Miracle-dz/UniFAR-FTUs huggingface dataset:
Digital Marketing Strategy for Health Food and Beverage Products in a Pandemi Wave

During the Covid-19 pandemic in Indonesia, food and beverage products were the products out of 4 other product sectors purchased by consumers with fast turnover, often called fast-moving consumer goods (FMCG). Products that are excellent during the Covid-19 pandemic are healthy food and drinks. In marketing these products, an appropriate and effective marketing strategy is needed in order to win the competition. Digital marketing strategy. The purpose of this paper is to discuss CRM strategies that can be developed to support OsmarO's digital product business. In addition, this paper also discusses the benefits that can be obtained from applying social media marketing strategies for OsmarO products.
Room-temperature lasing in a single nanowire with quantum dots

The room-temperature lasing of a single nanowire containing 50 quantum dots is demonstrated, paving the way towards ultrasmall lasers with extremely low power consumption for integrated photonic systems. Semiconductor nanowire lasers are promising as ultrasmall, highly efficient coherent light emitters in the fields of nanophotonics, nano-optics and nanobiotechnology1,2. Although there have been several demonstrations of nanowire lasers using homogeneous bulk gain materials3,4,5,6,7,8,9,10,11,12,13,14 or multi-quantum-wells/disks15,16,17, it is crucial to incorporate lower-dimensional quantum nanostructures into the nanowire to achieve superior device performance in relation to threshold current, differential gain, modulation bandwidth and temperature sensitivity. The quantum dot is a useful and essential nanostructure that can meet these requirements18. However, difficulties in forming stacks of quantum dots in a single nanowire hamper the realization of lasing operation. Here, we demonstrate room-temperature lasing of a single nanowire containing 50 quantum dots by properly designing the nanowire cavity and tailoring the emission energy of each dot to enhance the optical gain. Our demonstration paves the way toward ultrasmall lasers with extremely low power consumption for integrated photonic systems.
An online auction mechanism for double time-varying constraints in vehicular edge computing

Real-time resource allocation has become a hot topic in vehicular edge computing environment. However, vehicle equipment with limited computing capability cannot meet the Quality of service of computation intensive and delay sensitive vehicle applications. Moreover, in most studies, the deployment constraints in edge computing and users’ resource demand are static, which is inconsistent with real scenarios. In this paper, an online auction mechanism with double time-varying constraints is proposed to solve the resource allocation problem in a vehicular edge computing environment. Specifically, we first formulate the resource allocation problem between edge computing servers (ECSs) and vehicles as a novel integer programming model with time-varying deployment constraint and time-varying resource demand. Then, we design an online auction mechanism based on heuristics. In the resource allocation algorithm, a matching model and dominant-resource-proportion strategy are adopted to improve the resource utilization and social welfare. Simultaneously, a payment pricing algorithm based on the dichotomy is proposed. Finally, we prove that the online mechanism is individually rational and truthful. The experimental results demonstrate that our online mechanism has higher social welfare and resource utilization than existing research.
Order continuous measures

1. Objective. It is possible to define order convergence on the vector lattice of all continuous functions of compact support on a locally compact topological space. Every measure is a linear form on this vector lattice. The object of this paper is to prove that a measure is such that every set of the first category of Baire has measure zero if and only if the measure is a linear form which is continuous in the order convergence.
A Knowledge Reasoning Model Based on Non-Factoid Information Enhancement

Q&A system plays an increasingly important role in the modern society with information explosion, and knowledge reasoning model (KRM) is the main research content of Q&A system. Existing knowledge reasoning models are mainly divided into text-based information retrieval (IR) and knowledge graph embedding (KGE). KGE is superior to IR in terms of storage and reasoning capabilities for massive factoid information, but lacks the ability to reason non-factoid information, merely focus on the mining of structural information without the semantic information. We proposed a knowledge reasoning model based on non-factoid information enhancement (NFE-KRM) in scenic Q&A. It realizes the KGE integrates semantic information (SIKGE) and the unified semantic embedding space (USES), so that NFE-KRM has the ability to answer both factoid and non-factoid questions. We have used a large number of experiments to prove that SIKGE gets a better performance on Mean Rank and Hits@10. NFE-KRM's F1 score and accuracy on the mixed dataset are both competitive.
Chronic hepatitis B complicated with secondary hemochromatosis was cured clinically: A case report

