Miracle-dz/UniFAR-FTUs huggingface dataset:
Perinatal health predictors using artificial intelligence: A review

Advances in public health and medical care have enabled better pregnancy and birth outcomes. The rates of perinatal health indicators such as maternal mortality and morbidity; fetal, neonatal, and infant mortality; low birthweight; and preterm birth have reduced over time. However, they are still a public health concern, and considerable disparities exist within and between countries. For perinatal researchers who are engaged in unraveling the tangled web of causation for maternal and child health outcomes and for clinicians involved in the care of pregnant women and infants, artificial intelligence offers novel approaches to prediction modeling, diagnosis, early detection, and monitoring in perinatal health. Machine learning, a commonly used artificial intelligence method, has been used to predict preterm birth, birthweight, preeclampsia, mortality, hypertensive disorders, and postpartum depression. Real-time electronic health recording and predictive modeling using artificial intelligence have found early success in fetal monitoring and monitoring of women with gestational diabetes especially in low-resource settings. Artificial intelligence–based methodologies have the potential to improve prenatal diagnosis of birth defects and outcomes in assisted reproductive technology too. In this scenario, we envision artificial intelligence for perinatal research to be based on three goals: (1) availability of population-representative, routine clinical data (rich multimodal data of large sample size) for perinatal research; (2) modification and application of current state-of-the-art artificial intelligence for prediction and classification in health care research to the field of perinatal health; and (3) development of methods for explaining the decision-making processes of artificial intelligence models for perinatal health indicators. Achieving these three goals via a multidisciplinary approach to the development of artificial intelligence tools will enable trust in these tools and advance research, clinical practice, and policies to ensure optimal perinatal health.
CellSense

Data from the cellular network have been proved as one of the most promising way to understand large-scale human mobility for various ubiquitous computing applications due to the high penetration of cellphones and low collection cost. Existing mobility models driven by cellular network data suffer from sparse spatial-temporal observations because user locations are recorded with cellphone activities, e.g., calls, text, or internet access. In this paper, we design a human mobility recovery system called CellSense to take the sparse cellular billing data (CBR) as input and outputs dense continuous records to recover the sensing gap when using cellular networks as sensing systems to sense the human mobility. There is limited work on this kind of recovery systems at large scale because even though it is straightforward to design a recovery system based on regression models, it is very challenging to evaluate these models at large scale due to the lack of the ground truth data. In this paper, we explore a new opportunity based on the upgrade of cellular infrastructures to obtain cellular network signaling data as the ground truth data, which log the interaction between cellphones and cellular towers at signal levels (e.g., attaching, detaching, paging) even without billable activities. Based on the signaling data, we design a system CellSense for human mobility recovery by integrating collective mobility patterns with individual mobility modeling, which achieves the 35.3% improvement over the state-of-the-art models. The key application of our recovery model is to take regular sparse CBR data that a researcher already has, and to recover the missing data due to sensing gaps of CBR data to produce a dense cellular data for them to train a machine learning model for their use cases, e.g., next location prediction.
Technetium Stabilization in Low-Solubility Sulfide Phases: A Review

Technetium contamination remains a major environmental problem at nuclear reprocessing sites, e.g., the Hanford Site, Washington, USA. At these sites, Tc is present in liquid waste destined for immobilization in a waste form or has been released into the subsurface environment. The high environmental risk associated with Tc is due to its long half-life (214 000 years) and the mobility of the oxidized anionic species Tc(VII)O4–. Under reducing conditions, TcO4– is readily reduced to Tc(IV), which commonly exists as a relatively insoluble and therefore immobile, hydrous Tc-oxide (TcO2·nH2O). The stability of Tc(IV) sequestered as solid phases depends on the solubility of the solid and susceptibility to reoxidation to TcO4–, which in turn depend on the (biogeo)chemical conditions of the environment and/or nuclear waste streams. Unfortunately, the solubility of crystalline TcO2 or amorphous TcO2·H2O is still above the maximum contaminant level (MCL) established by the U.S. EPA (900 pCi/L), and the kinetics of.
Protective Effects of Caesalpinia sappan Linn. and Its Bioactive Compounds on Cardiovascular Organs

