cerebral infarction using PPG sensor data.

A cerebral infarction (CI), often known as a stroke, is a cognitive impairment in which a group of brain cells perishes from a lack of blood supply. The early prediction and evaluation of this problem are essential to avoid atrial fibrillation, heart valve disease, and other cardiac disorders. Different clinical strategies like Computerized tomography (CT) scans, Magnetic resonance imaging (MRI), and Carotid (ka-ROT-id) ultrasound are available to diagnose this problem. However, these methods are time-consuming and expensive. Wearable devices based on photoplethysmography (PPG) are gaining prevalence in diagnosing various cardiovascular diseases. This work uses the PPG signal to classify the CI subjects from the normal. We propose an automated framework and fiducial point-independent approach to predict CI with sufficient accuracy. The experiment is performed with a publicly available database having PPG and other physiological data of 219 individuals. The best validation and test accuracy of 91.8% and 91.3% are obtained after diagnosis with Coarse Gaussian SVM. The proposed work aims to extract cerebral infarction pathology by extracting relevant entropy features from higher order PPG derivatives for the prediction of CI and offers a simple, automated and inexpensive approach for early detection of CI and promotes awareness for the subjects to undergo further treatment to avoid major disorders.

Experimental Analysis for the Performance Assessment and Characteristics of Enhanced Magnesium Composites Reinforced with Nano-Sized Silicon Carbide Developed Using Powder Metallurgy.

Magnesium, which is lightweight and abundant by nature, was widely used in the 19th century to make parts for automobiles and airplanes. Due to their superior strength-to-weight ratios, magnesium alloys were favored for engineering applications over unadulterated magnesium. These alloys result from the combination of magnesium with various metals, including aluminum (Al), titanium (Ti), zinc (Zn), manganese (Mn), calcium (Ca), lithium (Li), and zirconium (Zr). In this study, an alloy of magnesium was created using the powder metallurgy (PM) technique, and its optimal performance was determined through the Taguchi-Gray (TG) analysis method. To enhance the alloy's mechanical properties, diverse weight fractions of silicon carbide (SiC) were introduced. The study primarily focused on the Mg-Zn-Cu-Mn alloy, achieving the optimal composition of Mg-3Zn-1Cu-0.7Mn (ZC-31). Subsequently, composites of ZC-31/SiC were produced via PM and the hot extrusion (HE) process, followed by the assessment of the mechanical properties under various strain rates. The use of silicon carbide (SiC) resulted in enhanced composite densities as a consequence of the increased density exhibited by SiC particles. In addition, the high-energy postsintering approach resulted in a decrease in porosity levels. By integrating silicon carbide (SiC) to boost the microhardness, as well as the ultimate compressive and tensile strength of the composite material, we can observe significant improvements in these mechanical properties. The experimental findings also demonstrated that an augmentation in the weight fraction of SiC and the strain rate led to enhanced ductility and a shift toward a more transcrystalline fracture behavior inside the composite material.