Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Comparison: Relation Columns for Few-Shot Learning

Few-shot deep learning is a topical challenge area for scaling visual recognition to open-ended growth in the space of categories to recognise. A promising line work towards realising this vision is deep networks that learn to match queries with stored training images. However, methods in this paradigm usually train a deep embedding followed by a single linear classifier. Our insight is that effective general-purpose matching requires discrimination with regards to features at multiple abstraction levels. We therefore propose a new framework termed Deep Comparison Network(DCN) that decomposes embedding learning into a sequence of modules, and pairs each with a relation module. The relation modules compute a non-linear metric to score the match using the corresponding embedding module's representation. To ensure that all embedding module's features are used, the relation modules are deeply supervised. Finally generalisation is further improved by a learned noise regulariser. The resulting network achieves state of the art performance on both miniImageNet and tieredImageNet, while retaining the appealing simplicity and efficiency of deep metric learning approaches.
Conserved Composition of Nod Factors and Exopolysaccharides Produced by Different Phylogenetic Lineage Sinorhizobium Strains Nodulating Soybean

The structural variation of symbiotic signals released by rhizobia determines the specificity of their interaction with legume plants. Previous studies showed that Sinorhizobium strains from different phylogenetic lineages had different symbiotic performance on certain cultivated soybeans. Whether they released similar or different symbiotic signals remained unclear. In this study, we compared their nod and exo gene clusters and made a detailed structural analysis of Nod factors and EPS by ESI-MS/MS and two dimensions NMR. Even if there are some differences among nod or exo gene clusters; they produced much conserved Nod factor and EPS compositions. The Nod factors consist of a cocktail of β-(1, 4)-linked tri-, tetra-, and pentamers of N-acetyl-D-glucosamine (GlcNAc). The C2 position on the non-reducing terminal end is modified by a lipid chain that contains 16 or 18 atoms of carbon–with or without unsaturations-, and the C6 position on the reducing residue is decorated by a fucose or a 2-O-methylfucose. Their EPS are composed of glucose, galactose, glucuronic acid, pyruvic acid in the ratios 5:1:2:1 or 6:1:2:1. These findings indicate that soybean cultivar compatibility of Sinorhizobium strains does not result from Nod factor or EPS structure variations. The structure comparison of the soybean microbionts with other Sinorhizobium strains showed that Nod factor structures of soybean microbionts are much conserved, although there are no specific genes shared by the soybean microsymbionts. EPS produced by Sinorhizobium strains are different from those of Bradyrhizobium. All above is consistent with the previous deduction that Nod factor structures are related to host range, while those of EPS are connected with phylogeny.
Development and Implementation of the Model for Sales Volume Forecasting for the Brewing Company

The success of the company rests on its ability to manage flexible market offerings and sales volume by meeting the needs of the customer. Therefore, development of the effective planning of the sales based on the accurate forecast and marketing strategy is paramount for the companies. This paper is discussing the research results conducted for "Beer of Yerevan" Closed Joint-Stock Company (CJSC). The results are presented after conducting correlation-regression and Fourier analyses, which allow us to forecast the production and retail sales for the brewing company. This model could be replicated and applied to any brewing company with the input of the appropriate parameters. Recommendations will help to formulate strategy and develop a management system that ties together company strategy and execution tools. The outcome will be enhanced competitiveness and increased efficiency of the brewing companies
Bayesian Modeling of Intersectional Fairness: The Variance of Bias

Intersectionality is a framework that analyzes how interlocking systems of power and oppression affect individuals along overlapping dimensions including race, gender, sexual orientation, class, and disability. Intersectionality theory therefore implies it is important that fairness in artificial intelligence systems be protected with regard to multi-dimensional protected attributes. However, the measurement of fairness becomes statistically challenging in the multi-dimensional setting due to data sparsity, which increases rapidly in the number of dimensions, and in the values per dimension. We present a Bayesian probabilistic modeling approach for the reliable, data-efficient estimation of fairness with multi-dimensional protected attributes, which we apply to two existing intersectional fairness metrics. Experimental results on census data and the COMPAS criminal justice recidivism dataset demonstrate the utility of our methodology, and show that Bayesian methods are valuable for the modeling and measurement of fairness in an intersectional context.
Signaling in Online Retail: Efficacy of Public Signals

