Relevance-based Word Embedding

Learning a high-dimensional dense representation for vocabulary terms, also known as a word embedding, has recently attracted much attention in natural language processing and information retrieval tasks. The embedding vectors are typically learned based on term proximity in a large corpus. This means that the objective in well-known word embedding algorithms, e.g., word2vec, is to accurately predict adjacent word(s) for a given word or context. However, this objective is not necessarily equivalent to the goal of many information retrieval (IR) tasks. The primary objective in various IR tasks is to capture relevance instead of term proximity, syntactic, or even semantic similarity. This is the motivation for developing unsupervised relevance-based word embedding models that learn word representations based on query-document relevance information. In this paper, we propose two learning models with different objective functions; one learns a relevance distribution over the vocabulary set for each query, and the other classifies each term as belonging to the relevant or non-relevant class for each query. To train our models, we used over six million unique queries and the top ranked documents retrieved in response to each query, which are assumed to be relevant to the query. We extrinsically evaluate our learned word representation models using two IR tasks: query expansion and query classification. Both query expansion experiments on four TREC collections and query classification experiments on the KDD Cup 2005 dataset suggest that the relevance-based word embedding models significantly outperform state-of-the-art proximity-based embedding models, such as word2vec and GloVe.Comment: to appear in the proceedings of The 40th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR '17

Author Correction: Intensified summer monsoon and the urbanization of Indus Civilization in northwest India.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.NERC (NE/H011463/1

Reverse-flow anterolateral thigh flap for knee soft-tissue reconstruction: case report

The reconstruction of the injured tissue around the knee is a complex procedure for the plastic and orthopaedic surgeon. The objective is to provide an acceptable function and aesthetic result. Successful wound management includes meticulous debridement, planning and proper execution of the surgical procedure. An 11-year-old male patient with a right patellar fracture using an anterolateral thigh flap with reverse flow to cover the skin defect. For such purposes, the reverse flow anterolateral flap is an effective, trustworthy and well-documented option. The correct obtaining and implantation of the flap reduces the morbidity of the donor site, offers options in size and design, an adequate length of the pedicle and the possible combination with the fascia lata in case it is required. The versatility of the reverse flow anterolateral flap makes it a possible therapeutic alternative in reconstructive surgery since it is aesthetic and functional for the reconstruction of tissue near the knee joint

A headspace solid-phase microextraction method of use in monitoring hexanal and pentane during storage: Application to liquid infant foods and powdered infant formulas

The determination of two secondary lipid oxidation compounds (hexanal and pentane) in liquid infant foods using a headspace solid-phase microextraction gas chromatographic (HS-SPME-GC) method has been developed and validated. The HS-SPME analytical conditions (fibre position, equilibration and sampling times) were selected. The analytical parameters of the method (linearity: hexanal from 2.48 to 84.78 ng/g, pentane from 6.21 to 79.55 ng/g; precision: hexanal 2.87%, pentane 2.343.46%; recovery: hexanal 106.60%, pentane 95.39%; detection limit: hexanal 3.63 ng and pentane 4.2 ng) demonstrate the usefulness of the method. Once optimized, the method was applied to liquid infant foods based on milk and cereals, and to powdered adapted and follow-up milk-based infant formulas (IF), stored for four and seven months. In all cases the hexanal content was higher in IF than in milk-cereal based infant foods. No pentane was found in IF

Monitoring credit risk in the social economy sector by means of a binary goal programming model

