Miracle-dz/UniFAR-FTUs huggingface dataset:
In-Database Machine Learning with SQL on GPUs

In machine learning, continuously retraining a model guarantees accurate predictions based on the latest data as training input. But to retrieve the latest data from a database, time-consuming extraction is necessary as database systems have rarely been used for operations such as matrix algebra and gradient descent. In this work, we demonstrate that SQL with recursive tables makes it possible to express a complete machine learning pipeline out of data preprocessing, model training and its validation. To facilitate the specification of loss functions, we extend the code-generating database system Umbra by an operator for automatic differentiation for use within recursive tables: With the loss function expressed in SQL as a lambda function, Umbra generates machine code for each partial derivative. We further use automatic differentiation for a dedicated gradient descent operator, which generates LLVM code to train a user-specified model on GPUs. We fine-tune GPU kernels at hardware level to allow a higher throughput and propose non-blocking synchronisation of multiple units. In our evaluation, automatic differentiation accelerated the runtime by the number of cached subexpressions compared to compiling each derivative separately. Our GPU kernels with independent models allowed maximal throughput even for small batch sizes, making machine learning pipelines within SQL more competitive.
Nursing Intervention PROGRAM FOR MOTHERS AND THEIR MUMPS CHILD BY USING EPIDEMIOLOGICAL MODEL

Background: Mumps epidemics have occurred worldwide with school-aged children generally serving as the vector for horizontal spread to household family members. The aim of this study was to evaluate the effect of nursing intervention program for mothers' and their mumps child by using epidemiological model. Research design: A quasiexperimental design was used in this study. Setting: The study was conducted at Out-patient Clinic in Health Insurance Hospital where the children were treated and referral. The sample: Convenient sample of all children were admitted to previous mentioned setting which include 40 child and their mothers according to certain criteria less than 8 years and residence with mothers at home. Tools: An interviewing questionnaire which consists of three parts: I): a) Socio-demographic characteristics of child mothers'. b): Children characteristics II): a): Mothers knowledge regarding mumps. b): Mothers knowledge regarding an epidemiological model. III): Practices as reported by mothers regarding mumps child. Results of this study showed; there were improvement of mothers knowledge regarding mumps infection after the program especially for site of parotid gland, complication and mode of transmission which represent 92.5% compared by 45.0%, 37.5%, and 65.0% respectively pre program. This study concluded that: The nursing intervention program has showed a highly statistically significant effect on knowledge and practices of the mothers post program compared by pre program. The study recommended that: Health education program should be provided for mumps children and their mothers regarding epidemiological model during follow-up visits, illustrated booklet should be provided with description of disease control and prevention measurement.
Effect of Self-Care Management Program on Quality of Life among Acquired Immune Deficiency Syndrome Patients

Background: Acquired Immune Deficiency Syndrome (AIDS) is one of the chronic and progressive diseases that have complex health problems, which affect the quality of life. The aim of this study was to evaluate the effect of self-care management program on quality of life among Acquired Immune Deficiency Syndrome patients. Research design: Quasi-experimental research design was used in this study. Setting: This study was conducted at AIDS Outpatient Clinic in Fever Hospital at Benha City. Sample: Simple random sample of 25 % of attended AIDS patients in last year (2018-2019), the total sample was included (100) patients. Tools: Two tools were used. Tool I): A structured interviewing questionnaire which consisted of three parts a) socio-demographic characteristics, b) AIDS patients` knowledge and c) AIDS patients` self-care reported practices. Tool II): Scale to measure quality of life among AIDS patients. Results; 64% of AIDS patients were males, 39 % of them their aged 35 years or more with mean age was 41.73±11.90, 51% of patients had AIDS for 5years or more and 57% of them during symptomatic stage. 67% the studied AIDS patients had poor knowledge regarding AIDS before program compared with 11% post program. 29% of the studied AIDS patients had satisfactory self-care reported practices before program, which increased to 79% during the post program. 39% of the AIDS patients had poor total scores of quality of life preprogram, which decreased to 16% post program. There were positive statistically significant correlations between AIDS patients` total knowledge scores and AIDS patients ` total self-care reported practices scores, and AIDS patients ` total quality of life scores post program. This study concluded that: Self-care management program succeeded to improve knowledge; self-care reported practices and quality of life among AIDS patients. The study recommended that: Continuous self-care management program for AIDS patients to increase their knowledge, self-care practices and improve their quality of life.
Percutaneous Argon-Helium Cryoablation for Small Hepatocellular Carcinoma Located Adjacent to a Major Organ or Viscus: A Retrospective Study of 92 Patients at a Single Center

