Miracle-dz/UniFAR-FTUs huggingface dataset:
Marker-based analysis of CMS lines for grain and kernel traits in rice hybrids

The grain size is considered to be one of the complex traits affecting rice yield as it is directed by multifaceted gene combinations. In the present experiment, 34 pollen parents were crossed with four female lines in line × tester matting design and 136 hybrids were generated. Wide phenotypic differences were observed across the hybrids for grain length, grain width and grain length-width ratio. The correlation analysis depicted a strong association among two grain size regulating traits viz., kernel length and kernel length-width ratio. However, kernel width shows negative correlation with these traits and influences the final grain size. The hybrids were also investigated at GS3 and GW8 loci. Gene based markers SF28 and DRR-GL showed strong association with the grain size related traits. The population structure analysis divided the entire material into four subgroups viz., I, II, III and IV with demarcation of long, homozygous and short grain types. The analysis of molecular variance (AMOVA) as well as a pairwise FST analysis indicated significant differentiation of population II as compared to rest of the populations, suggesting that only one among the four subgroups structured significantly different. Marker based evaluation in the present study provides the understanding for selection of suitable candidate markers for obtaining preferred grain shape/size and improving the grain yield through marker-assisted breeding. Bangladesh J. Bot. 51(2): 343-351, 2022 (June)
Finite Element Analysis and Near-Infrared Hyperspectral Reflectance Imaging for the Determination of Blueberry Bruise Grading

Bruising of the subcutaneous tissues of blueberries is an important form of mechanical damage. Different levels of bruising have a significant effect on the post-harvest marketing of blueberries. To distinguish different grades of blueberry bruises and explore the effects of different factors, explicit dynamic simulation and near-infrared hyperspectral reflectance imaging were employed without harming the blueberries in this study. Based on the results of the compression experiment, an explicit dynamic simulation of blueberries was performed to measure the potential locations of bruises and preliminarily divide the bruise stages. A near-infrared hyperspectral reflectance imaging system was used to detect the actual blueberry bruises. According to the blueberry photos taken by the near-infrared hyperspectral reflectance imaging system, the actual bruise rates of blueberries were obtained by using the Environment for Visualizing Images software for training and classification. Bruise grades of blueberries were divided accordingly. Response surface methodology was used to determine the effects of ripeness, loading speed and loading location on the blueberry bruising rate. Under the optimized parameters, the actual damage rate of blueberries was 1.1%. The results provide an important theoretical basis for the accurate and rapid identification and classification of blueberry bruise damage.
Parallel ILU Ordering and Convergence Relationships: Numerical Experiments

Abstract : We recently developed a parallel algorithm for computing ILU preconditioners, which was presented at Super Computing 1999. The algorithm has been shown to be highly scalable, in terms of execution time required for preconditioner factorization and application, for problems with up to 20 million unknowns running on up to 216 processors. However, since the algorithm reorders the matrix, and it is widely known that ordering can significantly affect convergence, questions were raised concerning the quality of the computed preconditioners. In this report we present experimental results demonstrating that the orderings imposed by the algorithm do not significantly degrade convergence, as long as the number of unknowns per subdomain is not too small. We report on two model problems, Poisson's equation, and a special case of the convection-diffusion equation, which other researchers have used for ordering and convergence studies. We show that convergence behavior is fairly flat as long as subdomains contain at least 512 nodes.
Effect of non-surgical periodontal therapy (NSPT) on salivary and serum levels of a disintegrin-like and metalloproteinase with thrombospondin-1 (ADAMTS-1)

Objectives: A Disintegrin -like and Metalloproteinase with Thrombospondin-1 (ADAMTS-1) is a protease with structure similar to Matrix metalloproteinase. ADAMTS-1 has role in wound healing, fibroblast migration, tissue modeling, vasculogenesis and development of neuronal system. The levels of ADAMTS-1 vary in periodontal health and disease. To evaluate the effect of Non-Surgical Periodontal Therapy (NSPT) on salivary and serum ADAMTS-1 levels in generalized periodontitis patients. Methodology: Forty-five subjects suffering from generalized periodontitis were selected and periodontal parameters were assessed using periodontal probing depth (PPD) and clinical attachment level (CAL). Salivary and serum ADAMTS-1 levels were assessed using enzyme-linked immunosorbent assay. NSPT was performed involving scaling and root planning, followed by oral hygiene instructions. The patients were recalled after three months, periodontal parameters and ADMATS-1 levels were analyzed. Pre- NSPT levels of periodontal parameters and ADAMTS-1 levels were compared with post NSPT. Descriptive statistics and paired t-test were applied to compare the variables. P-value < 0.05 was considered statistically significant. Results: Serum ADAMTS-1 levels pre NSPT was 119.45ng/L and elevated post NSPT to 143.43ng/L. The salivary ADAMTS-1 at baseline was 157.81 and post NSPT 161.53 ng/L and both the values were statistically significant post NSPT.
Control Aspects of Shape Memory Alloys in Robotics Applications: A Review over the Last Decade

