Miracle-dz/UniFAR-FTUs huggingface dataset:
Immunogenicity of BNT162b2 and CoronaVac boosters in fully vaccinated individuals with CoronaVac against SARS-CoV-2: A Longitudinal Study

Objective: There is a need for the immunogenicity of different boosters after widely used inactivated vaccine regimens. We aimed to determine the effects of BNT162b2 and CoronaVac boosters on the humoral and cellular immunity of individuals who had two doses of CoronaVac vaccination. Methods: The study was conducted in three centers (Koc University Hospital, Istanbul University Cerrahpasa Hospital, and Istanbul University, Istanbul Medical School Hospital) in Istanbul. Individuals who had two doses of CoronaVac and no history of COVID-19 were included. The baseline blood samples were collected three to five months after two doses of CoronaVac. Follow-up samples were taken one and three months after third doses of CoronaVac or one dose of mRNA BNT162b2 boosters. Neutralizing antibody titers were detected by plaque reduction assay. T cell responses were evaluated by Elispot assay and flow cytometry. Results: We found a 3.38-fold increase in neutralizing antibody titers (Geometric Mean Titer [GMT], 78.69) one month after BNT162b2 booster and maintained at the three months (GMT, 80). However, in the CoronaVac group, significantly lower GMTs than BNT162b2 after 1 month and 3 months (21.44 and 28.44, respectively) indicated the weak immunogenicity of the CoronaVac booster (p<0.001). In the ELISpot assay, IL-2 levels after BNT162b2 were higher than baseline and CoronaVac booster (p<0.001) and IFN-γ levels were significantly higher than baseline (P<0.001). The CD8+CD38+CD69+ and CD4+CD38+CD69+ T cells were stimulated significantly at the 3 month of the BNT162b2 boosters. Conclusion: The neutralizing antibody levels after three months of the BNT162b2 booster were higher than the antibody levels after CoronaVac. On the other hand, specific T cells might contribute to immune protection. By considering the waning immunity, we suggest a new booster dose with BNT162b2 for the countries that already have two doses of primary CoronaVac regimens.
Study of underwater passive Motion Target Analysis (TMA) in revise extend Kalman filter

The method of the revise Extend Kalman Filter (EKF) is used in the problem passive TMA of a constant known depth in three dimensions. The model of motive system is made in the light of measurements of target bearings, elevation and frequency by passive sonar. Pseudo-linear method is used in new information due to nonlinear measurement equation. Then revise EKF equation is gained. In the other hand, data is divided in to groups in adding stability of filter. Simulation shows that this algorithm can gain effective parameter estimation which error covariance curves is reduced rapidly, thus this passive TMA of precise estimation can be realized in this algorithm.
Arc information extraction of CO_2 welding based on time-frequency analysis

In order to study the droplet transfer controlling associated with CO2 welding quality,the method of quadratic time-frequency analysis was used to investigate the signal of arc voltage to obtain the patterns of time-frequency distribution.The further characteristic information,namely energy spectral density and instantaneous frequency estimation of the signal,was obtained on this basis of extraction to the information of time-frequency image during welding process.Experimental results showed that the time-frequency energy distribution of arc welding signal can be studied by means of Choi-Williams distribution analysis.The characteristic information of time and instantaneous frequency in arc physical phenomena such as short circuit and arc broken can be extracted according to the results of time-frequency analysis.There is a different characteristic about instantaneous frequency at singular point,which can be used to recognize the physical phenomenon of the arc.
NT-pro B-type natriuretic peptide, early menopause, and incident heart failure in postmenopausal women of the ARIC study