Cardiovascular diseases are the leading cause of death worldwide. The long-term aim of cardiovascular disease therapy is to reduce the mortality rate and decelerate the progression of cardiovascular organ damage. Current therapies focus on recovering heart function and reducing risk factors such as hyperglycemia and dyslipidemia. However, oxidative stress and inflammation are important causes of further damage to cardiovascular organs. Caesalpinia sappan Linn. (Fabaceae), a flowering tree native to tropical Asia, has antioxidant and anti-inflammatory properties. It is used as a natural dye to color food and beverages and as a traditional treatment for diarrhea, diabetes, and blood stasis. The phytochemical compounds in C. sappan, mainly the homoisoflavonoids brazilin, sappanone A, protosappanin, and hematoxylin, can potentially be used to protect cardiovascular organs. This review aims to provide updates on recent developments in research on C. sappan in relation to treatment of cardiovascular diseases. Many studies have reported protective effects of the plant’s bioactive compounds that reduce cardiac damage and enhance vasorelaxation. For example, brazilin and sappanone A have an impact on molecular and cellular changes in cardiovascular disease pathogenesis, mainly by modulating oxidative, inflammatory, and apoptotic signaling pathways. Therefore, bioactive compounds of C. sappan have the potential to be developed as therapeutic agents to combat cardiovascular diseases like myocardial infarction and vascular disease. This review could help further the understanding of the possible modulatory role of the compounds in cardiovascular diseases, thereby facilitating future studies.
Building‐up fit muscles for the future

‘Special issue ‐ In Utero and Early Life Programming of Aging and Disease’. Skeletal muscle (SM) adaptations to physical exercise (PE) have been extensively studied due, not only to the relevance of its in situ plasticity, but also to the SM endocrine‐like effects in noncontractile tissues, such as brain, liver or adipocytes. Regular PE has been considered a pleiotropic nonpharmacological strategy to prevent and counteract the deleterious consequences of several metabolic, cardiovascular, oncological and neurodegenerative disorders. Additionally, PE performed by parents seems to have a direct impact in the offspring through the transgenerational programming of different tissues, such as SM. In fact, SM offspring programming mechanisms seems to be orchestrated, at least in part, by epigenetic machinery conditioning transcriptional or post‐transcriptional processes. Ultimately, PE performed in the early in life is also a critical window of opportunity to positively modulate the juvenile and adult phenotype. Parental PE has a positive impact in several health‐related offspring outcomes, such as SM metabolism, differentiation, morphology and ultimately in offspring exercise volition and endurance. Also, early‐life PE counteracts conceptional‐related adverse effects and induces long‐lasting healthy benefits throughout adulthood. Additionally, epigenetics mechanisms seem to play a key role in the PE‐induced SM adaptations. Despite the undoubtedly positive role of parental and early‐life PE on SM phenotype, a strong research effort is still needed to better understand the mechanisms that positively regulate PE‐induced SM programming.
A survey of cloud network fault diagnostic systems and tools

Recently, cloud computing has become a vital part that supports people’s normal lives and production. However, accompanied by the increasing complexity of the cloud network, failures constantly keep coming up and cause huge economic losses. Thus, to guarantee the cloud network performance and prevent execrable effects caused by failures, cloud network diagnostics has become of great interest for cloud service providers. Due to the characteristics of cloud network (e.g., virtualization and multi-tenancy), transplanting traditional network diagnostic tools to the cloud network face several difficulties. Additionally, many existing tools cannot solve problems in the cloud network. In this paper, we summarize and classify the state-of-the-art technologies of cloud diagnostics which can be used in the production cloud network according to their features. Moreover, we analyze the differences between cloud network diagnostics and traditional network diagnostics based on the characteristics of the cloud network. Considering the operation requirements of the cloud network, we propose the points that should be cared about when designing a cloud network diagnostic tool. Also, we discuss the challenges that cloud network diagnostics will face in future development.
Intelligent Recognition Method of Vehicle Path with Time Window Based on Genetic Algorithm