This paper mainly focuses on various types of robots driven or actuated by shape memory alloy (SMA) element in the last decade which has created the potential functionality of SMA in robotics technology, that is classified and discussed. The wide spectrum of increasing use of SMA in the development of robotic systems is due to the increase in the knowledge of handling its functional characteristics such as large actuating force, shape memory effect, and super-elasticity features. These inherent characteristics of SMA can make robotic systems small, flexible, and soft with multi-functions to exhibit different types of moving mechanisms. This article comprehensively investigates three subsections on soft and flexible robots, driving or activating mechanisms, and artificial muscles. Each section provides an insight into literature arranged in chronological order and each piece of literature will be presented with details on its configuration, control, and application.
Prevalence and correlates of mental health difficulties amongst LGBTQ people in Southeast Asia: A systematic review

Abstract Introduction No study to date has reviewed the evidence base concerning prevalence and correlates of depression, anxiety, non-suicidal self-injury, and suicidality amongst LGBTQ people in Southeast Asia. Method We carried out a systematic review of quantitative articles (n = 25) identified through electronic databases. Result Heightened prevalence of mental health difficulties and minority stressors were found amongst Southeast Asian LGBTQ people which included significant effect size differences relative to cisgender and heterosexual people. Conclusion This review underscores the need for a more nuanced understanding of minority stressors and protective factors to inform mental health prevention efforts.
Assessment of the prevalence of Pseudomonas aeruginosa among Iraqi patients with acne and study of their antibiotic susceptibility patterns

Background: Pseudomonas aeruginosa is found in soil and water all over the world. It prefers moist areas, such as wash basins, toilets, and swimming pools that are insufficiently chlorinated, and expired and ineffective disinfection solutions. Pseudomonas aeruginosa infections range from external infections such as acne. A simple, severe, life-threatening disorder that is highly antibiotic-resistant. Aims: The current study was undertaken to analyze the frequency of P. aeruginosa as a microbial skin infection patient with acne and study their antibiotic sensitivity patterns due to a rise in instances of acne among young people in Iraq. Methods: A total of 61 samples were taken from inflamed and pus discharge patients,27 males and 34 females, with acne vulgaris on the face. Samples were cultured on selective, enrichment, and special media then incubated for 18-24 hr. at 37 °C. Bacterial Isolates Identification was done using different culture media, Microscopic Examination with Gram stain, in addition to Biochemical tests. In addition to API 20E identification system and conformation by VITEK 2 compact system. Antibiotic susceptibility test is done using different antibiotics. Results: Pseudomonas aeruginosa isolates were found in 23 (37.70%)/ 61 of the samples, with 11 (47.83%) male and 12 (52.17%) female.
New tight frames of curvelets and optimal representations of objects with piecewise C2 singularities

This paper introduces new tight frames of curvelets to address the problem of finding optimally sparse representations of objects with discontinuities along piecewise C2 edges. Conceptually, the curvelet transform is a multiscale pyramid with many directions and positions at each length scale, and needle‐shaped elements at fine scales. These elements have many useful geometric multiscale features that set them apart from classical multiscale representations such as wavelets. For instance, curvelets obey a parabolic scaling relation which says that at scale 2−j, each element has an envelope that is aligned along a “ridge” of length 2−j/2 and width 2−j.
Automatic adjustment of laparoscopic pose using deep reinforcement learning

Abstract. Laparoscopic arm and instrument arm control tasks are usually accomplished by an operative doctor. Because of intensive workload and long operative time, this method not only causes the operation not to be flow, but also increases operation risk. In this paper, we propose a method for automatic adjustment of laparoscopic pose based on vision and deep reinforcement learning. Firstly, based on the Deep Q Network framework, the raw laparoscopic image is taken as the only input to estimate the Q values corresponding to joint actions. Then, the surgical instrument pose information used to formulate reward functions is obtained through object-tracking and image-processing technology. Finally, a deep neural network adopted in the Q-value estimation consists of convolutional neural networks for feature extraction and fully connected layers for policy learning. The proposed method is validated in simulation. In different test scenarios, the laparoscopic arm can be well automatically adjusted so that surgical instruments with different postures are in the proper position of the field of view. Simulation results demonstrate the effectiveness of the method in learning the highly non-linear mapping between laparoscopic images and the optimal action policy of a laparoscopic arm.
Employment Psychology of Young Migrant Workers During Coronavirus Disease 2019: A Comparative Study Between Construction Workers and Food Delivery Knights