Abstract Objective: N-Terminal pro B-type Natriuretic Peptide (NT-proBNP), a biomarker of heart failure (HF) has been associated with early menopause. We evaluated the modifying role of early menopause on the association of NT-proBNP with incident HF, and separately for HF subtypes, HF with preserved ejection fraction (HFpEF) and HF with reduced ejection fraction (HFrEF). Methods: We included 4,352 postmenopausal women including 1,174 with early menopause, ages 63.5 ± 5.5 years, without prevalent HF at the Atherosclerosis Risk in Communities study Visit 4. Binary log-transformation was performed for NT-proBNP. Cox proportional hazards models were used to examine the association of NT-proBNP with incident HF, and separately for incident HFpEF and incident HFrEF, testing for effect modification by early menopause and adjusting for HF risk factors. Results: We observed 881 HF events over a mean follow-up of 16.5 years. The interaction terms of NT-proBNP and early menopause were not significant for incident HF (Pinteraction 0.95) and incident HFpEF (Pinteraction 0.17) but were significant for incident HFrEF (Pinteraction 0.03). The adjusted hazard ratios resulting from each doubling of NT-proBNP levels amongst women with and without early menopause were 1.33 (1.20-1.47) and 1.34 (1.24-1.44), respectively, for incident HF; 1.57 (1.34-1.86) and 1.38 (1.24-1.54), respectively, for incident HFpEF; and 1.68 (1.42-1.99) and 1.36 (1.22-1.52), respectively, for incident HFrEF. Conclusions: The association of NT-proBNP with incident HFpEF is similar irrespective of early menopause status. However, the association of NT-proBNP with incident HFrEF is greater among women with early menopause when compared to those without early menopause. Video Summary:http://links.lww. com/MENO/A893.
Ab initio Study of the Electronic and Optical Properties of Stable Boron Sheet

Utilizing first principles calculations within PW91 exchange-correlation method, we investigated a boron sheet that exhibits related electronic properties. The 2dimensional boron sheet is flattened and has an atomic structure where the pair cores of every three ordered hexagons within the hexagonal network are loaded up by extra atoms, which saves the triangular lattice symmetry. The boron sheet takes possession of intrinsic metal properties and the electronic bands are comparable to the bands of the graphene that are close to the Fermi level. The real and imaginary parts of the dielectric function show a metallic or semiconductor behaviour, depending on the electric field direction.
Farmers’ adaptations strategies towards soil salinity effects in agriculture: the interior coast of Bangladesh

ABSTRACT In this study, we critically analyze the general and climate-smart adaptation strategies used by farmers in four sub-districts in southern Bangladesh to address the effects of soil salinity in agriculture. Data were collected from 360 respondents using face-to-face interviews and were analyzed using multiple analyses (variance inflation factor, ordinary least squares, Tukey’s post hoc test). The adaptations used by farmers to manage the impacts of soil salinity in agriculture were significantly influenced by their age, education, family size, farm size, level of contact with agricultural extension department officials, and their training experience. Farmers found adult education programmes particularly useful, since they focused on smart technique(s) rather than traditional approaches for agricultural development. Adaptation was comparatively more common in ‘early adapters’ and ‘early majority’ (slower to adapt) farmers. Our analysis suggests that climate-smart agriculture (CSA) programmes should be implemented in all affected sub-districts and similarly affected parts of the world. Extension workers should provide face-to-face demonstrations to affected farmers and support them with self-help programmes, which can help to attenuate and minimize the effects of soil salinity on agriculture. It will also be important to provide agricultural innovation support to affected farmers to cope with the adverse effects of soil salinity. Effective extension services are key to increasing farmers’ access to innovative information and advice. Key policy insights A philosophy of ‘learning by viewing’ for climate-smart agricultural innovations may encourage them to adopt adaptation strategies to minimize the impacts of soil salinity on agriculture. Training programmes could be offered to farmers by the Department of Agricultural Extension, especially to target innovators and early adopters of climate-smart practices, supporting them with a ‘self-help’ approach. A motivational approach and good communication skills play a vital role when introducing new adaptation strategies. A climate-smart investment plan could identify policy opportunities to further develop agriculture actions to combat climate change. Building resilience to global climate change would help to sustainably increase agricultural productivity and incomes across farming communities.
Resilience and psychosocial factors linked to symptom experience during the menopause transition for women living with HIV*

