Mobile Communication Signatures of Unemployment

The mapping of populations socio-economic well-being is highly constrained by the logistics of censuses and surveys. Consequently, spatially detailed changes across scales of days, weeks, or months, or even year to year, are difficult to assess; thus the speed of which policies can be designed and evaluated is limited. However, recent studies have shown the value of mobile phone data as an enabling methodology for demographic modeling and measurement. In this work, we investigate whether indicators extracted from mobile phone usage can reveal information about the socio-economical status of microregions such as districts (i.e., average spatial resolution < 2.7km). For this we examine anonymized mobile phone metadata combined with beneficiaries records from unemployment benefit program. We find that aggregated activity, social, and mobility patterns strongly correlate with unemployment. Furthermore, we construct a simple model to produce accurate reconstruction of district level unemployment from their mobile communication patterns alone. Our results suggest that reliable and cost-effective economical indicators could be built based on passively collected and anonymized mobile phone data. With similar data being collected every day by telecommunication services across the world, survey-based methods of measuring community socioeconomic status could potentially be augmented or replaced by such passive sensing methods in the future

Identifying physical activity type in manual wheelchair users with spinal cord injury by means of accelerometers

Objectives: The main objective of this study was to develop and test classification algorithms based on machine learning using accelerometers to identify the activity type performed by manual wheelchair users with spinal cord injury (SCI). Setting: The study was conducted in the Physical Therapy department and the Physical Education and Sports department of the University of Valencia. Methods: A total of 20 volunteers were asked to perform 10 physical activities, lying down, body transfers, moving items, mopping, working on a computer, watching TV, arm-ergometer exercises, passive propulsion, slow propulsion and fast propulsion, while fitted with four accelerometers placed on both wrists, chest and waist. The activities were grouped into five categories: sedentary, locomotion, housework, body transfers and moderate physical activity. Different machine learning algorithms were used to develop individual and group activity classifiers from the acceleration data for different combinations of number and position of the accelerometers. Results: We found that although the accuracy of the classifiers for individual activities was moderate (55-72%), with higher values for a greater number of accelerometers, grouped activities were correctly classified in a high percentage of cases (83.2-93.6%). Conclusions: With only two accelerometers and the quadratic discriminant analysis algorithm we achieved a reasonably accurate group activity recognition system (490%). Such a system with the minimum of intervention would be a valuable tool for studying physical activity in individuals with SCI.X Garcia-Masso gratefully acknowledges the support of the University of Valencia under project UV-INV-PRECOMP13-115364.García-Massó, X.; Serra-Añó P.; Gonzalez, L.; Ye Lin, Y.; Prats-Boluda, G.; Garcia Casado, FJ. (2015). Identifying physical activity type in manual wheelchair users with spinal cord injury by means of accelerometers. Spinal Cord. 53(10):772-777. https://doi.org/10.1038/sc.2015.81S7727775310Buchholz AC, Martin Ginis KA, Bray SR, Craven BC, Hicks AL, Hayes KC et al. Greater daily leisure time physical activity is associated with lower chronic disease risk in adults with spinal cord injury. Appl Physiol Nutr Metab 2009; 34: 640–647.Hetz SP, Latimer AE, Buchholz AC, Martin Ginis KA . Increased participation in activities of daily living is associated with lower cholesterol levels in people with spinal cord injury. Arch Phys Med Rehabil 2009; 90: 1755–1759.Manns PJ, Chad KE . Determining the relation between quality of life, handicap, fitness, and physical activity for persons with spinal cord injury. Arch Phys Med Rehabil 1999; 80: 1566–1571.Serra-Añó P, Pellicer-Chenoll M, García-Massó X, Morales J, Giner-Pascual M, González