Based on particle filter and improved cuckoo genetic algorithm, an algorithm for intelligent vehicle path recognition with a time window is designed. Particle filter (PF) is an influential visual tracking tool; it relies on the Monte Carlo Chain framework and Bayesian probability, which are essential for intelligent monitoring systems. The algorithm first uses particle filters for visual tracking and then obtains the current operating environment of the vehicle, then performs cluster analysis on customer locations, and finally performs path recognition in each area. The algorithm not only introduces particle filters, which are advanced visual tracking, but also improves the cuckoo search algorithm; when the bird’s egg is found by the bird’s nest owner, it needs to randomly change the position of the entire bird’s nest, which speeds up the search speed of the optimal delivery route. Analyze and compare the hybrid intelligent algorithm and the cuckoo search algorithm. Finally, the international standard test set Benchmark Problems is used for testing. The experimental outcomes indicated that the new hybrid intelligent approach is an effective algorithm for handling vehicle routing tasks with time windows.
OTT_A_242567 4767..4778

*These authors contributed equally to this work Introduction: Bufalin is a component of Chinese traditional medicine, Chansu, which is reported to induce cell death among various kinds of tumors. Apoptosis evasion is a common problem of cancer treatment. Materials and Methods: The proliferation of U-87 and U-373 treated by bufalin combined with or without apoptosis inhibitor was detected by MTT assay. The protein levels related to apoptosis and necroptosis were measured by Western blotting. Immunoprecipitation (IP) was applied for monitoring the formation of necrosome. The gene knockdown by CRISPR/Cas9 was applied to determine the roles of the proteins in apoptosis and necroptosis. Results: In this study, we found that bufalin could induce apoptosis or necroptosis when U-87 and U-373 escaped from apoptosis. Bufalin triggered cell death by upregulating tumor necrosis factor (TNF) -α, TNF receptor 1 (TNFR1) and receptor-interacting protein 1 (RIPK1). Antagonizing cellular inhibitor of apoptosis 1 (cIAP1) and cIAP2 were also contributory. Caspase-8 activation led to apoptosis. When caspase-8 was functionally lost, necrosome consisted of RIPK1, receptor-interacting protein 3 (RIPK3) and mixed lineage kinase domain-like protein (MLKL) formed and necroptosis happened. The knockdown of above genes or the drug treatment confirmed the mechanism of bufalininduced cell death. Cytotoxicity of bufalin to caspase-8 knockdown cell lines made control cell lines more sensitive to bufalin in their mixture. Discussion: The cytotoxicity of bufalin to U-87 and U-373 was by inducing apoptosis or necroptosis when they were sensitive to apoptosis or not. The results indicated that seeking for treatments that could induce apoptosis and necroptosis was a good solution for the tumor evasion of apoptosis.
KEY BASED SECURE FILE ENCRYPTION IN CLOUD

-------------------------------------------------------------------------------------------------------------------------------------------------- Abstract -Cloud storage is associate degree application of cloud that liberates organizations from establishing in-house knowledge storage systems. However, cloud storage provides rise to security considerations. Just in case of group-shared knowledge, the info faced are cloud specific and traditional business executive threats. Secure knowledge sharing among a gaggle that counters business executive threats of legitimate nevertheless malicious users is a vital analysis issue. We have a tendency to propose a replacement system within which the information are shared to the individual user a lot of firmly through secret writing. The one info is maintained for the individual user for a lot of security. We have a tendency to produce a neighborhood server during this system that contains user key for secret writing purpose. The documents to be shared are kept as an encrypted format and keep within the cloud info. We have a tendency to produce native server for maintaining the users key a lot of firmly. Therefore, we have a tendency to stopping the key to be shared globally.
A heuristic for statistical seriation