Abstract Objective: Women living with HIV (WLWH) are commonly symptomatic during perimenopause and menopause (≥1 y without menstruation), however, little is known of risks for symptoms and their timing. We analyzed these unwanted experiences to inform care. Methods: WLWH (≥40 y) in the Canadian HIV Women’s Sexual and Reproductive Health Cohort Study rated midlife experiences for seven symptoms and a symptom composite (from 0 to 21). Timing was categorized into four phases: i) perimenopause (flow in the last year), ii) 1-2 years from final menstrual period (FMP), iii) 2-5 years post-FMP; and iv) >5 years post-FMP. Resilience (standardized out of 100) was assessed based on Wagnild’s Resilience Scale. Univariable/multivariable mixed effects linear regression assessed correlates of symptom intensity by composite score. Results: Among 457 peri-/menopausal women mean age 54.7 (±6.6) over two time points (703 observations), 88% experienced ≥1 mild symptom; 75% were of moderate and 55% severe intensity. The most frequently reported symptoms were joint/muscle stiffness (67%), depressed mood (67%), and hot flashes (57%). After adjusting for reproductive phase, we found that women with greater resilience had fewer/lower intensity symptoms (symptom score 1.37 [2.30 to 0.44] lower; P = 0.004); those with depressive symptoms and recreational drug use (respectively) had more/higher intensity symptoms (scores 1.71 [0.61 to 2.82] [P = 0.002]; 2.89 [2.09 to 3.77] [P<0.001] higher). Symptoms were most intense in perimenopause and declined with increasing menopausal years (P = 0.03). Conclusions: WLWH experiences a high burden of midlife symptoms, decreased by resilience and most intense during perimenopause. Unwanted experiences were linked to psychosocial and behavioral factors. These data encourage HIV providers to adopt a bio-psychosocial approach to midlife management.
Creating and Augmenting Keyboards for Extended Reality with the Keyboard Augmentation Toolkit

This article discusses the Keyboard Augmentation Toolkit (KAT), which supports the creation of virtual keyboards that can be used both for standalone input (e.g., for mid-air text entry) and to augment physically tracked keyboards/surfaces in mixed reality. In a user study, we firstly examine the impact and pitfalls of visualising shortcuts on a tracked physical keyboard, exploring the utility of virtual per-keycap displays. Supported by this and other recent developments in XR keyboard research, we then describe the design, development, and evaluation-by-demonstration of KAT. KAT simplifies the creation of virtual keyboards (optionally bound to a tracked physical keyboard) that support enhanced display—2D/3D per-key content that conforms to the virtual key bounds; enhanced interactivity—supporting extensible per-key states such as tap, dwell, touch, swipe; flexible keyboard mappings that can encapsulate groups of interaction and display elements, e.g., enabling application-dependent interactions; and flexible layouts—allowing the virtual keyboard to merge with and augment a physical keyboard, or switch to an alternate layout (e.g., mid-air) based on need. Through these features, KAT will assist researchers in the prototyping, creation and replication of XR keyboard experiences, fundamentally altering the keyboard’s form and function.
The intensive care management of acute ischaemic stroke