Abstract Chronic hepatitis B (CHB) often causes iron overload in the liver but rarely causes severe secondary hemochromatosis (SH). A 48-year-old man was infected with CHB via vertical transmission. For 21 years, nonstandard treatment with second-line hepatitis B antiviral drugs has been administered. Repeated abnormalities in the liver transaminase function and continuous low-level replication of the hepatitis B virus (HBV) have been detected. The skin had turned black 5 years back. Biochemical tests and imaging revealed the presence of hemochromatosis. A liver biopsy suggested severe iron overload. Two genetic tests ruled out hereditary hemochromatosis. The patient was diagnosed with SH and treated with 400 ml bloodletting once per week and an iron-chelating agent. After 12 weeks, liver function was normal, and the skin turned white. First, hepatitis B surface antigen (HBsAg) was lost, and HBV DNA was copied at low levels. The patient was diagnosed with an occult hepatitis B infection. HBV DNA was undetectable after 4 weeks of antiviral treatment with tenofovir. Upon reviewing the patient’s medical history, hemochromatosis was believed to be related to CHB with chronic inflammatory damage and no complete virological response. Improvements in hemochromatosis may promote HBsAg disappearance.
Analysis of the possibility of quantum computers and quantum computings for cryptanalysis of modern cryptosystems

На основе использования доступных источников приводится обзор и анализ современных мировых достижений в области квантовых вычислений и построения квантового компьютера. Проводится анализ угроз безопасности относительно симметричных и асимметричных криптосистем в случае применения методов квантового криптоанализа. Приводятся оценки пространственных и временных сложностей, которые нужно достигать для успешного осуществления квантового криптоанализа.
Neural timescales reflect behavioral demands in freely moving rhesus macaques

Previous work has demonstrated remarkably reproducible and consistent hierarchies of neural timescales across cortical areas at rest. The question arises how such stable hierarchies give rise to adaptive behavior that requires flexible adjustment of temporal coding and integration demands. Potentially, this previously found lack of variability in the hierarchical organization of neural timescales could be a reflection of the structure of the laboratory contexts in which they were measured. Indeed, computational work demonstrates the existence of multiple temporal hierarchies within the same anatomical network when the input structure is altered. We posit that unconstrained behavioral environments where relatively little temporal demands are imposed from the experimenter are an ideal test bed to address the question of whether the hierarchical organization and the magnitude of neural timescales reflect ongoing behavioral demands. To tackle this question, we measured timescales of local field potential activity while rhesus macaques were foraging freely in a large open space. We find a hierarchy of neural timescales that is unique to this foraging environment. Importantly, although the magnitude of neural timescales generally expanded with task engagement, the brain areas’ relative position in the hierarchy was stable across the recording sessions. Notably, the magnitude of neural timescales monotonically expanded with task engagement across a relatively long temporal scale spanning the duration of the recording session. Over shorter temporal scales, the magnitude of neural timescales changed dynamically around foraging events. Moreover, the change in the magnitude of neural timescales contained functionally relevant information, differentiating between seemingly similar events in terms of motor demands and associated reward. That is, the patterns of change were associated with the cognitive and behavioral meaning of these events. Finally, we demonstrated that brain areas were differentially affected by these behavioral demands - i.e., the expansion of neural timescales was not the same across all areas. Together, these results demonstrate that the observed hierarchy of neural timescales is context-dependent and that changes in the magnitude of neural timescales are closely related to overall task engagement and behavioral demands.
Cultured Mesenchymal Cells from Nasal Turbinate as a Cellular Model of the Neurodevelopmental Component of Schizophrenia Etiology

