Miracle-dz/UniFAR-FTUs huggingface dataset:
Apic Text of Infection Control and Epidemiology 4th Edition Table of Contents

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Mining Related Queries from Query Logs Based on Linear Regression

In this paper a novel linear regression model is proposed to mine related queries from query logs. Three types of association relationships between queries are identified and leveraged in our model, which include query session co-occurence, URL-clicked sharing and text similarity. Previous work directly applies part of these relations, which may be largely affected by the noise in query logs, such as the sparsity of click-through data, query-session segmentation errors and noisy clicks. In this work we propose linear regression analysis to identify effective features. In this way, we can effectively deal with the noise issue. The experiments demonstrate that the features identified with linear regression analysis are very effective. Moreover, the performance of our proposed linear regression model outperforms existing methods.
Fast orthorectified mosaics of thousands of aerial photographs from small UAVs

Small unmanned air vehicles (UAVs) provide an economical means of imaging large areas of terrain at far lower cost than satellites. Applications range from precision agriculture to disaster response and power line maintenance. Because small UAVs fly at low altitudes of approximately 100 meters, their cameras have only a limited field of view and must take thousands of photographs to cover a reasonably sized area. To provide a unified view of the area, these photographs must be combined into a seamless photo mosaic. The conventional approach for accomplishing this mosaicking process is called block bundle adjustment, and it works well if there are only a few tens or hundreds of photographs. It runs in O(n3) time, where n is the number of images. When there are thousands of photographs, this method fails because its memory and computational time requirements become prohibitively excessive. We have developed a new technique that replaces bundle adjustment with an iterative algorithm that is very fast and requires little memory. After pairwise image registration, the algorithm projects the resulting tie points to the ground and moves them closer to each other to produce a new set of control points. It fits the image parameters to these control points and repeats the process iteratively to convergence. The algorithm is implemented as an image mosaicking application in Java and runs on a Windows PC. It executes in O(n) time and produces very high resolution mosaics (2 cm per pixel) at the rate of 14 sec per image. This time includes all steps of the mosaicking process from the disk read of the imagery to the disk output of the final mosaic. Experiments show the algorithm to be accurate and reliable for mosaicking thousands of images.
The Effects of COVID-19 Pandemic on Italian School-Aged Children: Sleep-Related Difficulties and Trauma Reactions

Purpose The COVID-19 pandemic has affected the mental and physical health of the world population. This study aims to investigate incidence of sleep-related difficulties and post-traumatic stress disorder in the school-aged children after 1 year of the pandemic. Methods A sample of Italian children (6-12 years) was queried about their sleep behaviors after 1 year of the pandemic, answering the Children's Sleep Habits Questionnaire (CSHQ). We also evaluated trauma symptoms with the Children's Impact of Event Scale (CRIES-8). Results Among 205 participants, 184 (89.8%) presented sleep-related difficulties. Out of all, 99 (48.3%) had a high risk to develop post-traumatic stress disorder. Ninety-five (51.6%) children with sleep-related difficulties also presented an abnormal CRIES-8 total score. A correlation was found between the CSHQ total score and the CRIES-8 total score (r = 0.354, P < .01). Conclusions The sleep-related difficulties occurring during COVID-19 outbreak may compound to increase the risk to develop post-traumatic stress disorder among Italian children.
An ontology-driven approach to personalised mHealth application development

Mobile devices when provisioned with intuitive mobile healthcare (mHealth) applications provide a powerful platform that has been recognised to have made a significant impact on healthcare delivery. The popularity of mHealth applications is rapidly expanding amongst consumers and there is a continuous demand to improve the effectiveness of mHealth applications. Personalisation has already been acknowledged by the healthcare industry as a mechanism to improve healthcare delivery, recognising that each consumer is unique. Yet, a typical mHealth application is designed to cater for the needs of large target demographics and are frequently developed without the necessary knowledge and expertise of healthcare providers. As a result, they often fail to meet the consumer’s specific healthcare requirements. Since healthcare professionals understand the specific healthcare requirements of a consumer, they are best suited for developing personalised mobile healthcare applications. However, they do not possess the familiarity, skills and knowledge to address the challenges associated with mobile application development. Therefore, this research addresses the need for a new approach to personalised mHealth application development in the form of an extensible ontology-driven framework that enables healthcare professionals to create personalised mHealth applications for healthcare consumers. This research explored personalisation & the challenges of personalised mobile application development, existing approaches and related works. Followed by a detailed investigation into the various health-related functions available in mHealth applications designed for healthcare consumers, that led to the creation of the mHealth Application Function Taxonomy. The next phase presents the theoretical design and development considerations of the Personalised Mobile Application Development (PMAD) ontology. The PMAD ontology encapsulates key knowledge associated with the development of personalised mHealth applications, that can be operationalised to compensate for the missing domain expertise during the personalised mHealth application development process. The final and contribution of this research describes and defines the approach and components of the Personalised Mobile Application Development ontology-driven framework that addresses the limitations of existing end-user programming solutions and enables healthcare professionals to create personalised mHealth applications for healthcare consumers.
[Surveillance of Sensitivity to Penicillin in streptococcus Agalactiae recovered from pregnant women between 35-37 weeks of gestation].