L-M . Effects of resistance training on strength, pain and shoulder functionality in paraplegics. Spinal Cord 2012; 50: 827–831.Slater D, Meade MA . Participation in recreation and sports for persons with spinal cord injury: review and recommendations. NeuroRehabilitation 2004; 19: 121–129.Lee M, Zhu W, Hedrick B, Fernhall B . Determining metabolic equivalent values of physical activities for persons with paraplegia. Disabil Rehabil 2010; 32: 336–343.Lee M, Zhu W, Hedrick B, Fernhall B . Estimating MET values using the ratio of HR for persons with paraplegia. Med Sci Sports Exerc 2010; 42: 985–990.Hayes AM, Myers JN, Ho M, Lee MY, Perkash I, Kiratli BJ . Heart rate as a predictor of energy expenditure in people with spinal cord injury. J Rehabil Res Dev 2005; 42: 617–624.Washburn RA, Zhu W, McAuley E, Frogley M, Figoni SF . The physical activity scale for individuals with physical disabilities: development and evaluation. Arch Phys Med Rehabil 2002; 83: 193–200.Ginis KAM, Latimer AE, Hicks AL, Craven BC . Development and evaluation of an activity measure for people with spinal cord injury. Med Sci Sports Exerc 2005; 37: 1099–1111.Khan AM, Lee Y-K, Lee S, Kim T-S . Accelerometer’s position independent physical activity recognition system for long-term activity monitoring in the elderly. Med Biol Eng Comput 2010; 48: 1271–1279.Khan AM, Lee Y-K, Lee SY, Kim T-S . A triaxial accelerometer-based physical-activity recognition via augmented-signal features and a hierarchical recognizer. IEEE Trans Inf Technol Biomed Publ 2010; 14: 1166–1172.Liu S, Gao RX, John D, Staudenmayer J, Freedson PS . SVM-based multi-sensor fusion for free-living physical activity assessment. Conf Proc Annu Int Conf IEEE Eng Med Biol Soc 2011; 2011: 3188–3191.Liu S, Gao RX, John D, Staudenmayer JW, Freedson PS . Multisensor data fusion for physical activity assessment. IEEE Trans Biomed Eng 2012; 59: 687–696.Staudenmayer J, Pober D, Crouter S, Bassett D, Freedson P . An artificial neural network to estimate physical activity energy expenditure and identify physical activity type from an accelerometer. J Appl Physiol 2009; 107: 1300–1307.Trost SG, Wong W-K, Pfeiffer KA, Zheng Y . Artificial neural networks to predict activity type and energy expenditure in youth. Med Sci Sports Exerc 2012; 44: 1801–1809.David Apple MD . Pain above the injury level. Top Spinal Cord Inj Rehabil 2001; 7: 18–29.Subbarao JV, Klopfstein J, Turpin R . Prevalence and impact of wrist and shoulder pain in patients with spinal cord injury. J Spinal Cord Med 1995; 18: 9–13.Postma K, van den Berg-Emons HJG, Bussmann JBJ, Sluis TAR, Bergen MP, Stam HJ . Validity of the detection of wheelchair propulsion as measured with an Activity Monitor in patients with spinal cord injury. Spinal Cord 2005; 43: 550–557.Hiremath SV, Ding D, Farringdon J, Vyas N, Cooper RA . Physical activity classification utilizing SenseWear activity monitor in manual wheelchair users with spinal cord injury. Spinal Cord 2013; 51: 705–709.Itzkovich M, Gelernter I, Biering-Sorensen F, Weeks C, Laramee MT, Craven BC et al. The Spinal Cord Independence Measure (SCIM) version III: reliability and validity in a multi-center international study. Disabil Rehabil 2007; 29: 1926–1933.García-Massó X, Serra-Añó P, García-Raffi LM, Sánchez-Pérez EA, López-Pascual J, Gonzalez LM . Validation of the use of Actigraph GT3X accelerometers to estimate energy expenditure in full time manual wheelchair users with spinal cord injury. Spinal Cord 2013; 51: 898–903.Preece SJ, Goulermas JY, Kenney LPJ, Howard D . A comparison of feature extraction methods for the classification of dynamic activities from accelerometer data. IEEE Trans Biomed Eng 2009; 56: 871–879.Hurd WJ, Morrow MM, Kaufman KR . Tri-axial accelerometer analysis techniques for evaluating functional use of the extremities. J Electromyogr Kinesiol 2013; 23: 924–929.Teixeira FG, Jesus IRT, Mello RGT, Nadal J . Cross-correlation between head acceleration and stabilograms in humans in orthostatic posture. Conf Proc Annu Int Conf IEEE Eng Med Biol Soc 2012; 2012: 3496–3499.Hastie T, Tibshirani R, Friedman J . The Elements of Statistical Learning. Data Mining, Inference, and Prediction. Springer: New York, NY. 2009

Microalgae production in fresh market wastewater and its utilization as a protein substitute in formulated fish feed for oreochromis spp.