With the rapid growth of online retail, a number of services have arisen that provide customers with information about price history, product availability, demand, etc., enabling them to strategically time their purchases to obtain a better price. For example, services like Kayak inform a user whether the price of an airline ticket is likely to fall in the future. While a user of such a service may choose to wait for the price to decrease, she risks the product going out-ofstock and becoming unavailable. Without the availability of demand and inventory information, a customer must rely on her beliefs to optimally make this trade-off between a better price and the risk of a stock-out. Online retailers, on the other hand, would prefer customers not strategize the timing of their purchase decisions since this may lead to lower revenue. Such online retailers have better estimates of the demand and inventory of their products, and to induce customers to purchase, they may let customers know when an item has low inventory. Some retailers, such as Amazon, give the exact number of items remaining when the inventory is low. Others just print “low stock” to encourage customers to buy the item sooner, but rarely do they tell customers exactly how low “low stock” implies. If a firm says all items have low inventory, then customers will simply ignore the warning altogether. This leads to a natural question: how can a retailer credibly communicate inventory and demand information to customers to maximize its expected revenue? In this paper, we consider the setting where a retailer seeks to sell their inventory of an item that will drop in price. A common example of this is fashion, where summer wears are sold in mass clearance sales after autumn arrives. In particular, we consider a two period model, where prices are high the first time period and low the second, and customers who arrive at time 1 decide whether to buy the item right away or wait to buy in the next time period. The firm sends
Reevaluation of the Kidney Donor Risk Index (KDRI).

BACKGROUND The Kidney Donor Risk Index (KDRI) is a score applicable to deceased kidney donors which reflects relative graft failure risk associated with deceased donor characteristics. The KDRI is widely used in kidney transplant outcomes research. Moreover, an abbreviated version of KDRI is the basis, for allocation purposes, of the "top 20%" designation for deceased donor kidneys. Data upon which the KDRI model was based used kidney transplants performed between 1995 and 2005. Our purpose in this report was to evaluate the need to update the coefficients in the KDRI formula, with the objective of either (a) proposing new coefficients or (b) endorsing continued used of the existing formula. METHODS Using data obtained from the Scientific Registry of Transplant Recipients (SRTR), we analyzed n=156,069 deceased donor adult kidney transplants occurring from 2000 to 2016. Cox regression was used to model the risk of graft failure. We then tested for differences between the original and updated regression coefficients, and compared the performance of the original and updated KDRI formulas with respect to discrimination and predictive accuracy. RESULTS In testing for equality between the original and updated KDRIs, few coefficients were significantly different. Moreover, the original and updated KDRI yielded very similar risk discrimination and predictive accuracy. CONCLUSIONS Overall, our results indicate that the original KDRI is robust and is not meaningfully improved by an update derived through modeling analogous to that originally employed.
Combatting mucosal melanoma: recent advances and future perspectives

Mucosal melanomas are a rare subtype of melanoma and are associated with a particularly poor prognosis. Due to the rarity of the diagnosis, and the pace with which the management of cutaneous melanoma has evolved over recent years, there is little good evidence to guide management and evidence-based clinical guidelines are still in development in the UK. In this review we provide an overview of the management of mucosal melanoma, highlighting the critical differences between cutaneous and mucosal melanomas, before examining recent advances in the systemic treatment of this disease and likely future directions.
The association of XRCC1 polymorphism with osteosarcoma risk, clinicopathologic features, and prognosis in a Chinese Han population