Streptococcus agalactiae (GBS) cause severe infections in newborns under three months. Meningitis, pneumonia and sepsis are the main infectious diseases in these children. These infections are among the most serious that an individual can suffer in his first twelve hours of life. The child acquires the infection by vertical transmission of the colonized mother. To prevent neonatal disease, penicillin is recommended as the drug of choice for intrapartum prophylaxis (PIP) in pregnant women colonized. However, strains with decreased susceptibility to penicillin have been detected so it is important to monitor the susceptibility to penicillin to ensure its usefulness during prophylaxis. The aim of this study was to determine the sensitivity to penicillin in GBS strains recovered from pregnant women with 35-37 weeks of gestation. Ninety-six isolates were studied and sensitivity was determined by the epsilometric method Etest® (LIOFILCHEM, Italy), following the recommendations of the Clinical Laboratory Standards Institute (CLSI). Minimum Inhibitory Concentration (MIC) was obtained for each bacterial isolation. 100% (96) of the strains studied were sensitive to penicillin with MIC values between 0.012 and 0.094 ? g mL-1. These results indicate that penicillin remains the antimicrobial of choice during intrapartum prophylaxis, for the prevention of neonatal disease caused by GBS in our region. The importance of epidemiological surveillance of sensitivity to penicillin and other antimicrobials is highlighted in order to alert new resistance mechanisms and to adapt treatment strategies.
Evaluation of Conducting Phone Interviews on Sexual Behavior: An Iranian Population-Based Study

Background: Phone interview is a safe way for collecting sensitive data due to no need for direct contact with the interviewees and their privacy. Objectives: The purpose of this study was to investigate the feasibility and validity of phone interviewing using mobile phones to collect sensitive information related to the participants’ sexual behavior. Methods: This cross-sectional study was conducted on the sexually active population of Marvdasht, Iran, from 2017 - 2018. Results: A total of 5,894 individuals (2,991 from urban and 2,903 from rural areas) from both genders (n = 3,202 males vs. n = 2,692 females) with an age range of 18 - 50 years were included in this study. The participation rate was convincing (92.18%), and the response rate to all questions was also very high (99.1%). According to the results, gender and place of residency had statistically significant associations with the rates of participation and response. Conclusions: The results suggested that a phone interview is a potentially useful method for gathering sensitive information in Iranian population, a community with a religious background.
Entanglement under the renormalization-group transformations on quantum states and in quantum phase transitions

We consider quantum states under the renormalization-group (RG) transformations introduced by Verstraete et al. [Phys. Rev. Lett. 94, 140601 (2005)] and propose a quantification of entanglement under such RG (via the geometric measure of entanglement). We examine the resulting entanglement under RG for the ground states of "matrix-product-state" (MPS) Hamiltonians constructed by Wolf et al. [Phys. Rev. Lett. 97, 110403 (2006)] that possess quantum phase transitions. We find that near critical points, the ground-state entanglement exhibits singular behavior. The singular behavior within finite steps of RG obeys a scaling hypothesis and reveals the correlation length exponent. However, under the infinite steps of RG transformation, the singular behavior is rendered different and is universal only when there is an underlying conformal-field-theory description of the critical point.
The Effectiveness of Using the Six Thinking Hats in Acquiring Physical Concepts among Tenth Graders Based on their Achievement Motivation