Purpose of review To discuss recent advances in the critical care management of acute ischaemic stroke patients and highlight controversies and consensus. Recent findings Intravenous thrombolysis and endovascular thrombectomy are standard of care reperfusion therapies that have revolutionized the management of acute ischaemic stroke and transformed outcomes for patients. They can now be delivered in extended time windows and to those previously ineligible for intervention based on advanced neuroimaging criteria. Secondary systemic insults, such as hypo- and hypertension, hyperthermia or hyperglycaemia, which can extend the area of ischaemia must also be prevented or corrected to minimize infarct progression. Meticulous blood pressure management is of central importance, particularly in patients that have undergone reperfusion therapies. Neurological deterioration can occur because of infarct extension, haemorrhagic transformation or worsening cerebral oedema. Transcranial Doppler ultrasonography allows bedside, noninvasive evaluation of cerebral haemodynamics and is increasingly used in acute stroke triage, management and recovery prediction. The management of acute ischaemic stroke raises several ethical issues, and shared decision making is essential to ensure outcomes that are compatible with an individual patient's expectations. Summary A bundle of medical, endovascular and surgical strategies implemented by a multidisciplinary team working to locally agreed protocols can improve long-term stroke outcomes.
Gene regulatory evolution in cold-adapted fly populations neutralizes plasticity and may undermine genetic canalization

The relationships between adaptive evolution, phenotypic plasticity, and canalization remain incompletely understood. Theoretical and empirical studies have made conflicting arguments on whether adaptive evolution may enhance or oppose the plastic response. Gene regulatory traits offer excellent potential to study the relationship between plasticity and adaptation, and they can now be studied at the transcriptomic level. Here we take advantage of three closely-related pairs of natural populations of Drosophila melanogaster from contrasting thermal environments that reflect three separate instances of cold tolerance evolution. We measure the transcriptome-wide plasticity in gene expression levels and alternative splicing (intron usage) between warm and cold laboratory environments. We find that suspected adaptive changes in both gene expression and alternative splicing tend to neutralize the ancestral plastic response. Further, we investigate the hypothesis that adaptive evolution can lead to decanalization of selected gene regulatory traits. We find strong evidence that suspected adaptive gene expression (but not splicing) changes in cold-adapted populations are more vulnerable to the genetic perturbation of inbreeding than putatively neutral changes. We find some evidence that these patterns may reflect a loss of genetic canalization accompanying adaptation, although other processes including hitchhiking recessive deleterious variants may contribute as well. Our findings augment our understanding of genetic and environmental effects on gene regulation in the context of adaptive evolution. Significance Statement It is unclear whether adaptive evolution is concordant or discordant with regulatory plasticity, especially for splicing plasticity which is rarely studied. Here we analyzed RNA-seq data from three pairs of natural fly populations that represent separate adaptive evolution to cold climate. We found that adaptive evolution is generally discordant with the ancestral plasticity between cold and warm temperatures for gene expression abundance and splicing. We also investigate the hypothesis that adaptation leads to decanalization of the selected traits. By comparing the expression variance between inbred and outbred samples, we found evidence that adaptation may lead to genetic decanalization for expression abundance but not for splicing. Our study reveals the relationship between adaptation, plasticity and canalization in three instances in nature.
Squash Game Based on Augmented Reality

In this paper, we describe an augmented reality (AR) squash game, which is a squash-style game based on the AR technique. Our system operates based on the 2D–3D projective geometry. In the proposed system, a visual camera takes real-time images of a room that consists of several numbers of walls, and the geometric information of the room image is computed using planar markers, which are attached to the walls. Using the projective geometry and motion data of a ball created artificially, a realistic scene is generated in which a user can interact with a ball that makes realistic motions. A user watches the computer screen that displays the mixed image, and hits the virtual ball using a racket connected to a motion tracker. The ball motion is created based on the parabolic motion equations. Based on these motion data, the ball is created using the OpenGL library, and is overlaid on the real image received from the CCD camera. The position and the motion data of the racket are obtained from a 3D motion tracker. To compute the geometric information of the planes, which act as walls in the images, we compute the projective mapping and estimate the position and orientation of the planes using planar calibration objects.
The past and present of real-time lane detection method in autonomous vehicle system