We study the statistical seriation problem, where the goal is to estimate a matrix whose rows satisfy the same shape constraint after a permutation of the columns. This is a important classical problem, with close connections to statistical literature in permutation-based models and also has wide applications ranging from archaeology to biology. Speciﬁcally, we consider the case where the rows are monotonically increasing after an unknown per-mutation of the columns. Past work has shown that the least-squares estimator is optimal up to logarithmic factors, but efﬁcient algorithms for computing the least-squares estimator remain unknown to date. We approach this important problem from a heuristic perspective. Speciﬁcally, we replace the combinatorial permutation constraint by a continuous regularization term, and then use projected gradient descent to obtain a local minimum of the non-convex objective. We show that the attained local minimum is the global minimum in certain special cases under the noiseless setting, and preserves desirable properties under the noisy setting. Simulation results reveal that our proposed algo-rithm outperforms prior algorithms when (1) the underlying model is more complex than simplistic parametric assumptions such as low-rankedness, or (2) the signal-to-noise ratio is high. Under partial observations, the proposed algorithm requires an initialization, and different initializations may lead to different local minima. We empirically observe that the proposed algorithm yields consistent improvement over the initialization, even though different initializations start with different levels of quality.
Carrier dynamics of Ba(Fe 1- x Co x ) 2 As 2 as a function of doping

In this thesis a systematic light scattering study of the newly discovered iron-based superconductor Ba(Fe1-xCox)2As2 is presented. The main focus is placed on the study of electronic properties in a doping range x in which magnetism and superconductivity are in close proximity. The experiment affords a window into band and momentum-dependent electronic properties. The magnetic order is predominantly itinerant. The structure of the superconducting gap indicates that the coupling potential may result from magnetic fluctuations.
Magnetar giant flare in NGC 253 seen by Fermi-GBM

Dipartimento Interateneo di Fisica, Politecnico di Bari, Via E. Orabona 4, 70125 Bari, Italy Istituto Nazionale di Fisica Nucleare, Sezione di Bari, Via E. Orabona 4, 70125 Bari, Italy Universities Space and Research Association, 320 Sparkman Drive, Huntsville, AL 35805, USA Center for Space Plasma and Aeronomic Research, University of Alabama in Huntsville, Huntsville, AL 35899, USA Department of Physics and Astronomy, Rice University, Houston, TX 77251, USA 5 Space Science Department, University of Alabama in Huntsville, Huntsville, AL 35899, USA Department of Physics, The George Washington University, 725 21st Street NW, Washington, DC 20052, USA Astronomy, Physics, and Statistics Institute of Sciences (APSIS), The George Washington University, Washington, DC 20052, USA Department of Physics, The Pennsylvania State University, University Park, PA 16802, USA Center for Data-Intensive Research in Astronomy and Cosmology (DIRAC), Department of Astronomy, University of Washington Seattle, WA 98195, USA Department of Astronomy & Astrophysics, University of Toronto, Toronto, Ontario, Canada M5S 3H4 Sabancı University, Faculty of Engineering and Natural Sciences, Istanbul 34956, Turkey Department of Astronomy and Astrophysics, The Pennsylvania State University, 525 Davey Lab, University Park, PA 16802, USA Astrophysics Branch, ST12, NASA/Marshall Space Flight Center, Huntsville, AL 35812, USA National Radio Astronomy Observatory, P.O. Box O, Socorro, NM 87801, USA NASA Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA Department of Physics and Astronomy, Louisiana State University, Baton Rouge, LA 70803 USA E-mail: elisabetta.bissaldi@ba.infn. it
Accident Avoidance by Using Road Sign Recognition System