Objectives: The study aims to investigate the effectiveness of using the Six Thinking Hats Strategy in acquiring physical concepts for tenth grade students in the light of their achievement motivation compared to the traditional method. Methods: quantitative descriptive Approach was employed.The study sample consisted of (55) female students, that were selected from one school within the Education Directorate in Madaba for the academic year 2020/2021. The sample was divided into two groups: experimental group (28) students which studied using the Six Thinking Hats strategy, and a controlled group (27) students which studied using the traditional method. Data were collected by classifying students according to their achievement motivation into high and low achievement motivation based on the achievement motivation scale. The researcher used the quasi-experimental approach. The test of acquiring physical concepts was applied after determining the validity and reliability of the study tool. Results: The result showed that there were statistically significant differences (α=0.05) due to the method of teaching in acquiring physical concepts in favor of the experimental group. The results also showed that there were statistically significant differences (α=0.05) attributed to achievement motivation in favor of female students with high achievement motivation, and there was no statistically significant difference in the interaction between them. Conclusions: The need of universities to carry out further studies in order to enforce the result of the study.
Investigating the contribution of the inflammasome to persistent pain states

Neuropathic pain, a debilitating condition, occurs as a consequence of nerve injury with symptoms such as spontaneous pain, hyperalgesia, and allodynia commonly reported. In animal models of peripheral nerve injury, there is accumulation and proliferation of microglial cells in the injured spinal cord and macrophages within the injured nerve and dorsal root ganglion (DRG), contributing to the development of pain-like behaviours. The pro-inflammatory cytokine interleukin-1β (IL-1β) plays a key role in acute and chronic inflammation. It causes potent mechanical and thermal hyperalgesia when injected into peripheral tissues, and increased expression of IL-1β in the spinal cord, DRG, and injured nerve is seen in several animal models of inflammatory and neuropathic pain. A key step in the release of active IL-1β is the cleavage of pro-IL-1β by active caspase-1, generating mature IL-1β. Activation of this enzyme requires assembly of the inflammasome, a multi-protein complex. The active complex contains a central scaffold protein (eg nod-like receptor-1 (NLRP1), NLRP3), the adaptor protein apoptosis-associated speck-like protein containing a CARD (ASC), and pro-caspase-1. It is known to assemble in response to a variety of exogenous and endogenous danger signals (eg adenosine-5’-triphosphate (ATP), monosodium urate (MSU) crystals). Data presented in this thesis demonstrates that, following L5 Spinal Nerve Transection (SNT), an animal model of neuropathic pain, inflammasome components NLRP3, ASC, and caspase-1 are upregulated in the injured DRG and the ipsilateral lumbar dorsal horn. Immunohistochemical analysis reveals that ASC and caspase-1 are both highly co-localised with macrophage and microglial marker ionised calcium-binding adaptor molecule-1 (IBA1), but not with astrocytic marker glial fibrillary acid protein (GFAP) or neuronal marker NeuN. While daily intrathecal administration of Ac-YVAD-CMK, a cell-permeant caspase-1 inhibitor, significantly attenuated established behavioural hypersensitivity following L5 SNT, ASC-/and NLRP3-/mice developed behavioural hypersensitivity normally in the Partial Sciatic Nerve Ligation (PSNL) model of neuropathic pain, indicating an inflammasome-independent role of caspase-1 in neuropathic pain. In a model of central inflammatory pain,
Identification of Putative Plant Based Antiviral Compounds to Fight Against SARS-CoV-2 Infection

Background: This study aimed to examine the efficacy of some natural compounds and their derivatives in inhibiting the nucleocapsid protein N-terminal RNA binding domain (NSP-NTD), of SARS-CoV-2 virus by using the molecular doacking approach. Methods: Physiochemical and drug likeness properties of the compounds were characterized by using SWISS ADME server tool. ADMET and TOPKAT modules of Discovery studio 4.0 were used for prediction of pharmacokinetic properties and toxicity of the compounds. Molecular docking of the ligands with the target protein (NSP-NTD) was carried out using the receptor-ligand interactions module of DS 4.0. The CDOCKER energy, CDOCKER interaction energy and binding energy of the interactions were calculated to identify the best interacting compounds. Results: Four compounds including 4-hydroxybenzoic acid, benzoic acid, 4-aminobenzoic acid and salicylic acid have been predicted as effective compounds to inhibit the NSP-NTD (responsible for packing the viral RNA into the crown like capsid) vis-à-vis combat the SARS-Cov-2 virus infection. Conclusions: In vitro and in vivo evaluation of these compounds against SARS-CoV-2 virus is required prior to assuring their potential roles in SARS-CoV-2 infection control.
The Simplex Method is Strongly Polynomial for Deterministic Markov Decision Processes