Introduction The association of single-nucleotide polymorphisms at X-ray repair cross-complementing group-1 (XRCC1) with osteosarcoma (OS) development has not been fully clear to date. The aim of the present study is to evaluate the association of XRCC1 polymorphisms with risk, clinicopathologic features, and prognosis in Chinese OS patients. Methods A total of 146 patients with primary OS and 248 age- and gender-matched controls were included in the present study. The frequencies of four XRCC1 polymorphisms (rs25487, rs1799782, rs25489, and rs3213245) were determined between OS patients and controls. The association of XRCC1 polymorphism with clinicopathologic characteristics, prognosis, and XRCC1 expression was further evaluated. Results Compared with TT genotype, individuals carrying the minor C allele (TC+ CC) of rs3213245 had significantly increased risk of OS development (OR =1.83, 95% CI 1.14–3.00). OS patients carrying TC genotype and C allele at rs3213245 were more likely to be with larger tumor size and metastasis. Survival analysis demonstrated that OS patients carrying C allele (TC + CC) at rs3213245 had shorter survival time than those with TT genotype. The T to C substitution at rs3213245 could decrease XRCC1 gene transcriptional activity in vitro. XRCC1 mRNA and protein expression levels were lower in OS patients carrying TC or CC genotype at rs3213245. Besides, no significant association of rs25487, rs1799782, and rs25489 with OS was observed. Conclusion In conclusion, these findings revealed that XRCC1 rs3213245 polymorphism was associated with increased risk of OS, which could affect XRCC1 expression in vitro and in vivo.
Telerehabilitation Combined Speech-Language and Cognitive Training Effectively Promoted Recovery in Aphasia Patients

The present study investigated the efficacy of a computerized intervention for aphasia that combined speech-language and cognitive training delivered on an inpatient unit or via telerehabilitation to discharged patients. Forty inpatient and discharged aphasia patients were recruited and randomly assigned to the training group or control group. Computerized speech-language and cognitive training was provided for 14 days to the inpatients and 30 days to the discharged patients. Compared with the control group, training group had significantly more improved language function as assessed by the Western Aphasia Battery (WAB) and practical communication skills as assessed by the Communicative Abilities in Daily Living Test (CADL). It was also found that the positive effects of the computerized training when delivered via telerehabilitation to the discharged group were smaller than the effects when delivered on the inpatient unit. The results suggest that combining speech-language and cognitive training program is efficacious in promoting the recovery of patients with aphasia, both inpatients and discharged patients, and that the program works even when administered from a remote location.
ChainGAN: A sequential approach to GANs

We propose a new architecture and training methodology for generative adversarial networks. Current approaches attempt to learn the transformation from a noise sample to a generated data sample in one shot. Our proposed generator architecture, called $\textit{ChainGAN}$, uses a two-step process. It first attempts to transform a noise vector into a crude sample, similar to a traditional generator. Next, a chain of networks, called $\textit{editors}$, attempt to sequentially enhance this sample. We train each of these units independently, instead of with end-to-end backpropagation on the entire chain. Our model is robust, efficient, and flexible as we can apply it to various network architectures. We provide rationale for our choices and experimentally evaluate our model, achieving competitive results on several datasets.
An Efficient Approach to Informative Feature Extraction from Multimodal Data

One primary focus in multimodal feature extraction is to find the representations of individual modalities that are maximally correlated. As a well-known measure of dependence, the Hirschfeld-Gebelein-Rényi (HGR) maximal correlation be-´ comes an appealing objective because of its operational meaning and desirable properties. However, the strict whitening constraints formalized in the HGR maximal correlation limit its application. To address this problem, this paper proposes Soft-HGR, a novel framework to extract informative features from multiple data modalities. Specifically, our framework prevents the “hard” whitening constraints, while simultaneously preserving the same feature geometry as in the HGR maximal correlation. The objective of Soft-HGR is straightforward, only involving two inner products, which guarantees the efficiency and stability in optimization. We further generalize the framework to handle more than two modalities and missing modalities. When labels are partially available, we enhance the discriminative power of the feature representations by making a semi-supervised adaptation. Empirical evaluation implies that our approach learns more informative feature mappings and is more efficient to optimize.
Benign paroxysmal positional vertigo in the elderly: current insights