Background Cryoablation of hepatocellular carcinoma (HCC) close to major organs or viscus is challenging because it can cause complications. This retrospective study aimed to investigate the safety and efficacy of percutaneous argon-helium cryoablation of small HCC located adjacent to major organs or viscus. Material/Methods Ninety-two patients who underwent percutaneous argon-helium cryoablation between February 2012 and December 2018 at the Fifth Medical Center of the Chinese People’s Liberation Army General Hospital were included. Treatment efficacy was evaluated by magnetic resonance imaging or triphasic computed tomography scan within 1 week after each cryoablation procedure. Local tumor progression, distant recurrence, and overall survival were analyzed using the Kaplan-Meier method and log-rank test. Results A total of 92 patients with small HCC located adjacent to major organs or viscus who underwent cryoablation were retrospectively reviewed. The number of patients with tumors adjacent to the gallbladder, portal or hepatic vein, diaphragm, stomach, heart, and intestine was 22, 1, 39, 6, 8, and 16, respectively. Cumulative local tumor progression rates at 1 and 2 years were 2.8% and 7.3%, respectively. Cumulative distant recurrence rates at 1, 2, and 3 years were 11.1%, 17.6%, and 20.7%, respectively. The overall survival rates at 1, 2, and 4 years were 100%, 93.6%, and 74.9%, respectively. Major complications were observed in 5 (5.4%) patients. Minor complications were observed in 85 (92.4%) patients. Conclusions This experience from a single center showed that percutaneous argon-helium cryoablation was safe and effective in the management of small HCC that is located adjacent to major organs or viscus.
Climate Change Vulnerability and Key Adaptation Trajectory of the Regional Economic System

From the microperspective, climate change restricts human life in many aspects, and it affects the regional economic system from the macroperspective. The paper presents an inoperability input-output model (IIM) that is an extension approach of the Leontief input-output model. The IIM is able to provide a feasible methodology for measuring the impact of vulnerable economic factors on the whole economic system and identifying the key adaptation trajectory of the economic system. The IIM is applied in Tianjin to explore its dilemmas facing the increased demand for electricity, water, and public health service sectors under the RCP2.5, RCP4.5, and RCP8.5 climate scenarios. The results indicated that the inoperability ranking of all economic sectors is the same under the three climate scenarios. The key adaptation trajectory in Tianjin is S40, S27, S25, S17, S12, S02, S21, S16, S09, S24, S29, S33, S19, S13, and S15 sector in order. The costs required by the key adaptation trajectory to adapt to climate change account for more than 90% of that required by the whole economic system. These results can be helpful for policy-makers to prioritize sectors in terms of climate adaptation and understand the efficacy of climate change risk mitigation strategies.
Biological Activity and Therapeutic Potential of Quercetin for Inflammatory Bowel Disease