We prove that the simplex method with the highest gain/most-negative-reduced cost pivoting rule converges in strongly polynomial time for deterministic Markov decision processes (MDPs) regardless of the discount factor. For a deterministic MDP with n states and m actions, we prove the simplex method runs in O(n3m2 log2 n) iterations if the discount factor is uniform and O(n5m3 log2 n) iterations if each action has a distinct discount factor. Previously the simplex method was known to run in polynomial time only for discounted MDPs where the discount was bounded away from 1 [Ye11]. Unlike in the discounted case, the algorithm does not greedily converge to the optimum, and we require a more complex measure of progress. We identify a set of layers in which the values of primal variables must lie and show that the simplex method always makes progress optimizing one layer, and when the upper layer is updated the algorithm makes a substantial amount of progress. In the case of nonuniform discounts, we define a polynomial number of "milestone" policies and we prove that, while the objective function may not improve substantially overall, the value of at least one dual variable is always making progress towards some milestone, and the algorithm will reach the next milestone in a polynomial number of steps.
MCPIP1 restricts HIV infection and is rapidly degraded in activated CD4+ T cells

Significance Here, we present data showing that monocyte chemotactic protein-induced protein 1 (MCPIP1) acts as an RNase to limit HIV-1 production in resting CD4+ T cells. Unlike those previously identified factors with restrictions that tend to be overcome by virally encoded proteins, MCPIP1 becomes rapidly degraded on activation of human CD4+ T cells. These findings provide insights into the mechanisms of cellular activation-mediated HIV-1 production in CD4+ T cells and represent a breakthrough in the relevant field. HIV-1 primarily infects activated CD4+ T cells and macrophages. Quiescent CD4+ T cells, however, possess cellular factors that limit HIV-1 infection at different postentry steps of the viral life cycle. Here, we show that the previously reported immune regulator monocyte chemotactic protein-induced protein 1 (MCPIP1) restricts HIV-1 production in CD4+ T cells. While the ectopic expression of MCPIP1 in cell lines abolished the production of HIV-1, silencing of MCPIP1 enhanced HIV-1 production. Subsequent analysis indicated that MCPIP1 imposes its restriction by decreasing the steady levels of viral mRNA species through its RNase domain. Remarkably, common T-cell stimuli induced the rapid degradation of MCPIP1 in both T-cell lines and quiescent human CD4+ T cells. Lastly, blocking the proteosomal degradation of MCPIP1 by MG132 abrogated HIV-1 production in phorbol 12-myristate 13-acetate/ionomycin-stimulated human CD4+ T cells isolated from healthy donors. Overall, MCPIP1 poses a potent barrier against HIV-1 infection at a posttranscriptional stage. Although the observed HIV restriction conferred by MCPIP1 does not seem to be overcome by any viral protein, it is removed during cellular stimulation. These findings provide insights into the mechanisms of cellular activation-mediated HIV-1 production in CD4+ T cells.
A new and improved algorithm for online bin packing

We revisit the classic online bin packing problem. In this problem, items of positive sizes no larger than 1 are presented one by one to be packed into subsets called "bins" of total sizes no larger than 1, such that every item is assigned to a bin before the next item is presented. We use online partitioning of items into classes based on sizes, as in previous work, but we also apply a new method where items of one class can be packed into more than two types of bins, where a bin type is defined according to the number of such items grouped together. Additionally, we allow the smallest class of items to be packed in multiple kinds of bins, and not only into their own bins. We combine this with the approach of packing of sufficiently big items according to their exact sizes. Finally, we simplify the analysis of such algorithms, allowing the analysis to be based on the most standard weight functions. This simplified analysis allows us to study the algorithm which we defined based on all these ideas. This leads us to the design and analysis of the first algorithm of asymptotic competitive ratio strictly below 1.58, specifically, we break this barrier and provide an algorithm AH (Advanced Harmonic) whose asymptotic competitive ratio does not exceed 1.5783.
Front-to-End Bidirectional Heuristic Search with Near-Optimal Node Expansions

It is well-known that any admissible unidirectional heuristic search algorithm must expand all states whose $f$-value is smaller than the optimal solution cost when using a consistent heuristic. Such states are called "surely expanded" (s.e.). A recent study characterized s.e. pairs of states for bidirectional search with consistent heuristics: if a pair of states is s.e. then at least one of the two states must be expanded. This paper derives a lower bound, VC, on the minimum number of expansions required to cover all s.e. pairs, and present a new admissible front-to-end bidirectional heuristic search algorithm, Near-Optimal Bidirectional Search (NBS), that is guaranteed to do no more than 2VC expansions. We further prove that no admissible front-to-end algorithm has a worst case better than 2VC. Experimental results show that NBS competes with or outperforms existing bidirectional search algorithms, and often outperforms A* as well.