The final publication is available at Springer via http://dx.doi.org/10.1007/s11628-012-0173-7Monitoring the credit risk of firms in the social economy sector presents a considerable challenge, since it is difficult to calculate ratings with traditional methods such as logit or discriminant analysis, due to the relatively small number of firms in the sector and the low default rate among cooperatives. This paper intro- duces a goal programming model to overcome such constraints and to successfully manage credit risk using economic and financial information, as well as expert advice. After introducing the model, its application to a set of Spanish cooperative societies is described.García García, F.; Guijarro Martínez, F.; Moya Clemente, I. (2013). Monitoring credit risk in the social economy sector by means of a binary goal programming model. Service Business. 7(3):483-495. doi:10.1007/s11628-012-0173-7S48349573Alfares H, Duffuaa S (2009) Assigning cardinal weights in multi-criteria decision making based on ordinal rankings. J Multicriteria Decis Anal 15:125–133Altman EI (1968) Financial ratios, discriminant analysis and the prediction of corporate bankruptcy. J Financ 23:589–609Altman EI, Hadelman RG, Narayanan P (1977) Zeta analysis: a new model to identify bankruptcy risk of corporations. J Bank Financ 1:29–54Andenmatten A (1995) Evaluation du risque de défaillance des emetteurs d’obligations: Une approche par l’aide multicritère á la décision. Presses Polytechniques et Univertitaires Romandes, LausanneBeaver WH (1966) Financial ratios as predictors of failure. J Account Res 4:71–111Boritz JE, Kennedey DB (1995) Effectiveness of neural network types for prediction of business failure. 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Financ Manage 17:66–76Frydman H, Altman EI, Kao DL (1985) Introducing recursive partitioning for financial classification: the case of financial distress. J Financ 40:269–291García F, Guijarro F, Moya I (2008) La valoración de empresas agroalimentarias: una extensión de los modelos factoriales. Rev Estud Agro-Soc 217:155–181Gupta MC, Huefner RJ (1972) A cluster analysis study of financial ratios and industry characteristics. J Account Res 10:77–95Jensen RE (1971) A cluster analysis study of financial performance of selected firms. Account Rev 16:35–56Juliá J (2011) Social economy: a responsible people-oriented economy. Serv Bus 5:173–175Keasey K, Mcguinnes P, Short H (1990) Multilogit approach to predicting corporate failure: further analysis and the issue of signal consistency. Omega-Int J Manage S 18:85–94Li H, Adeli H, Sun J, Han JG (2011) Hybridizing principles of TOPSIS with case-based reasoning for business failure prediction. Comput Oper Res 38:409–419Luoma M, Laitinen EK (1991) Survival analysis as a tool for firm failure prediction. Omega-Int J Manage S 19:673–678March I, Yagüe RM (2009) Desempeño en empresas de economía social. Un modelo para su medición. CIRIEC 64:105–131Martin D (1977) Early warning of bank failure: a logit regression approach. J Bank Financ 1:249–276Mateos A, Marín M, Marí S, Seguí E (2011) Los modelos de predicción del fracaso empresarial y su aplicabilidad en cooperativas agrarias. CIRIEC 70:179–208McKee T (2000) Developing a bankruptcy prediction model via rough sets theory. Int J Intell Syst Account Finan Manage 9:159–173Messier WF, Hansen JV (1988) Inducing rules for expert system development: an example using default and bankruptcy data. Manage Sci 34:1403–1415Ohlson JA (1980) Financial ratios and the probabilistic prediction of bankruptcy. J Account Res 18:109–131Peel MJ (1987) Timeliness of private firm reports predicting corporate failure. 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Antioxidant activities of sulfated polysaccharides from brown and red seaweeds

The in vitro antioxidant activities of the following six sulfated polysaccharides were investigated: iota, kappa and lambda carrageenans, which are widely used in the food industry, fucoidan (homofucan) from the edible seaweed Fucus vesiculosus and fucans (heterofucans) F0.5 and F1.1 from the seaweed Padina gymnospora. With respect to the inhibition of superoxide radical formation, fucoidan had an IC50 (the half maximal inhibitory concentration) of 0.058 mg·mL−1, while the IC50 for the kappa, iota and lambda carrageenans were 0.112, 0.332 and 0.046 mg·mL−1, respectively. All of the samples had an inhibitory effect on the formation of hydroxyl radicals. The results of peroxidation tests showed that fucoidan had an IC50 of 1.250 mg·mL−1 and that the kappa, iota and lambda carrageenans had an IC50 of 2.753 and 2.338 and 0.323 mg·mL−1, respectively. Fucan fractions showed low antioxidant activity relative to fucoidan. These results clearly indicate the beneficial effect of algal polysaccharides as antioxidants

Clinical Efficacy, Safety and Tolerability of a New Subcutaneous Immunoglobulin 16.5% (Octanorm [Cutaquig®]) in the Treatment of Patients With Primary Immunodeficiencies