Rates of inflammatory bowel disease (IBD) are increasing globally. IBD is an idiopathic chronic inflammatory disorder of the gastrointestinal tract characterized by acute disease flares and remission. IBD has a multifactorial pathogenesis whereby environmental and genetic factors contribute to disease onset. IBD is a serious clinical disorder that significantly impairs the patient’s quality of life, and is associated with increased morbidity, mortality, and cancer risk. IBD is characterized by the loss of tolerance to luminal antigens resulting in a persistent and excessive immune response. There is currently an unmet need for novel treatment options for patients with IBD. In recent years, flavonoids, a class of polyphenols widely distributed in fruits and vegetables gained significant interest as potential therapeutic agents for inflammatory disorders including IBD. Many flavonoids regulate cellular transcription factors critical in antioxidant and antiinflammatory pathways within the innate and adaptive immune response. Among these flavonoids, quercetin and its related glycosides have demonstrated remarkable effects capable of attenuating inflammation in experimental models of IBD. To date, many mechanisms underlying quercetin’s biological activity have been elucidated; wherein quercetin is reported to downregulate NFκB, MAPK, STAT and AP-1, and upregulate Nrf2. Thus, the aim of the review is to present the evidence surrounding quercetins biological activity, and its potential as a novel dietary intervention for IBD.
The Relationship between Personality Traits, Optimism of Pediatric Nursing Student and their Theoretical and Practical Achievement *Howaida

*Howaida Moawad Ahmed, **Rehab El sayed Mohammed, *** Rodina Ahmed mokbel and ****Samah Ramdan Ibrahim. * Lecturer of pediatric nursing, Faculty of Nursing, Benha University **Lecturer of psychiatric Nursing, Faculty of Nursing, Benha University. *** Lecturer of pediatric nursing, Faculty of Nursing, Damanhur University ****Lecturer of psychiatric Nursing, Faculty of Nursing, Benha University. Abstract:
Intermediate Representations for Trajectory Forecasting

In urban driving scenarios, forecasting future trajectories of surrounding vehicles is of paramount importance. It is an essential component in the autonomous driving pipeline as the forecasted trajectories are used as inputs in the planning and control modules of the autonomous vehicles. While several approaches for the problem have been proposed, the best-performing ones tend to require extremely detailed input representations (e.g., image sequences). As a result, such methods do not generalize to datasets they have not been trained on. On the other end of the representation spectrum, some approaches represent the vehicle of interest in a scene in terms of geometric properties such as 3D location w.r. t ego vehicle, rotational parameters, and velocity. These approaches suffer from a lack of semantics / contextual information and cannot produce the most accurate forecasts. In this thesis, we propose intermediate representations that are particularly well-suited for trajectory forecasting. We show that these intermediate representations, generated using off-the-shelf computer vision methods for object detection and semantic segmentation, provide the right balance between competing features of expressiveness and generalizability. As opposed to using texture (color) information from images, we condition on semantics and train an autoregressive model to accurately predict future trajectories of traffic participants (vehicles). We demonstrate that semantics provide a significant boost over techniques that operate over raw pixel intensities/disparities. Uncharacteristic of state-of-the-art approaches, our representations and models generalize across different sensing modalities (stereo imagery, LiDAR, a combination of both), and also across completely different datasets, collected across several cities, and also across countries where people drive on opposite sides of the road (left-handed vs. right-handed driving). We also conduct detailed ablation studies to understand which semantics generalize across datasets and demonstrate their importance in the generalizability of the model. Additionally, we demonstrate an application of our approach in multi-object tracking (data association).
Socioeconomic position and mental health during the COVID- 19 pandemic: a cross-sectional analysis of the CovidLife study [version 1; peer review: awaiting peer review]

Background: The coronavirus disease 2019 (COVID-19) pandemic has been linked to an increase in mental health problems. This study examined their association with socioeconomic position (SEP), as well as potential confounding and mediating factors. Methods: We analysed data from the CovidLife study (N=14,387; 66.4% female; mean [SD] age, 57.4 [13.9] years). Data were collected in an online survey of UK adults (aged 18 years or over) between 17 April and 7 June 2020. SEP measures included area deprivation (the Scottish Index of Multiple Deprivation [SIMD]), education level, household income, and employment status. Mental health was measured using the Patient Health Questionnaire-9 (PHQ-9) and the Generalised Anxiety Disorder-7 (GAD-7) scale. Worry indices were derived using principal component analysis. Logistic regression was used to estimate the associations between SEP and mental health. Results: Low SEP was associated with increased odds of depression and anxiety (odds ratio [OR] range 1.18-2.69). These associations remained significant after adjusting for age, sex, relationship status, and psychiatric history. Multivariable adjustment for medical worry and isolation during the pandemic had the largest attenuating effects (ranges 18-60% and 4-46%, respectively) on mental health outcomes. When adding further adjustment for the remaining SEP markers and Open Peer Review Reviewer Status AWAITING PEER REVIEW Any reports and responses or comments on the article can be found at the end of the article. Page 1 of 18 Wellcome Open Research 2021, 6:139 Last updated: 04 JUN 2021
Machine Learning-powered Iterative Combinatorial Auctions (