--------------------------------------------------------------------- Abstract - The increase in the number of vehicles has led to a number of traffic signs. Therefore, a system that can automatically recognize the traffic signs is being needed to reduce traffic accidents and to drive more freely. Traffic Sign Recognition (TSR) systems employ vehicle mounted cameras that identify traffic signs while driving on these road. Typically, these systems recognize speed limit signs, stop signs and warning signs such as pedestrian crossing, railroad crossing etc. Their primary function is to inform the driver of recent traffic signs that may have been missed due to distraction or inattentiveness. A camera scans the roadside for traffic signs. The Raspberry Pi is a credit card sized single computer or SoC that uses ARM1176JZF-S core SoC, or System on a Chip, is a method of placing all necessary electronics for running a computer on a single chip. Raspberry Pi needs an Operating system to start up. In the aim of cost reduction, the Raspberry Pi omits any on-board non-volatile memory used to store the boot loaders, Linux Kernels and file systems as seen in more traditional embedded systems. Rather, a SD/MMC card slot is provided for this purpose. After boot load, as per the application program Raspberry Pi will get execute.
TWITTER OPINION MINING USING NEURAL NETWORKS

- Twitter is one type of social media that is often used. Users use Twitter to convey their tweet to the general public. The number of Twitter users has reached 330 million people worldwide. Besides that, in Twitter there are tweets that can be sentiments. Twitter is one of the most popular online social networking sites where users communicate and interact on various topics. In this paper, Deep CNN Algorithm is used to analysis the sentiments in twitter data. The sentiments are analyzed and labelled as positive and negative labels. These sentiments are visualized as bar graph. This improves the accuracy of the classification.
Surgical management of primary palatoplasty-A systematic Review

Clefts of the secondary palate, either isolated or accompanying, a cleft lip, are characterized by a defect in the palate of varying extent and by abnormal insertion of the levator veli palatini muscles. It is argued that repair of the palate should be carried out in one stage, shortly before or after 1 year of age, and should include intralveloplasty. Surgical corrections of cleft lip and palate primary lip repair such as (surgery for lip correction) and primary palatoplasty (reconstruction of hard and/or soft palate), are recommended in the first year of life. Primary palate surgery can be performed through various surgical techniques, of which the best for the type and the extent of the cleft is chosen, always seeking correction from the anatomic and functional point of view. Surgical failure may occur due to the surgical technique, the surgeon's skill, and/or the extent of the cleft palate. A Cleft palate repair is of concern to plastic surgeons, speech pathologists, otolaryngologists and orthodontists with respect to the timing of the operation, the type of palatoplasty to be considered and the effect of the repair on speech, facial growth and eustachian tube function. The objective of this procedure is to close the palatal defect and create an adequately functioning velopharyngeal mechanism for normal speech production. Surgery of the palate generally occurs between 9-15 months of age. It is done at this time in an effort to provide the child with the best physiological mechanisms for language and speech development. A preoperative work-up with hemoglobin and hematocrit levels must occur within 30 days of surgery. Most children spend 1 or 2 nights in the hospital following surgery. They will return for a follow-up appointment 3-4 weeks after surgery. A visit with the cleft surgeon and other members of the cleft team should occur 3-6 months later.The principal outcome measures are facial, attractiveness, speech, facial growth and psychological wellbeing.
Cosmic rays and the structure of the universe studied in Cosmic Ray Extremely Distributed Observatory with citizen science

The CREDO project aims to observe sets of simultaneous global air showers, i.e. covering the entire hemisphere of the Earth. To do this, it is necessary to deploy detectors of various sizes as densely as possible across the globe. These observations are intended to help answer some basic questions of astrophysics, such as the occurrence and nature of dark matter, the sources of high-energy particles, and the structure of space-time. The method of work of the CREDO project is citizen science, i.e. participation in the project activities not only of scientists but also students, adults, organized groups of enthusiasts and individuals interested in the topic. This community also includes people with disabilities, e.g. visually impaired or blind. The synergy of these two tasks of CREDO - science and education of the society, results in an increasing and wider territorial participation of outsiders in the activities of the project and a very rapid scientiﬁc development of the project. The following text (provisional version) presents two aspects of the CREDO project - scientiﬁc and educational, and the state of art of the project for June 2021.