Study of the neurodevelopmental molecular mechanisms of schizophrenia requires the development of adequate biological models such as patient-derived cells and their derivatives. We previously used cell lines with neural progenitor properties (CNON) derived from superior or middle turbinates of patients with schizophrenia and control groups to study gene expression specific to schizophrenia. In this study, we compared single cell-RNA seq data from two CNON cell lines, one derived from an individual with schizophrenia (SCZ) and the other from a control group, with two biopsy samples from the middle turbinate (MT), also from an individual with SCZ and a control. In addition, we compared our data with previously published data from olfactory neuroepithelium (1). Our data demonstrated that CNON originated from a single cell type which is present both in middle turbinate and olfactory neuroepithelium. CNON express multiple markers of mesenchymal cells. In order to define relatedness of CNON to the developing human brain, we also compared CNON datasets with scRNA-seq data of embryonic brain (2) and found that the expression profile of CNON very closely matched one of the cell types in the embryonic brain. Finally, we evaluated differences between SCZ and control samples to assess usability and potential benefits of using single cell RNA-seq of CNON to study etiology of schizophrenia.
Polynomial foldings and rank of tensors

We review facts about rank, multilinear rank, multiplex rank and generic rank of tensors as well as folding of a tensor into a matrix of multihomogeneous polynomials. We de(cid:12)ne the new concept of folding rank of tensors and compare its properties to other ranks. We review the concept of determinantal schemes associated to a tensor. Then we de(cid:12)ne the new concept of a folding generic tensor meaning that all its determinantal schemes behave generically. Our main theorem states that for \small" 3- tensors, any folding generic tensor has generic rank, and the reverse does not always hold. 13C40, 14M12, 15A69.
Sensing the rainbow: genetic and physiological responses to light quality in Ostreococcus, an ecologically important photosynthetic picoeukaryote

Phytoplankton is exposed to dramatic variations in light quality as it moves up and down the water column or encounters the presence of sediments in the water. We investigated the potential impact on Ostreococcus, a key marine photosynthetic picoeukaryote, by analysing changes in its transcriptome, pigment content and photophysiology after acclimation to monochromatic red, green or blue light. The clade B species RCC809, isolated from the deep Atlantic Ocean, responded to blue light by accelerating cell division at the expense of storage reserves, and by increasing the relative level of blue-light absorbing pigments. In contrast, it responded to red and green light by increasing its potential for photoprotection. In contrast, the clade A species OTTH0595, which originates from a shallow water environment, showed no difference in photosynthetic properties and minor differences in carotenoid contents between light qualities. These results demonstrate that light quality can have a major influence on the physiology of eukaryotic phytoplankton, and suggest that different light quality environments can drive selection for diverse patterns of responsiveness and environmental niche partitioning. Highlight We characterise the effects of light quality on the transcriptome and photophysiology of Ostreococcus, a photosynthetic picoeukaryote, and show that responses are distinct between two ecotypes originating from different environments.
TESTING TIME REVERSAL SYMMETRY USING MOLECULES

Some years ago while on sabbatical leave in Oxford I discussed with George Series the experiments in my group to measure the electric dipole moments of the proton and electron using the magnetic resonance in molecules. He asked about the current interest in this kind of measurement and he wanted to find out why we use molecules rather than something simple like the hydrogen atom. After about an hour, George was satisfied with the answers I gave him, but on several occasions after that, he encouraged me to write up some notes about all this. Well George, here they are.
Lineage-specific dynamics of erasure of X-upregulation during inactive-X reactivation