Introduction: Subcutaneously administered immunoglobulin (SCIG) is increasingly used to treat patients with primary immunodeficiencies (PIDs). Octanorm (marketed as cutaquig® in USA and Canada) is a new 16.5% solution of human SCIG, manufactured by a process based on that of the intravenous preparation (IVIG) octagam®.Objectives: To investigate the efficacy, safety and tolerability of octanorm in a prospective, open-label, single-arm phase 3 study involving adult and pediatric patients with PIDs (NCT01888484; clinicaltrials.gov/ct2/show/NCT01888484).Methods: Patients who were previously treated with IVIG received a total of 64 weekly SCIG infusions, including 12 weekly infusions during the wash-in/wash-out period, followed by 52 weekly infusions during the evaluation period.Results: A total of 61 patients aged 2–73 years received 3,497 infusions of octanorm. The mean dose per patient was 0.175 g/kg/infusion. The mean calculated dose conversion factor from the patients' previous IVIG dose for octanorm was 1.37. No serious bacterial infections developed during the study. The rate of other infections per person-year during the primary observation period was 3.43 (upper 95% CI 4.57). All but one non-bacterial infection were mild or moderate in intensity. IgG trough levels were constant during the course of the study. Eleven patients (18.0%) experienced 14 mild or moderate systemic adverse events (AEs) related to octanorm. The rate of related AEs per infusion was 0.004. In 76.7% of infusions, no infusion site reactions were observed and only two (0.3%) reactions were deemed severe. The incidence of site reactions decreased with successive infusions.Conclusion: The new 16.5% SCIG octanorm was shown to be efficacious in preventing infections in PIDs, and was well tolerated

Transient pulsed radio emission from a magnetar

Anomalous X-ray pulsars (AXPs) are slowly rotating neutron stars with very bright and highly variable X-ray emission that are believed to be powered by ultra-strong magnetic fields of >1e14 G, according to the 'magnetar' model. The radio pulsations that have been observed from more than 1,700 neutron stars with weaker magnetic fields have never been detected from any of the dozen known magnetars. The X-ray pulsar XTE J1810-197 was revealed (in 2003) as the first AXP with transient emission when its luminosity increased 100-fold from the quiescent level; a coincident radio source of unknown origin was detected one year later. Here we show that XTE J1810-197 emits bright, narrow, highly linearly polarized radio pulses, observed at every rotation, thereby establishing that magnetars can be radio pulsars. There is no evidence of radio emission before the 2003 X-ray outburst (unlike ordinary pulsars, which emit radio pulses all the time), and the flux varies from day to day. The flux at all radio frequencies is approximately equal -- and at >20 GHz XTE J1810-197 is currently the brightest neutron star known. These observations link magnetars to ordinary radio pulsars, rule out alternative accretion models for AXPs, and provide a new window into the coronae of magnetars.Comment: accepted by Nature; some new data and significantly revised discussio

A GBD 2019 study of health and Sustainable Development Goal gains and forecasts to 2030 in Spain

This study aimed to report mortality, risk factors, and burden of diseases in Spain. The Global Burden of Disease, Injuries, and Risk Factors 2019 estimates the burden due to 369 diseases, injuries, and impairments and 87 risk factors and risk factor combinations. Here, we detail the updated Spain 1990-2019 burden of disease estimates and project certain metrics up to 2030. In 2019, leading causes of death were ischaemic heart disease, stroke, chronic obstructive pulmonary disease, Alzheimer's disease, and lung cancer. Main causes of disability adjusted life years (DALYs) were ischaemic heart disease, diabetes, lung cancer, low back pain, and stroke. Leading DALYs risk factors included smoking, high body mass index, and high fasting plasma glucose. Spain scored 74/100 among all health-related Sustainable Development Goals (SDGs) indicators, ranking 20 of 195 countries and territories. We forecasted that by 2030, Spain would outpace Japan, the United States, and the European Union. Behavioural risk factors, such as smoking and poor diet, and environmental factors added a significant burden to the Spanish population's health in 2019. Monitoring these trends, particularly in light of COVID-19, is essential to prioritise interventions that will reduce the future burden of disease to meet population health and SDG commitments