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Skeletal dysplasias are a heterogeneous group of disorders presenting mild to lethal defects. Several factors, such as genetic, prenatal, and postnatal environmental may contribute to reduced growth. Fourteen families of Pakistani origin, presenting the syndromic form of short stature either in the autosomal recessive or autosomal dominant manner were clinically and genetically investigated to uncover the underlying genetic etiology. Homozygosity mapping, whole exome sequencing, and Sanger sequencing were used to search for the disease‐causing gene variants. In total, we have identified 13 sequence variants in 10 different genes. The variants in the HSPG2 and XRCC4 genes were not reported previously in the Pakistani population. This study will expand the mutation spectrum of the identified genes and will help in improved diagnosis of the syndromic form of short stature in the local population. [ABSTRACT FROM AUTHOR]

The gelatinization and retrogradation characteristics of wheat starch affect the eating quality of Chinese-style food. Rapid Visco Analyzer (RVA) parameters have been widely used as important indicators to evaluate and improve the quality of wheat starch. However, the genetic basis of RVA parameters remains to be further explored. In the present study, a natural population was genotyped using 90K single nucleotide polymorphism (SNP) arrays, and the RVA parameters of this population grown in five environments were evaluated. The results showed that 22,068 high-quality SNP markers were identified and distributed unequally on the chromosomes. According to the genetic distance, 214 wheat materials were divided into four groups. Except for the pasting temperature (PTT), six parameters followed a normal distribution. Based on the general linear model, 969 significant association SNPs were detected by genome-wide association studies (GWAS), and chromosomes 7A and 2B had the most associated SNPs. Breakdown viscosity (BV) was associated with the most SNPs (n = 238), followed by PTT (n = 186), peak viscosity (PV; n = 156), trough viscosity (TV; n = 127), and final viscosity (FV; n = 126). According to the average linkage disequilibrium (LD), 33 stable quantitative trait loci (QTLs) were identified for single parameters in multiple environments, of which 12 were associated with BV, followed by peak time (PT; n = 8) and PTT (n = 7). On the other hand, 67 pleiotropic QTLs were identified for multiple parameters. Three candidate genes--TasbeIIa, TasbeI, and TassIIa--were screened for phenotyping analysis. The grain width and the weight of the TasbeIIa and TaSSIIa knockout (KO) lines were significantly lower than those of the TasbeI KO lines and the control (CK). The KO lines had smaller endosperm cells, smaller A-type starch granules, and higher amylose content. The TasbeI KO lines showed normal RVA curves, while the TasbeIIa KO lines showed flat curves. However, the TaSSIIa lines failed to paste under the RVA temperatures. Conclusively, the SNPs/QTLs significantly associated with the RVA parameters and genetic resources with novel haplotypes could be used to improve the quality of wheat starch. [ABSTRACT FROM AUTHOR]

Introduction: Early studies exploring the physiological effects of space travel have indicated the body's capacity for reversible adaptation. However, the impact of long‐duration spaceflight, exceeding 6 months, presents more intricate challenges. Effects on the Cardiovascular (CV) System: Extended exposure to microgravity and radiation profoundly affects the CV system. Notable phenomena include fluid shifts toward the head and modified arterial pressure. These changes disrupt blood pressure regulation and elevate cardiac output. Additionally, the loss of venous compression leads to a reduction in central venous pressure. Fluid and Plasma Volume Changes: The displacement of fluid from the vascular system to the interstitium, driven by baroreceptor stimulation, results in a 10%–15% decline in plasma volume. Cardiac Muscle and Hematocrit Variations: Intriguingly, despite potential increases in cardiac workload, cardiac muscle atrophy and perplexing variations in hematocrit levels have been observed. The mechanism underlying atrophy appears to involve a shift in protein synthesis from the endoplasmic reticulum to the mitochondria via mortalin‐mediated mechanisms. Arrhythmias and QT Interval Prolongation: Instances of arrhythmias have been recurrently documented, although generally nonlethal, in both Russian and American space missions. Long‐duration spaceflight has been associated with the prolongation of the QT interval, particularly in extended missions. Radiation Effects: Exposure of the heart to the proton and heavy ion radiation pervasive in deep space contributes to coronary artery degeneration, augmented aortic stiffness, and carotid intima thickening through collagen‐mediated processes. Moreover, it accelerates the onset of atherosclerosis and triggers proinflammatory responses. Reentry and Postflight Challenges: Upon reentry, astronauts frequently experience orthostatic intolerance and altered sympathetic responses, which bear potential hazards in scenarios requiring rapid mobilization or evacuation. Conclusion: Consequently, careful monitoring of these cardiac risks is imperative for forthcoming missions. While early studies illuminate the adaptability of the body to space travel's challenges, the intricacies of long‐duration missions and their effects on the CV system necessitate continued investigation and vigilance to ensure astronaut health and mission success. [ABSTRACT FROM AUTHOR]