Over the last forty years, the continued increase in computational power has encouraged the spread of markets that use optimization software to find possible trades among participants. Combinatorial auctions (CAs) are certainly one of the key examples of these markets and have already found several applications in the real world, ranging from industrial procurement to spectrum sales. In a CA, a seller puts multiple indivisible items up for sale among several buyers who express their preferences via bids on arbitrary bundles of items. One of the major challenges when conducting CAs in practice is that the size of the bundle space grows exponentially in the number of items, which may allow bidders to only bid on a small fraction of their bundles of interest. Thus, CAs are often deployed in iterative forms, integrating price-based preference elicitation algorithms that provide bidding guidance. However, the currently adopted solutions are still unsatisfactory, leading to suboptimal bidding behavior and market inefficiencies. In this thesis, I introduce iterative CAs that use preference elicitation algorithms based on statistical machine learning (ML) algorithms. Statistical ML algorithms allow the auctioneer to exploit prior data about bidders’ valuations to reduce the costs of elicitation. My first research question focuses on how to use statistical ML algorithms to decrease the number of rounds in price-based auction designs. I introduce a Bayesian iterative CA design that alternates between refining beliefs over bidders’ valuations and quoting the prices that are most likely to clear the auction under these beliefs. This Bayesian auction performs remarkably well against standard baselines under reasonable priors over bidders’ valuations. Recent experimental studies have highlighted that, in price-based iterative CAs, bidders focus their bidding on a small set of bundles selected before the auction; this suboptimal bidding was one of the leading causes of inefficiencies in these experiments. My second research question focuses on how to use statistical ML algorithms to select which bundle bids bidders should submit to let the auction implement efficient allocations. I develop an elicitation algorithm based on value queries that, under reasonable prior beliefs over bidders’ valuations, reveals highly efficient allocations even when only a small fraction of bundle bids are submitted. My third research question focuses on how to design value query-based auctions that integrate this elicitation algorithm.
Ocean carbon cycle feedbacks in CMIP6 models: contributions from different basins

Abstract. The ocean response to carbon emissions involves the combined effect of an increase in atmospheric CO2, acting to enhance the ocean carbon storage, and climate change, acting to decrease the ocean carbon storage. This ocean response can be characterised in terms of a carbon–concentration feedback and a carbon–climate feedback. The contribution from different ocean basins to these feedbacks on centennial timescales is explored using diagnostics of ocean carbonate chemistry, physical ventilation and biological processes in 11 CMIP6 Earth system models. To gain mechanistic insight, the dependence of these feedbacks on the Atlantic Meridional Overturning Circulation (AMOC) is also investigated in an idealised climate model and the CMIP6 models. For the carbon–concentration feedback, the Atlantic, Pacific and Southern oceans provide comparable contributions when estimated in terms of the volume-integrated carbon storage. This large contribution from the Atlantic Ocean relative to its size is due to strong local physical ventilation and an influx of carbon transported from the Southern Ocean. The Southern Ocean has large anthropogenic carbon uptake from the atmosphere, but its contribution to the carbon storage is relatively small due to large carbon transport to the other basins. For the carbon–climate feedback estimated in terms of carbon storage, the Atlantic and Arctic oceans provide the largest contributions relative to their size. In the Atlantic, this large contribution is primarily due to climate change acting to reduce the physical ventilation. In the Arctic, this large contribution is associated with a large warming per unit volume. The Southern Ocean provides a relatively small contribution to the carbon–climate feedback, due to competition between the climate effects of a decrease in solubility and physical ventilation and an increase in accumulation of regenerated carbon. The more poorly ventilated Indo-Pacific Ocean provides a small contribution to the carbon cycle feedbacks relative to its size. In the Atlantic Ocean, the carbon cycle feedbacks strongly depend on the AMOC strength and its weakening with warming. In the Arctic, there is a moderate correlation between the AMOC weakening and the carbon–climate feedback that is related to changes in carbonate chemistry. In the Pacific, Indian and Southern oceans, there is no clear correlation between the AMOC and the carbon cycle feedbacks, suggesting that other processes control the ocean ventilation and carbon storage there.
Immunity to SARS-CoV-2 persists 9 months post-symptoms with an altered T cell phenotype compared to influenza A virus-specific memory