The employment psychology of young migrant workers in China has changed drastically in past decades. In particular, the construction industry has been facing labor shortages and aging workforces for years, and the eruption of coronavirus disease 2019 has exacerbated the problem. In contrast, the food delivery business has grown rapidly during the pandemic with a surge in the number of food delivery knights. It is vitally important to understand the employment psychology of the young migrant workers, the main component of the workforce for both industries. The presented study conducted a comparative analysis between construction workers and food delivery knights using data from face-to-face interviews, online social media, and World Value Survey. Results showed that the two groups of young migrant workers have different employment psychology during their job selection, construction workers cared more about income, and food delivery knights paid more attention to autonomy, working environment, and family.
Exercise: A Possibly Effective Way to Improve Vitamin D Nutritional Status

Vitamin D deficiency has become a widespread public health problem owing to its potential adverse health effects. Generally, the nutritional status of vitamin D depends on sunlight exposure and dietary or supplementary intake. However, recent studies have found that exercise can influence circulating 25(OH)D levels; although, the results have been inconclusive. In this review, we focused on the effect of exercise on circulating vitamin D metabolites and their possible mechanisms. We found that endurance exercise can significantly increase serum 25(OH)D levels in vitamin D-deficient people but has no significant effect on vitamin D-sufficient people. This benefit has not been observed with resistance training. Only chronic endurance exercise training can significantly increase serum 1,25(OH)2D, and the effect may be sex-dependent. Exercise may influence 25(OH)D levels in the circulation by regulating either the vitamin D metabolites stored in tissues or the utilization by target tissues. The effects of exercise on 25(OH)D levels in the circulation may be dependent on many factors, such as the vitamin D nutritional status, exercise type and intensity, and sex. Therefore, further research on the effects and mechanisms of exercise on vitamin D metabolites is required.
Analysis and Measurement of Noise Suppression in a Nonlinear Regenerative Amplifier

This paper analyzes the ability to suppress in-band noise power of a regenerative amplifier (RA) operating in the nonlinear regime in response to a continuous wave (CW) input tone. As opposed to the linear regime where a CW tone and the noise floor experience the same transfer function, it is shown that the non-linear saturation behavior of an RA yields different transfer characteristics between a CW tone and noise, ultimately leading to an improvement in the output carrier-to-noise ratio (CNR). This is all thanks to the high gain, narrow bandwidth, and the compressive third-order nonlinearity of the RA. This non-linear noise suppression is first analyzed mathematically using single tones in the frequency domain to represent the signal and the noise. Then, simulation of an RA circuit model is shown to be in excellent agreement with the analytical results. Lastly, a discrete RA has been implemented to experimentally verify the noise-suppression phenomenon. The measurement results clearly demonstrate noise suppression and show an output CNR improvement of up to 3 dB. Potential applications of the RA with noise suppression are also discussed.
Effect of supercritical CO2 on limestone's pore structure based on NMR and SEM

Abstract Supercritical CO2 (SC-CO2), as a new type of energizing fluid, has been widely applied in fracturing and acidizing treatment on tight sandstone, shale and carbonate formation. However, the effect of SC-CO2 on limestone's pore structure is unclear. To explore the effect, SC-CO2 reactor featuring high-temperature and high-pressure was used to carry out soaking experiments of SC-CO2-brine-limestone and SC-CO2-limestone respectively. With the help of NMR and SEM, this paper studies the effect of SC-CO2 on limestone's pore structure when the soaking time is different. It is found that in the experiment of SC-CO2-brine-limestone, SC-CO2 will react with brine to produce carbonic acid, which would react with calcite to augment limestone's porosity and permeability. Yet at the same time, Ca2+ and Mg2+ in the brine deposit continuously, which would lessen limestone's porosity and permeability. Besides, it is the generation of large pores that leads to augmentation of porosity, and more large pores are produced as time increases. While in the experiment of SC-CO2-limestone, volume expansion caused by transforming SC-CO2 into gaseous CO2 also augments limestone's porosity, and the augmentation is due to small pores. However, the increase of porosity in experiments without brine is much lower than that with brine.
The Effects of a Digital Well-being Intervention on Older Adults: Retrospective Analysis of Real-world User Data