In mammals, sex chromosome dosage is compensated through X-chromosome inactivation and active-X upregulation. It is believed that during early development, X-chromosome inactivation and active X upregulation happen in a highly coordinated fashion. However, such coordination between two X-chromosomes in other developmental contexts remains unexplored. Here, we have profiled the coordination between two X-chromosomes in female cells in different developmental contexts and cell types: pre-implantation embryos, embryonic epiblast cells, iPSC reprogramming, germ cell reprogramming, B-cell, and extra-embryonic endoderm stem (XEN) cells. Interestingly, we found that two X-chromosomes in female cells are not always coordinated; instead, it happens in a lineage-specific manner. Specially, while embryonic mouse epiblast cells, iPSC undergo erasure of X-upregulation upon reactivation of the inactive X, germ cells do not. Importantly, we show that the erasure of X-upregulation in epiblast or iPSC is potentially mediated via undifferentiated embryonic transcription Factor 1 (UTF1), which is absent or lowly expressed in late germ cells and therefore, germ cells are unable to erase upregulation. Moreover, we found that partial reactivation of the inactive X is insufficient to drive the erasure of upregulation globally, nor from their counterparts on the active X in XEN and B-cells. Finally, through a phenomenological mathematical model, we show that cross-inhibition between two X-chromosomes can reproduce the dynamics of reactivation and erasure of upregulation. Altogether, our study provides insight into the coordination between two X-chromosomes in female cells in different developmental contexts and related mechanistic aspects.
Dynamic remodelling of cadherin contacts in embryonic mesenchymal cells during differential cell migration

A fundamental aspect of morphogenesis is the capacity of cells to actively exchange neighbours while maintaining the overall cohesion of the tissue. These cell rearrangements require the dynamic remodelling of cadherin cell adhesions. Many studies have examined this process in tissues where it is driven by the joint action of cell protrusions and actomyosin contraction along the shrinking junction. However, cell rearrangements can also occur through differential migration. This mode of cell rearrangement, characteristic of mesenchymal tissues, is much less well understood. Here, we explore the prototypical case of the gastrulating Xenopus prechordal mesoderm, and provide the first detailed analysis at how cadherin contacts are remodelled and eventually disrupted in this type of tissue. Using a reductionist approach, including analysis of single contacts using a dual pipette aspiration setup, we unveil two concurrent mechanisms. Most cadherins are removed via “peeling”, i.e. disruption of the trans bonds and lateral diffusion out of the contact. In parallel, a remnant of cadherins concentrates at the shrinking contact, which is ultimately resolved by breakage of the link with the actin cytoskeleton, showing that the weakest link shifts at different stages of contact remodelling. Additionally, we observe recruitment of myosin peripheral to the shrinking contact, which influences the efficiency of the final detachment. Finally, manipulation of cortical tension indicates that the process is sensitive to the magnitude and orientation of the forces applied on the contact, revealing another key relationship between cell-cell adhesion and the cortical cytoskeleton. This study unravels a new modality of cell contact dynamics, which is likely to be widely relevant for highly migratory mesenchymal tissues.
Interpretable spatial cell learning enhances the characterization of patient tissue microenvironments with highly multiplexed imaging data

Multiplexed imaging technologies enable highly resolved spatial characterization of cellular environments. However, exploiting these rich spatial cell datasets for biological insight is a considerable analytical challenge. In particular, effective approaches to define disease-specific microenvironments on the basis of clinical outcomes is a complex problem with immediate pathological value. Here we present InterSTELLAR, a geometric deep learning framework for multiplexed imaging data, to directly link tissue subtypes with corresponding cell communities that have clinical relevance. Using a publicly available breast cancer imaging mass cytometry dataset, InterSTELLAR allows simultaneous tissue type prediction and interested community detection, with improved performance over conventional methods. Downstream analyses demonstrate InterSTELLAR is able to capture specific pathological features from different clinical cancer subtypes. The method is able to reveal potential relationships between these regions and patient prognosis. InterSTELLAR represents an application of geometric deep learning with direct benefits for extracting enhanced microenvironment characterization for multiplexed imaging of patient samples.
Basal forebrain activity predicts functional degeneration in the entorhinal cortex and decreases with Alzheimer’s Disease progression