: Smart cars have been one of the most heated debated issues in the automotive industry for decades. Although various efforts have been made to make cars smart and have the ability to drive themselves, the intention to find the optimal solution has never stopped. In the process, autonomous cars are becoming more and more stable and intelligent, moving towards the ideal of a smart car. This article describes the technologies used in self-driving cars of lane detection and how they have been improved over the last few decades. Two main sections are introduced in this article, traditional methods and deep learning based methods of lane detection.
Stock Market Volatility during COVID-19 Pandemic

The study investigates the response of the stock market to the coronavirus pandemic. The economic consequences of the coronavirus (COVID-19) for the stock market are considerable for a developing country, like Pakistan, which was amongst the list of fifteen countries with the highest number of coronavirus cases in May 2020. The present study is aimed at finding the effect of an increase in the number of confirmed cases of coronavirus on the stock returns in the Pakistan stock market. Additionally, the study investigates the effect of an increase in the number of deaths on stock returns. The results show that an increase in the number of confirmed cases has a significant negative effect on the stock returns. While the increase in the number of deaths does not have a significant effect on the stock returns. The results are in line with the results of Ashraf (2020). The findings are important for the policymakers in formulating policies to safeguard the investors in the stock market during this uncertain time.
A Congestion Control Framework Based on In-Network Resource Pooling

Congestion control has traditionally relied on monitoring packet-level performance (e.g., latency, loss) through feedback signals propagating end-to-end together with various queue management practices (e.g., carefully setting various parameters, such as router buffer thresholds) in order to regulate traffic flow. Due to its end-to-end nature, this approach is known to transfer data according to the path’s slowest link, requiring several RTTs to transmit even a few tens of KB during slow start. In this paper, we take a radically different approach to control congestion, which obviates end-to-end performance monitoring and careful setting of network parameters. The resulting In-Network Resource Pooling Protocol (INRPP) extends the resource pooling principle to exploit in-network resources such as router storage and unused bandwidth along alternative sub-paths. In INRPP, content caches or large (possibly bloated) router buffers are used as a place of temporary custody for incoming data packets in a store and forward manner. Data senders push data in the network and when it hits the bottleneck link, in-network caches at every hop store data in excess of the link capacity; nodes progressively move/send data (from one cache to the next) towards the destination. At the same time alternative sub-paths are exploited to move data faster towards the destination. We demonstrate through extensive simulations that INRPP is TCP friendly, and improves flow completion time and fairness by as much as 50% compared to RCP, MPTCP and TCP, under realistic network conditions.
Assessment of contextualised representations in detecting outcome phrases in clinical trials

Automating the recognition of outcomes reported in clinical trials using machine learning has a huge potential of speeding up access to evidence necessary in healthcare decision-making. Prior research has however acknowledged inadequate training corpora as a challenge for the Outcome detection (OD) task. Additionally, several contextualized representations like BERT and ELMO have achieved unparalleled success in detecting various diseases, genes, proteins, and chemicals, however, the same cannot be emphatically stated for outcomes, because these models have been relatively under-tested and studied for the OD task. We introduce"EBM-COMET", a dataset in which 300 PubMed abstracts are expertly annotated for clinical outcomes. Unlike prior related datasets that use arbitrary outcome classifications, we use labels from a taxonomy recently published to standardize outcome classifications. To extract outcomes, we fine-tune a variety of pre-trained contextualized representations, additionally, we use frozen contextualized and context-independent representations in our custom neural model augmented with clinically informed Part-Of-Speech embeddings and a cost-sensitive loss function. We adopt strict evaluation for the trained models by rewarding them for correctly identifying full outcome phrases rather than words within the entities i.e. given an outcome"systolic blood pressure", the models are rewarded a classification score only when they predict all 3 words in sequence, otherwise, they are not rewarded. We observe our best model (BioBERT) achieve 81.5\% F1, 81.3\% sensitivity and 98.0\% specificity. We reach a consensus on which contextualized representations are best suited for detecting outcomes from clinical-trial abstracts. Furthermore, our best model outperforms scores published on the original EBM-NLP dataset leader-board scores.