Rapid growing of human population has led to increasing demand of aquaculture production. Oreochromis niloticus or known as tilapia is one of the most globally cultured freshwater fish due to its great adaptation towards extreme environment. Besides, farming of tilapia not only involves small scales farming for local consumption but also larger scales for international market which contributes to a foreign currency earning. Extensive use of fishmeal as feed for fish and for other animals indirectly caused an increasing depletion of the natural resource and may consequently cause economic and environmental unstable. Microalgae biomass seems to be a promising feedstock in aquaculture industry. It can be used for many purposes such as live food for fish larvae and dried microalgae to substitute protein material in fish feed. The microalgae replacement in fish feed formulation as protein alternative seem potentially beneficial for long term aqua-business sustainability. The present chapter discussed the potential of microalgae as an alternative nutrition in fish feed formulations, specifically Tilapia

FindFoci: a focus detection algorithm with automated parameter training that closely matches human assignments, reduces human inconsistencies and increases speed of analysis

Accurate and reproducible quantification of the accumulation of proteins into foci in cells is essential for data interpretation and for biological inferences. To improve reproducibility, much emphasis has been placed on the preparation of samples, but less attention has been given to reporting and standardizing the quantification of foci. The current standard to quantitate foci in open-source software is to manually determine a range of parameters based on the outcome of one or a few representative images and then apply the parameter combination to the analysis of a larger dataset. Here, we demonstrate the power and utility of using machine learning to train a new algorithm (FindFoci) to determine optimal parameters. FindFoci closely matches human assignments and allows rapid automated exploration of parameter space. Thus, individuals can train the algorithm to mirror their own assignments and then automate focus counting using the same parameters across a large number of images. Using the training algorithm to match human assignments of foci, we demonstrate that applying an optimal parameter combination from a single image is not broadly applicable to analysis of other images scored by the same experimenter or by other experimenters. Our analysis thus reveals wide variation in human assignment of foci and their quantification. To overcome this, we developed training on multiple images, which reduces the inconsistency of using a single or a few images to set parameters for focus detection. FindFoci is provided as an open-source plugin for ImageJ

Simvastatin inhibits TLR8 signaling in primary human monocytes and spontaneous TNF production from rheumatoid synovial membrane cultures

Simvastatin has been shown to have anti-inflammatory effects that are independent of its serum cholesterol lowering action, but the mechanisms by which these anti-inflammatory effects are mediated have not been elucidated. To explore the mechanism involved, the effect of simvastatin on Toll-like receptor (TLR) signalling in primary human monocytes was investigated. A short pre-treatment with simvastatin dose-dependently inhibited the production of tumor necrosis factor-α (TNF) in response to TLR8 (but not TLRs 2, 4, or 5) activation. Statins are known inhibitors of the cholesterol biosynthetic pathway, but intriguingly TLR8 inhibition could not be reversed by addition of mevalonate or geranylgeranyl pyrophosphate; downstream products of cholesterol biosynthesis. TLR8 signalling was examined in HEK 293 cells stably expressing TLR8, where simvastatin inhibited IKKα/β phosphorylation and subsequent NF-κB activation without affecting the pathway to AP-1. Since simvastatin has been reported to have anti-inflammatory effects in RA patients and TLR8 signalling contributes to TNF production in human RA synovial tissue in culture, simvastatin was tested in these cultures. Simvastatin significantly inhibited the spontaneous release of TNF in this model which was not reversed by mevalonate. Together, these results demonstrate a hitherto unrecognized mechanism of simvastatin inhibition of TLR8 signalling that may in part explain its beneficial anti-inflammatory effects

On the nature of the fourth generation neutrino and its implications

We consider the neutrino sector of a Standard Model with four generations. While the three light neutrinos can obtain their masses from a variety of mechanisms with or without new neutral fermions, fourth-generation neutrinos need at least one new relatively light right-handed neutrino. If lepton number is not conserved this neutrino must have a Majorana mass term whose size depends on the underlying mechanism for lepton number violation. Majorana masses for the fourth generation neutrinos induce relative large two-loop contributions to the light neutrino masses which could be even larger than the cosmological bounds. This sets strong limits on the mass parameters and mixings of the fourth generation neutrinos.Comment: To be published. Few typos corrected, references update