Coronavirus disease (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. COVID-19 become an active epidemic disease due to its spread around the globe. The main causes of the spread are through interaction and transmission of the droplets through coughing and sneezing. The spread can be minimized by isolating the susceptible patients. However, it necessitates remote monitoring to check the breathing issues of the patient remotely to minimize the interactions for spread minimization. Thus, in this article, we offer a wearable-IoTs-centered framework for remote monitoring and recognition of the breathing pattern and abnormal breath detection for timely providing the proper oxygen level required. We propose wearable sensors accelerometer and gyroscope-based breathing time-series data acquisition, temporal features extraction, and machine learning algorithms for pattern detection and abnormality identification. The sensors provide the data through Bluetooth and receive it at the server for further processing and recognition. We collect the six breathing patterns from the twenty subjects and each pattern is recorded for about five minutes. We match prediction accuracies of all machine learning models under study (i.e. Random forest, Gradient boosting tree, Decision tree, and K-nearest neighbor. Our results show that normal breathing and Bradypnea are the most correctly recognized breathing patterns. However, in some cases, algorithm recognizes kussmaul well also. Collectively, the classification outcomes of Random Forest and Gradient Boost Trees are better than the other two algorithms. [ABSTRACT FROM AUTHOR]

Foliar application of nitrogen and zinc has proven beneficial to achieve high yield and growth of wheat. A field trial was conducted with Randomized Complete Block Design (RCBD) in three replications, at Student's Experiment Farm, Department of Agronomy, Sindh Agriculture University, Tandojam during spring 2022-2023. The study explored the effect of foliar application of nitrogen (N) and zinc (Zn) on wheat (Triticum sativum L.) variety TD-1 on different growth stages. The treatment comprised T1 = Control, T2 = 2.0% N (tillering), T3 = 2.0% N (booting), T4 = 0.1% Zn (tillering), T5 = 0.1% Zn (booting), T6 = 2.0% N + 0.1% Zn (tillering), and T7 = 2.0% N + 0.1% Zn (booting). The results revealed that all the parameters were significantly affected (p <0.05) by foliar applications of N and Zn at both tillering and booting stages. The highest growth and yield traits were recorded when the plants were treated with 2.0 % N + 0.1% Zn applied (foliar) at tillering stage. However, the plants grown under control conditions exhibited lower performance for all the traits recorded. In conclusion, the interaction of 2.0% N + 0.1% Zn with foliar spray demonstrated positive response towards wheat variety TD-1 at tillering stage as compared to other treatments. Hence, the combined strategy of applying foliar nitrogen and zinc at tillering stage is recommended to get higher grain yields and plant growth for chaff production. [ABSTRACT FROM AUTHOR]

A time cartogram visualizes travelling-times between locations. It replaces the geographic distance by time distance and distorts the underlyingmap accordingly. By distorting themap, time cartogramsmay give a more intuitive and clear picture of travelling-times. The distortion of the map, however, can make time cartograms harder to recognize and use. Although cartograms are becoming widespread in use, very little is known about their usability. This study focuses on the usability of centered time cartograms: time cartograms that visualize travellingtimes from a fixed starting location to other destinations in a region. We created several centered time cartograms to answer spatio-temporal questions related to the Dutch railway network. Two experiments were performed: a laboratory test and an online survey. In the laboratory test, we used eye-tracking, thinking aloud, and video-recording to compare four different designs of centered time cartograms to find out which one (or combination) of these performs better in answering spatiotemporal questions and thus, to establish a favorable design strategy for these cartograms. In the online survey, centered time cartograms were evaluated against a geographic and schematic map for accuracy, response time, and preference. The first experiment suggested that among various designs, the centered time cartogram with emphasized railroads is the most preferred design and the centered time cartogram without railroads is the least preferred. The second experiment indicated that overall, centered time cartograms perform better than the two other solutions in performing spatio-temporal tasks, particularly when the task has a dominant time-related component.

The 4.0 industry revolution and the prevailing technological advancements have made industrial units more intricate. These complex electro-mechanical units now aim to improve efficiency and increase reliability. Downtime of such essential units in the current competitive age is unaffordable. The paradigm of fault diagnostics is being shifted from conventional to proactive predictive approaches. As a result, Condition-based Monitoring and prognostics are now essential components of complex industrial systems. This research is focused on developing a fault prognostic system using Long Short-Term Memory for rolling element bearings because they are a critical component of industrial systems and have one of the highest fault frequencies. Compared to other research, feature engineering is minimized by using raw time series sensor data as an input to the model. Our model achieved the lowest root mean square error and outperformed similar research models where time domain, frequency domain, or time-frequency domain features were used as input to the model. Furthermore, using raw vibration data also enabled better generalization of the model. This has been confirmed by evaluating the performance of the developed model against vibration data generated by distinct sources, including hydro and wind power turbines. [ABSTRACT FROM AUTHOR]