SARS-CoV-2 induces T cell, B cell and antibody responses that are detected for several months in recovered individuals. Whether this response resembles a typical respiratory viral infection is a matter of debate. Here we followed T cell and antibody responses in 24 mainly non-hospitalized SARS-CoV-2 recovered subjects at two time points (median of 45- and 145-days post-symptom onset). Antibody responses were detected in 95% of subjects, with a strong correlation between plasma and salivary anti-S and anti-RBD IgG, as well as a correlation between circulating T follicular helper cells and the SARS-CoV-2-specific IgG response. Based on intracellular cytokine production or proliferation, CD4+ T cell responses to SARS-CoV-2 were detected in all subjects, decaying with a half-life of 5-6 months for S-specific IL-2-producing cells. CD4+ responses were largely of the T helper 1 phenotype, but with a lower ratio of IFN-{gamma} : IL-2 producing cells and a lower frequency of CD8+: CD4+ T cells compared to influenza A virus-(IAV)-specific memory responses within the same subjects. Analysis of secreted molecules also revealed a lower ratio of IFN-{gamma}: IL-2 and IFN-{gamma}: IL-6 and an altered cytotoxic profile for S- and N-specific compared to IAV-specific responses. These data suggest that the memory T-cell phenotype after a single infection with SARS-CoV-2 persists over time, with an altered cytokine and cytotoxic profile compared to long term memory to IAV within the same subjects.
Study on settlement characteristics of deep soft strata by vacuum preloading

In order to study the vacuum preloading settlement characteristics of Hengli Island soft strata, the monitoring data of the vacuum preloading area are analyzed, and the hyperbolic method and the three-points method are used to predict the final settlement. The results show that the variation trend of settlement, vacuum degree and water level has a high consistency. The larger the calculated data span, the larger the calculated result. The three-points method is closer to the measured value than the hyperbolic method, the ratio of the three-points method to the measured value was 94%∼110%, and the latter 110%∼120%. However, the three-points method is sensitive to settlement saltation, and the calculation result error will be large if the calculated data span the saltation region, while the hyperbolic method is not sensitive to settlement saltation. According to the settlement rate and predicted settlement, the unloading time is earlier than the actual unloading time, which provides a reference for the reasonable evaluation of the unloading time and the reduction of the low-efficiency preloading time.
Resarch on Calculation Method of Pile Horizontal Response under Combined Loads

The main function of the pile foundation is to bear the vertical load, but in actual engineering, the pile foundation usually bears combined loads which contain vertical load, lateral load and bending moment. Under combined loads, due to the P-Δ effect, the calculation of the bearing capacity and deformation of the pile foundation is very complicated. The small deformation superposition principle recommended by the current pile foundation codes fails to consider the resistance of the soil around the pile under the combined loads, and it is difficult to accurately evaluate the influence of P-Δ effect on the bearing capacity and deformation of pile foundation. In view of this, this paper firstly starts from the potential energy equation of the pile-soil system and deduces the calculation formula for the horizontal displacement of the pile considering the P-Δ effect, and it is verified in conjunction with related calculation examples. Then the factors affecting the P-Δ effect are discussed in detail, and the results show that the larger the load ratio is, the more obvious the P-Δ effect will be; when the pile top is fixed under the same load condition, the P-Δ effect will be significantly weakened.