Background Digital interventions have been shown to be effective for a variety of mental health disorders and problems. However, few studies have examined the effects of digital interventions in older adults; therefore, little is known about how older adults engage with or benefit from these interventions. Given that adoption rates for technology among people aged ≥65 years remain substantially lower than in the general population and that approximately 20% of older adults are affected by mental health disorders, research exploring whether older adults will use and benefit from digital interventions is needed. Objective This study aimed to examine the extent to which older adults engaged with a digital well-being intervention (Happify) and whether engaging with this program led to improvements in both subjective well-being and anxiety symptoms. Methods In this retrospective analysis, we analyzed data from 375 real-world Happify users aged ≥65 years who signed up for the platform between January 1, 2019, and December 23, 2021. Changes in well-being and anxiety symptoms across 42 to 182 days were assessed using responses to the in-app assessment, which users were prompted to take every 2 weeks, and were compared among users who engaged with the program at the recommended level (ie, 2 or more activities per week) or below the recommended level. Results In all, 30% (113/375) of the sample engaged with the platform at the recommended level (ie, completed an average of 2 or more activities per week), and overall, users completed an average of 43.35 (SD 87.80) activities, ranging from 1 to 786, between their first and last assessment. Users were also active on the platform for an average of 19.36 (SD 27.16) days, ranging from 1 to 152 days. Moreover, older adults who engaged at the recommended level experienced significantly greater improvements in subjective well-being (P=.002) and anxiety symptoms (P<.001) relative to those who completed fewer activities. Conclusions These data provide preliminary evidence that older adults engage with and benefit from digital well-being interventions. We believe that these findings highlight the importance of considering older adult populations in digital health research. More research is needed to understand potential barriers to using digital interventions among older adults and whether digital interventions should be modified to account for this population’s particular needs (eg, ensuring that the intervention is accessible using a variety of devices). However, these results are an important step in demonstrating the feasibility of such interventions in a population that is assumed to be less inclined toward digital approaches.
XBO Model: a Useful Method for Optimizing the Efficiency of Life Insurance Companies

: A life insurance policy can pay off any debt one left behind, which will put a burden on the family. Debts such as mortgages, credit cards, car loans, and even the funeral expenses can have a significant impact on one's family and their lifestyle. In a one-click shopping world with on-demand everything, only 40% of US household own individual life insurance due to the antiquated application process from life insurance companies. Customers need to provide extensive information for identification of risk classification and eligibility, which includes scheduling medical exams, a process that takes an average of 30 days. Gradually, customers tend to fall off. Here we propose an approach named ‘XGBoost Based on Offset' estimator to solve such a problem. XBO is a predictive model that accurately classifies customer's level using a more automated approach. With technology frameworks and the application of mathematical statistics, we show that XBO estimator makes the identification quicker and less labour-intensive for new and existing customers while maintaining privacy boundaries. By automatically separating clients to eight ranks, this model can facilitate the pricing process of life insurance policy and can make a difference for the life insurance companies' risk management.
Audit committee, external audit and accounting conservatism: Does company’s growth matter?

The objective of this analysis is to examine the joint effect of the audit committee and external audit on conservatism accounting and how a company’s rate of growth influences these relationships. The sample used in this study comprises all non-financial listed Portuguese firms from 2005 to 2017. A fixed-effects regression is performed to examine the association between the audit committee and external audit and conservatism accounting and how the company’s rate of growth influences these relationships. Using an accruals-based proxy to compute accounting conservatism, this study indicates that companies audited by Big 4 audit firms report more conservative accounting than firms audited by non-Big 4 audit firms and that audit committee and external auditors together appear to increase accounting conservatism. Additionally, the findings suggest that the degree of conservatism reduction related to more growth is diminished when the companies are examined by a Big 4 auditor and the board of directors have an audit committee. The findings based on this study offer valuable data to investors and regulators in assessing the effect of the audit committee and external audit on the quality of earnings.
STUDY OF EFFECT OF DIFFERENT PARAMETERS ON BEARING CAPACITY OF SOIL

Soil is considered by the engineer as a complex material produced by weathering of the solid rock. Soil is the most important material which is in use for construction of civil engineering structures. Amongst all parameters, the bearing capacity of soil to support the load coming over its unit area is very Important. There are various methods for calculation of bearing capacity of soil put forth by scientists like Prandtl, Terzaghi, Meyerhoff, Hansen, Vesic and others. Principal factors that Influence ultimate bearing capacities are type of soil, width of foundation, soil weight in shear zone and surcharge. Structural rigidity and the contact stress distribution do not greatly influence bearing capacity. Bearing capacity analysis assumes a uniform contact pressure between the foundation and underlying soil. With other factors unchanged the type of failure of soil, depth of foundation, and effect of water table also governs the bearing capacity of soil. The present paper deals with the study of effect of shape of footing on bearing capacity of soil. Similarly the effect of depth of footing on bearing capacity of soil is studied. In general, other factors remaining constant, bearing capacity of soil goes on increasing as depth or width of foundation increases. The comparison of bearing capacity of soil with methods of analysis given by Terzaghi and IS code method is carried out for different shapes i.e. strip, square, circular and rectangle. In case of local shear failure, amongst different shapes of footing the bearing capacity of strip footing is found to be lowest in comparison with square, circular and rectangular shaped footings.