INCOME AND PRICE ELASTICITIES OF MACEDONIAN EXPORT AND IMPORT OF GOODS – A PANEL APPROACH

This paper uses a sectoral version of the conventional Imperfect substitutes model to motivate a parsimonious estimation of trade elasticities. The elasticities we compute depend directly on the specialization of trade across sectors, which is believed to add econometric precision to our estimates. On the other hand, estimates of income and price elasticities in the existing literature dealing with the case of North Macedonia are typically obtained from aggregate data, which tend to mitigate the importance of sectoral specialization. The basic assumption of the imperfect substitutes model is that neither imports, nor exports serve as perfect substitutes for domestic goods. Moreover, our import and export functions along with the income and price variables, consider some additional parameters as well, such as foreign direct investments and tariffs on imports. To this end, we were able to obtain theory-implied estimates of import and export income and price elasticities for North Macedonia – i.e. trade elasticities relevant to policy - and ultimately to calibration choices. The income and price elasticity coefficients, both in the import and in the export model, have the expected signs - increases in income positively affect exports and imports (coefficients of 0.29 and 0.85, consequently), while increases in prices lower them (coefficients of -0.23 and technically 0, respectively). Judging by the size of the coefficients, incomeeffects appear to be much more substantial than price effects

FIRST 5-DAYS FOLLOW-UP AND CORRELATION STUDY BETWEEN URINARY CYSTEINYL LEUKO TRIENES AND EDEMA VALUES IN PRIMARY SPONTANEOUS SUPRATENTORIAL INTRACEREBRAL HEMO RRHAGE

Background: After intracerebral hemorrhage cysteinyl leukotrienes (C4, D4, E4) are synthetisized in the contact brain parenchyma-extravasated blood and participate in producing of edema formation. The study aim is a 5-days follow up (admittance/3thday/5thday) of urinary cysteinyl leukotrienes, hematoma and edema volume in patients with primary spontaneous supratentorial intracerebral hemorrhage and to determine the relationship: edema/haematoma and edema/leuko trienes. Methods: An enzyme immunoassay for leukotrienes measuring in the urine samples from 62 patients with hemorrhage during the first 5 days ( admittance/3thday/5thday) and 80 health controls is used. Hematoma and edema volume is visualised and measured by computed-tomography. Results: Admission values of leukotrienes were significantly higher in the hemorrhagic patients (min =268.61; max = 5787.36; mean = 1842.20 ± 1413.19 pg/ml/mg creatinine) versus control subjects (min =297.8; max = 1684.2; mean = 918.6 ± 332) (p < 0.001). Significant leukotrienes excretion dynamism (mean:1842.20 ± 1413.19; 1181.54 ± 906.16; 982.30 ± 774.24pg/ml/mg creatinine) is found in hemorrhagic patients during 5 day-follow up (admittance/3thday for p < 0.001; the 3thday/5thday for p < 0.05). The followed hematoma volume (mean: 13.05 ± 14.49; 13.13 ± 14.66; 12.99 ±14.73 cm3) for all three periods of examination did not show significance (p > 0.05). The edema (mean: 12.86 ±13.52; 22.38 ± 21.10; 28.45 ± 29.41 cm3) showed very high significance (p < 0.001). At admitance and on the 5th day nonsignificant positive correlation (r = 0.4; p >0.05) of moderate strength is found between edema and hematoma; and significant positive correlation (r = 0.6; p < 0.05) of moderate to high strength at the 3thday. Between leukotrienes and edema, the coefficient of correlation r = – 0.1 (p > 0.05) at admittance, r = – 0.05 (p >0.05) on the 3th day (nonexistence of linear correlation, the sign minus presents their tendency for the opposite movement in their values) and r = 0.2 (p > 0.05) on the 5thday are found (positive linear nonsignificant correlation of slight strength). Conclusion: Significant urinary leukotrienes excretion (a brain capacity for significant leukotrienes synthesis) and significant edema progression versus constant haematoma are found. The edema size followed the hematoma size of moderate extent. The edema showed an inverse dependence of the leukotrienes (atendency for opposite movement of their values), the high leukotrienes values at admittance bring to greater edema volume on the third/the fifth day, respectively. Elevated cysteinyl leukotrienes synthesis and the elevated edema could point to cause-effective relationship between them establishing the leukotrienes as an edema promotive-factor in intracerebral haemorrhage

Using data-driven and phonetic units for speaker verification

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. A. E. Hannani, D. T. Toledano, D. Petrovska-Delacrétaz, A. Montero-Asenjo, J. Hennebert, "Using Data-driven and Phonetic Units for Speaker Verification" in Odyssey: The Speaker and Language Recognition Workshop, San Juan (Puerto Rico), 2006, pp.1 - 6Recognition of speaker identity based on modeling the streams produced by phonetic decoders (phonetic speaker recognition) has gained popularity during the past few years. Two of the major problems that arise when phone based systems are being developed are the possible mismatches between the development and evaluation data and the lack of transcribed databases. Data-driven segmentation techniques provide a potential solution to these problems because they do not use transcribed data and can easily be applied on development data minimizing the mismatches. In this paper we compare speaker recognition results using phonetic and data-driven decoders. To this end, we have compared the results obtained with a speaker recognition system based on data-driven acoustic units and phonetic speaker recognition systems trained on Spanish and English data. Results obtained on the NIST 2005 Speaker Recognition Evaluation data show that the data-driven approach outperforms the phonetic one and that further improvements can be achieved by combining both approache