BACKGROUND AND OBJECTIVES Recent models of Alzheimer’s Disease (AD) suggest the nucleus basalis of Meynert (NbM) as the origin of structural degeneration followed by the entorhinal cortex (EC). However, the functional properties of NbM and EC regarding amyloid-β and hyperphosphorylated tau remain unclear. METHODS We analyzed resting-state (rs)fMRI data with CSF assays from the Alzheimer’s Disease Neuroimaging Initiative (ADNI, n=71) at baseline and two years later. RESULTS At baseline, local activity, as quantified by fractional amplitude of low-frequency fluctuations (fALFF), differentiated between normal and abnormal CSF groups in the NbM but not EC. Further, NbM activity linearly decreased as a function of CSF ratio, resembling the disease status. Finally, NbM activity predicted the annual percentage signal change in EC, but not the reverse, independent from CSF ratio. DISCUSSION Our findings give novel insights into the pathogenesis of AD by showing that local activity in NbM is affected by proteinopathology and predicts functional degeneration within the EC.
The precedence effect for noise bursts of different bandwidths. II. Comparison of model algorithms

In this investigation, different model algorithms were tested for their ability to simulate the precedence effect for ongoing (non-impulsive) noise-bursts of different bandwidths (100 Hz, 400 Hz and 800 Hz). The psychoacoustical reference data—in which the perceived lateral position of a noise burst (200-ms duration, 20-ms cos 2 -ramps, 500-Hz center frequency) in the presence of one reflection (inter-stimulus interval: 0.0 ms-0.4 ms) was determined—were taken from a preceding paper on this investigation. It is shown that models which simulate the precedence effect by using the special characteristics of the auditory periphery or by focusing on the spectral dominance region fail when stimuli of longer duration than clicks are used, while a modified Lindemann model still shows satisfactory results. Furthermore, it was found that the trading ratio of ITDs and ILDs can be assumed to be constant for the stimuli tested. A discounting of ITD cues, as was found by Rakerd and Hartmann (1985), was not observed for the type of stimuli tested here. Instead, a discounting of the precedence effect occurred for some of the listeners when the bandwidth of the signals was very narrow. In the model simulation, it was not necessary to consider cross-frequency-band interaction like the second coincidence weighting of Stern et al. (1988), and it was sufficient to estimate the average of the outputs of the involved frequency bands.
Mass spectrometry and machine learning in the identification of COVID-19 biomarkers

Identifying specific diagnostic and prognostic biological markers of COVID-19 can improve disease surveillance and therapeutic opportunities. Mass spectrometry combined with machine and deep learning techniques has been used to identify pathways that could be targeted therapeutically. Moreover, circulating biomarkers have been identified to detect individuals infected with SARS-CoV-2 and at high risk of hospitalization. In this review, we have surveyed studies that have combined mass spectrometry-based omics techniques (proteomics, lipdomics, and metabolomics) and machine learning/deep learning to understand COVID-19 pathogenesis. After a literature search, we show 42 studies that applied reproducible, accurate, and sensitive mass spectrometry-based analytical techniques and machine/deep learning methods for COVID-19 biomarker discovery and validation. We also demonstrate that multiomics data results in classification models with higher performance. Furthermore, we focus on the combination of MALDI-TOF Mass Spectrometry and machine learning as a diagnostic and prognostic tool already present in the clinics. Finally, we reiterate that despite advances in this field, more optimization in the analytical and computational parts, such as sample preparation, data acquisition, and data analysis, will improve biomarkers that can be used to obtain more accurate diagnostic and prognostic tools.
A review of penicillin binding protein and group A Streptococcus with reduced-β-lactam susceptibility

With the widespread use of antibiotics, antimicrobial resistance (AMR) has become a global problem that endangers public health. Despite the global high prevalence of group A Streptococcus (GAS) infections and the global widespread use of β-lactams, β-lactams remain the first-line treatment option for GAS infection. β-hemolytic streptococci maintain a persistent susceptibility to β-lactams, which is an extremely special phenomenon in the genus Streptococci, while the exact current mechanism is not known. In recent years, several studies have found that the gene encoding penicillin binding protein 2X (pbp2x) is associated with GAS with reduced-β-lactam susceptibility. The purpose of this review is to summarize the current published data on GAS penicillin binding proteins and β-lactam susceptibility, to explore the relationship between them, and to be alert to the emergence of GAS with reduced susceptibility to β-lactams.