Neutrino masses from new generations

We reconsider the possibility that Majorana masses for the three known neutrinos are generated radiatively by the presence of a fourth generation and one right-handed neutrino with Yukawa couplings and a Majorana mass term. We find that the observed light neutrino mass hierarchy is not compatible with low energy universality bounds in this minimal scenario, but all present data can be accommodated with five generations and two right-handed neutrinos. Within this framework, we explore the parameter space regions which are currently allowed and could lead to observable effects in neutrinoless double beta decay, $\mu - e$ conversion in nuclei and $\mu \rightarrow e \gamma$ experiments. We also discuss the detection prospects at LHC.Comment: 28 pages, 4 figures. Version to be published. Some typos corrected. Improved figures 3 and

Non-standard interactions versus non-unitary lepton flavor mixing at a neutrino factory

The impact of heavy mediators on neutrino oscillations is typically described by non-standard four-fermion interactions (NSIs) or non-unitarity (NU). We focus on leptonic dimension-six effective operators which do not produce charged lepton flavor violation. These operators lead to particular correlations among neutrino production, propagation, and detection non-standard effects. We point out that these NSIs and NU phenomenologically lead, in fact, to very similar effects for a neutrino factory, for completely different fundamental reasons. We discuss how the parameters and probabilities are related in this case, and compare the sensitivities. We demonstrate that the NSIs and NU can, in principle, be distinguished for large enough effects at the example of non-standard effects in the $\mu$-$\tau$-sector, which basically corresponds to differentiating between scalars and fermions as heavy mediators as leading order effect. However, we find that a near detector at superbeams could provide very synergistic information, since the correlation between source and matter NSIs is broken for hadronic neutrino production, while NU is a fundamental effect present at any experiment.Comment: 32 pages, 5 figures. Final version published in JHEP. v3: Typo in Eq. (27) correcte

Small cell carcinoma arising in Barrett's esophagus: a case report and review of the literature

<p>Abstract</p> <p>Introduction</p> <p>Gastrointestinal tract small cell carcinoma is an infrequent and aggressive neoplasm that represents 0.1–1% of gastrointestinal malignancies. Very few cases of small cell esophageal carcinoma arising in Barrett's esophagus have been reported in the literature. An extremely rare case of primary small cell carcinoma of the distal third of the esophagus arising from dysplastic Barrett's esophagus is herein presented.</p> <p>Case presentation</p> <p>A 62-year-old man with gastroesophageal reflux history presented with epigastric pain, epigastric fullness, dysphagia, anorexia, and weight loss. Esophagogastroscopy revealed an ulceroproliferative, intraluminar mass in the distal esophagus obstructing the esophageal lumen. Biopsy showed small cell esophageal carcinoma. Contrast-enhanced chest and abdominal computed tomography demonstrated a large tumor of the distal third of the esophagus without any lymphadenopathy or distant metastasis. Preoperative chemotherapy with cisplatine and etoposide for 3 months resulted in a significant reduction of the tumor. After en block esophagectomy with two field lymph node dissection, proximal gastrectomy, and cervical esophagogastric anastomosis, the patient was discharged on the 14^thpostoperative day. Histopathology revealed a primary small cell carcinoma of the distal third of the esophagus arising from dysplastic Barrett's esophagus. The patient received another 3 month course of postoperative chemotherapy with the same agents and remained free of disease at 12 month review.</p> <p>Conclusion</p> <p>Although small cell esophageal carcinoma is rare and its association with dysplastic Barrett's esophagus is extremely infrequent, the high carcinogenic risk of Barrett's epithelium should be kept in mind. Prognosis is quite unfavorable; a better prognosis might be possible with early diagnosis and treatment strategies incorporating chemotherapy along with oncological radical surgery and/or radiotherapy as part of a multimodality approach. Since treatment protocols are not well established due to the rarity of the neoplasm, multi-institutional studies are needed to obtain sufficiently large populations for investigation and optimization of therapy of the disease.</p