Using data-driven and phonetic units for speaker verication

Abstract Recognition of speaker identity based on modeling the streams produced by phonetic decoders (phonetic speaker recognition) has gained popularity during the past few years. Two of the major problems that arise when phone based systems are being developed are the possible mismatches between the development and evaluation data and the lack of transcribed databases. Data-driven segmentation techniques provide a potential solution to these problems because they do not use transcribed data and can easily be applied on development data minimizing the mismatches. In this paper we compare speaker recognition results using phonetic and data-driven decoders. To this end, we have compared the results obtained with a speaker recognition system based on data-driven acoustic units and phonetic speaker recognition systems trained on Spanish and English data. Results obtained on the NIST 2005 Speaker Recognition Evaluation data show that the data-driven approach outperforms the phonetic one and that further improvements can be achieved by combining both approaches

Leveraging the Potential of Digital Technology for Better Individualized Treatment of Parkinson's Disease.

Recent years have witnessed a strongly increasing interest in digital technology within medicine (sensor devices, specific smartphone apps) and specifically also neurology. Quantitative measures derived from digital technology could provide Digital Biomarkers (DMs) enabling a quantitative and continuous monitoring of disease symptoms, also outside clinics. This includes the possibility to continuously and sensitively monitor the response to treatment, hence opening the opportunity to adapt medication pathways quickly. In addition, DMs may in the future allow early diagnosis, stratification of patient subgroups and prediction of clinical outcomes. Thus, DMs could complement or in certain cases even replace classical examiner-based outcome measures and molecular biomarkers measured in cerebral spinal fluid, blood, urine, saliva, or other body liquids. Altogether, DMs could play a prominent role in the emerging field of precision medicine. However, realizing this vision requires dedicated research. First, advanced data analytical methods need to be developed and applied, which extract candidate DMs from raw signals. Second, these candidate DMs need to be validated by (a) showing their correlation to established clinical outcome measures, and (b) demonstrating their diagnostic and/or prognostic value compared to established biomarkers. These points again require the use of advanced data analytical methods, including machine learning. In addition, the arising ethical, legal and social questions associated with the collection and processing of sensitive patient data and the use of machine learning methods to analyze these data for better individualized treatment of the disease, must be considered thoroughly. Using Parkinson's Disease (PD) as a prime example of a complex multifactorial disorder, the purpose of this article is to critically review the current state of research regarding the use of DMs, discuss open challenges and highlight emerging new directions

IRIM at TRECVID 2012: Semantic Indexing and Instance Search

International audienceThe IRIM group is a consortium of French teams work- ing on Multimedia Indexing and Retrieval. This paper describes its participation to the TRECVID 2012 se- mantic indexing and instance search tasks. For the semantic indexing task, our approach uses a six-stages processing pipelines for computing scores for the likeli- hood of a video shot to contain a target concept. These scores are then used for producing a ranked list of im- ages or shots that are the most likely to contain the tar- get concept. The pipeline is composed of the following steps: descriptor extraction, descriptor optimization, classi cation, fusion of descriptor variants, higher-level fusion, and re-ranking. We evaluated a number of dif- ferent descriptors and tried di erent fusion strategies. The best IRIM run has a Mean Inferred Average Pre- cision of 0.2378, which ranked us 4th out of 16 partici- pants. For the instance search task, our approach uses two steps. First individual methods of participants are used to compute similrity between an example image of in- stance and keyframes of a video clip. Then a two-step fusion method is used to combine these individual re- sults and obtain a score for the likelihood of an instance to appear in a video clip. These scores are used to ob- tain a ranked list of clips the most likely to contain the queried instance. The best IRIM run has a MAP of 0.1192, which ranked us 29th on 79 fully automatic runs

Facilitating free travel in the Schengen area - A position paper by the European Association for Biometrics

Due to migration, terror‐threats and the viral pandemic, various EU member states have re‐established internal border control or even closed their borders. European Association for Biometrics (EAB), a non‐profit organisation, solicited the views of its members on ways which biometric technologies and services may be used to help with re‐establishing open borders within the Schengen area while at the same time mitigating any adverse effects. From the responses received, this position paper was composed to identify ideas to re‐establish free travel between the member states in the Schengen area. The paper covers the contending needs for security, open borders and fundamental rights as well as legal constraints that any technological solution must consider. A range of specific technologies for direct biometric recognition alongside complementary measures are outlined. The interrelated issues of ethical and societal considerations are also highlighted. Provided a holistic approach is adopted, it may be possible to reach a more optimal trade‐off with regards to open borders while maintaining a high‐level of security and protection of fundamental rights. European Association for Biometrics and its members can play an important role in fostering a shared understanding of security and mobility challenges and their solutions

3D active shape model for automatic facial landmark location trained with automatically generated landmark points

International audienceIn this paper, a 3D Active Shape Model (3DASM) algorithm is presented to automatically locate facial landmarks from different views. The 3DASM is trained by setting different shape and texture parameters of 3D Morphable Model (3DMM). Using 3DMM to synthesize training data offers us two advantages: first, few manual operations are need, except labeling landmarks on the mean face of 3DMM. Second, since the learning data are directly from 3DMM, landmarks have one to one correspondence between the 2D points detected from the image and 3D points on 3DMM. This kind of correspondence will benefit 3D face reconstruction processing. During fitting, 3D rotation parameters are added comparing to 2D Active Shape Model (ASM). So we separate shape variations into intrinsic change (caused by the character of different person) and extrinsic change (caused by model projection). The experimental results show that our method is robust to pose variatio