Balance disorders, unsteadiness, dizziness and vertigo in the elderly are a significant health problem, needing appropriate treatment. One third of elderly patients with vertigo were diagnosed with benign paroxysmal positional vertigo (BPPV), the most common cause of dizziness in both primary care specialist Neurology and Ear Nose Throat settings. BPPV presents a specific paroxysmal positional nystagmus which can be obtained using the appropriate diagnostic positional test and can be treated effectively using specific therapeutic maneuvers. This review presents current insights into the diagnostic, pathogenetic and therapeutic aspects of BPPV in the elderly. BPPV in older patients does not differ significantly from BPPV in younger patients, with regard to pathogenesis, diagnosis and treatment. However, in older patients, its prevalence is higher and it responds less effectively to treatment, having a tendency for recurrence. Specific issues which should be considered in the elderly are: 1) difficulty in obtaining an accurate history; 2) difficulty in performing the diagnostic and therapeutic maneuvers, which should be executed with slow and gentle movements and extremely cautiously to avoid any vascular or orthopedic complications; and 3) the relation between BPPV and falls.
Sources of stress and worry in the development of stress-related mental health problems: A longitudinal investigation from early- to mid-adolescence

ABSTRACT Background and Objectives: Stress and stress-related mental health complaints are common and increasing among adolescents, especially girls. Identifying typical sources of stress as well as central intervention targets is an important effort in the development of effective prevention and treatment protocols. This study investigated worry as potential mediator in the development of mental health problems in response to common stressors in adolescence. We also examined to what sources adolescents ascribe their stress over the years from the 7th through the 9th grade. Design: Prospective cohort study. Methods: Self-reported subjective stressor load, worry, anxiety and depressive symptoms were assessed in a sample of Swedish 7th graders (N = 1137; 46% girls, mean age 13.2) with follow-up assessments one and two years later. Results: School was the most common source of stress across all time-points, with girls reporting considerable more stress than boys. Worry mediated the relationship between overall stressor load and depressive symptoms and anxiety over time and was not moderated by gender. Conclusions: Worry may be an important target in stress prevention and efforts to prevent stress-related problems would benefit from focusing on early adolescence as especially school stress is already relatively common in grade 7.
A Unique Human Immunoglobulin Heavy Chain Variable Domain-Only CD33 CAR for the Treatment of Acute Myeloid Leukemia

Acute myeloid leukemia (AML) remains a challenging pediatric and adult disease. Given the elevated expression of the CD33 antigen on leukemic blasts, therapeutic approaches to AML now feature the approved antibody drug conjugate (Mylotarg, GO) and investigational CART cell approaches incorporating CD33-binding domains derived from humanized scFvs. We designed a functional chimeric antigen receptor utilizing a human targeting sequence, derived from a heavy chain variable domain, termed CAR33VH. Lentiviral-based expression vectors which encoded CAR constructs incorporating the novel binding domain (CAR33VH), or the My96 scFv control binder (My96CAR) in frame with a CD8 hinge and transmembrane domain, a 4-1BB costimulatory domain and a CD3 zeta activation domain, were transduced into primary human CD4+ and CD8+ T cells, and CAR expression was confirmed by flow cytometry. CAR33VH, similar to My96CAR, demonstrated robust and specific cytotoxicity in short-term and long-term co-incubation killing assays against CD33+ AML lines. In overnight cytokine release assays in which CAR T cells were challenged with the CD33+ tumor cells HL-60, MOLM-14 and KG-1a, CAR33VH elicited IFN-gamma, TNF-alpha and IL-2. This was seen with CD33+ cell lines, but not when CAR T were cultured alone. Studies with a CD33− cell line engineered to stably express the full length CD33 variant 1, or the naturally occurring CD33 splice variant 2, revealed that both CAR33VH and My96CAR, target the V domain of CD33, suggesting a similar therapeutic profile. Colony-formation assays utilizing peripheral blood CD34+ hematopoietic stem cells treated with CAR33VH, My96CAR, or with an untransduced T cell control, yielded similar numbers of BFU-E erythroid and CFU-GM myeloid colonies, suggesting a lack of CAR-related overt toxicity. In an in vivo AML model, NSG mice engrafted with MOLM-14 cells stably expressing firefly luciferase, both CAR33VH and CARMy96 efficiently eliminated tumors. In conclusion, we demonstrate for the first time the feasibility and efficacy of employing human variable domain-only binder derived from a phage display library in an anti-AML CAR design. CAR33VH, comprised of a human heavy-chain variable fragment-only antigen binding domain, was efficient in tumor killing in vitro and in vivo, and showed comparable functionality to the scFv-based My96CAR.
Comparison of practical application steps of the previously used adrenaline auto injector in Turkey (EpiPen) and the currently available adrenaline auto injector (Penepin): a multi-center study.

Aim It has been shown by a great number of studies that the correct use of adrenaline auto injectors prescribed to patients with anaphylaxis is associated with the design of the auto injector, in addition to training. The aim of this study was to compare the skills of adults in using two different auto injectors prescribed to patients with anaphylaxis. Material and Methods Parents of patients aged between 1 and 18 years who referred to allergy outpatients were included in the study. Results A total of 630 volunteers from nine centers were included in the study. Four hundred fifty-seven (72.5%) of the participants were females and 235 (37.3%) were undergraduates. The rate of showing all the steps of auto injector trainers correctly by the participants was found as (60.2%) (n=379) for EpiPen and 42.9% (n=270) for Penepin (p<0.001). The most frequent mistake with both auto injector trainers was the step of "place appropriate injection tip into outer thigh/press the trigger so it clicks. " When the preferences of the volunteers were asked after training and application, 527 (83.7%) chose EpiPen, stating that it was easier and simpler to use. Conclusions Our study showed that the correct usage rates of both adrenaline auto injectors were much lower than expected and there could be mistakes in the application of both. It could be appropriate to make improvements in the design of Penepin, which is still the only available adrenaline auto injector in Turkey, such that its application steps will be simpler and quicker.
Clinical and virological properties of hepatitis C virus genotype 4 infection in patients treated with different direct-acting antiviral agents

Background The efficacy of direct-acting antivirals (DAAs) depends on the hepatitis C virus (HCV) genotype 4 (GT4) subtype which are used in the treatment of HCV. We aimed to retrospectively investigate the baseline prevalence of HCV NS5A and NS5B polymorphisms and their impact on virological outcome in GT4-infected patients treated with various DAA regimens. Patients and methods Available plasma samples from HCV GT4-infected patients treated with different DAA regimens were analyzed at baseline and after treatment failure, where applicable. Sanger sequencing of patient-derived NS5A and NS5B regions was performed on all available samples, while ultradeep pyrosequencing (UDPS) of NS5A and NS5B regions was performed only on samples from treatment failures at different time points. Results Sustained virological response (SVR) was achieved by 96% (48/50) of patients. Of 16 patients with baseline NS5A sequence, polymorphisms at amino acid positions associated with drug resistance were detected only at position 58: P58 (69.2%) and T58 (30.8%). Of 21 patients with baseline NS5B sequence, N142S was detected only in the two treatment failures, both with GT4d were treated with sofosbuvir (SOF)-based regimens, suggesting a potential involvement in SOF efficacy. Two patients (patient 1 [Pt1] and patient 2 [Pt2]) relapsed. In Pt1, NS5A-T56I and NS5A-Y93H/S emerged. In Pt2, NS5A-L28F emerged and a novel NS5B resistance-associated substitution (RAS), L204F, representing 1.5% of the viral population at baseline, enriched to 71% and 91.6% during and after treatment failure, respectively. UDPS of NS5B from Pt2 indicated a mixed infection of approximately 1:5, GT1a:GT4d, at baseline and GT4d during failure. Phylogenetic analysis of NS5A sequences indicated no clustering of HCV strains from patients achieving SVR vs patients who relapsed. The mean genetic distance in NS5A sequences was 5.8%, while a lower genetic distance (3.1%) was observed in NS5B sequences. Conclusion Results from these analyses confirm the importance of UDPS in the analysis of viral quasispecies variability and the identification of novel RASs potentially associated with DAA treatment failure in HCV GT4-infected patients.