The Long-Short Story of Movie Description

Generating descriptions for videos has many applications including assisting blind people and human-robot interaction. The recent advances in image captioning as well as the release of large-scale movie description datasets such as MPII Movie Description allow to study this task in more depth. Many of the proposed methods for image captioning rely on pre-trained object classifier CNNs and Long-Short Term Memory recurrent networks (LSTMs) for generating descriptions. While image description focuses on objects, we argue that it is important to distinguish verbs, objects, and places in the challenging setting of movie description. In this work we show how to learn robust visual classifiers from the weak annotations of the sentence descriptions. Based on these visual classifiers we learn how to generate a description using an LSTM. We explore different design choices to build and train the LSTM and achieve the best performance to date on the challenging MPII-MD dataset. We compare and analyze our approach and prior work along various dimensions to better understand the key challenges of the movie description task

Prestressing wire breakage monitoring using sound event detection

Detecting prestressed wire breakage in concrete bridges is essential for ensuring safety and longevity and preventing catastrophic failures. This study proposes a novel approach for wire breakage detection using Mel-frequency cepstral coefficients (MFCCs) and back-propagation neural network (BPNN). Experimental data from two bridges in Italy were acquired to train and test the models. To overcome the limited availability of real-world training data, data augmentation techniques were employed to increase the data set size, enhancing the capability of the models and preventing over-fitting problems. The proposed method uses MFCCs to extract features from acoustic emission signals produced by wire breakage, which are then classified by the BPNN. The results show that the proposed method can detect and classify sound events effectively, demonstrating the promising potential of BPNN for real-time monitoring and diagnosis of bridges. The significance of this work lies in its contribution to improving bridge safety and preventing catastrophic failures. The combination of MFCCs and BPNN offers a new approach to wire breakage detection, while the use of real-world data and data augmentation techniques are significant contributions to overcoming the limited availability of training data. The proposed method has the potential to be a generalized and robust model for real-time monitoring of bridges, ultimately leading to safer and longer-lasting infrastructure

The effects of alfalfa particle size and acid treated protein on ruminal chemical composition, liquid, particulate, escapable and non escapable phases in Zel sheep

This study was conducted to investigate the effects of alfalfa particle size (long vs. fine) and canola meal treated with hydrochloric acid solution (untreated vs treated) on ruminal chemical composition, liquid, particulate, escapable and non escapable phases in Zel sheep. Four ruminally cannulated sheep received a mixed diet (% of dry matter) consisting of 23.73 alfalfa, 8.70 canola meal, 39.56 wheat straw, 13.45 beet pulp and 13.45 barley grain and 1 mineral-vitamin mixture. The experimental design was a 4 × 4 Latin square with 22-days periods. The diet was offered twice daily (09:00 and 21:00 h). The rumens were evacuated manually at 3, 7.5 and 12 h post-feeding and total ruminal contents were separated into mat and liquids. Dry matter weight distribution of total recovered particles was determined by a wetsieving procedure and used to partition ruminal mat and liquids among percentage of large (≥ 6.35 mm), medium (< 6.35 and ≥ 1.18 mm), and small (< 1.18 and ≥ 0.5 mm) particles. Lyophilized ruminal digesta were analyzed for chemical composition especially for CP, NDF and EE. No interactions (P > 0.05) between dietary particle size and acid level were observed for ruminal chemical composition, liquid, particulate, escapable and non escapable phase. Treatment of canola meal and increase of particle size reduced the values of CP. Generally, with increase in time after feeding, the values of each nutrient decreased. Particle size and time post-feeding had a pronounced effect on the distribution of different particle fractions, whereas acid level did not influence it. With increase in time after feeding, percentage of particles ≥ 6.35 mm decreased, whereas the percentage of particles < 6.35 mm increased, illustrating intensive particle breakdown in the reticulo-rumen. Different particle size and time post-feeding had pronounced effect on total mass of ruminal digesta, ruminal mat and liquid part, in which fine particles and 12 h post feeding caused the lowest rumen mat. Time post feeding and acid level did not influence the values of pH significantly, whereas with increase in particle size, the values of pH increased.Key words: Canola meal, particle size, rumen mat, escapable, non escapable phase

Secure Simultaneous Information and Power Transfer for Downlink Multi-User Massive MIMO

In this article, downlink secure transmission in simultaneous information and power transfer (SWIPT) system enabled with massive multiple-input multiple-output (MIMO) is studied. A base station (BS) with a large number of antennas transmits energy and information signals to its intended users, but these signals are also received by an active eavesdropper. The users and eavesdropper employ a power splitting technique to simultaneously decode information and harvest energy. Massive MIMO helps the BS to focus energy to the users and prevent information leakage to the eavesdropper. The harvested energy by each user is employed for decoding information and transmitting uplink pilot signals for channel estimation. It is assumed that the active eavesdropper also harvests energy in the downlink and then contributes during the uplink training phase. Achievable secrecy rate is considered as the performance criterion and a closed-form lower bound for it is derived. To provide secure transmission, the achievable secrecy rate is then maximized through an optimization problem with constraints on the minimum harvested energy by the user and the maximum harvested energy by the eavesdropper. Numerical results show the effectiveness of using massive MIMO in providing physical layer security in SWIPT systems and also show that our closed-form expressions for the secrecy rate are accurate

Secure Simultaneous Information and Power Transfer for Downlink Multi-user Massive MIMO

In this paper, downlink secure transmission in simultaneous information and power transfer (SWIPT) system enabled with massive multiple-input multiple-output (MIMO) is studied. A base station (BS) with a large number of antennas transmits energy and information signals to its intended users, but these signals are also received by an active eavesdropper. The users and eavesdropper employ a power splitting technique to simultaneously decode information and harvest energy. Massive MIMO helps the BS to focus energy to the users and prevent information leakage to the eavesdropper. The harvested energy by each user is employed for decoding information and transmitting uplink pilot signals for channel estimation. It is assumed that the active eavesdropper also harvests energy in the downlink and then contributes during the uplink training phase. Achievable secrecy rate is considered as the performance criterion and a closed-form lower bound for it is derived. To provide secure transmission, the achievable secrecy rate is then maximized through an optimization problem with constraints on the minimum harvested energy by the user and the maximum harvested energy by the eavesdropper. Numerical results show the effectiveness of using massive MIMO in providing physical layer security in SWIPT systems and also show that our closed-form expressions for the secrecy rate are accurate

Insulin-like growth factor I gene polymorphism associated with growth traits in beluga (Huso huso) fish

The aim of the present study was to detect polymorphism in Insulin like growth factor-I (IGF-I) gene of beluga (Huso huso) fish using PCR-SSCP technique and also investigation of its association with growth traits (condition factor, body length and weight). A total of 150 specimens of beluga were randomly selected and DNA was isolated from caudal fin using modified salting out method. Then two fragments of 171 and 362 bp from 5'-UTR and 3'-UTR regions of IGF-I gene were amplified, respectively. Genotyping of individuals by SSCP technique showed five banding patterns of A, B, C, D and E for 5'-UTR region with the frequencies of 29.2, 0.76, 16.92, 51.53 and 10% respectively in one year-old and three banding patterns of A, C and D with the frequency of 45, 10 and 45% for two year-old fish. Also three banding patterns (A, B and C) were seen for 3'-UTR region with the frequency of 62.3, 27.69 and 10.76% in one-year-old and 20, 60 and 20% in two year-old fish. The A banding pattern in 3'-UTR and D banding pattern in 5'-UTR sites were the most frequent pattern in the studied beluga population. The association analysis using SAS statistical software indicated no significant association between observed banding patterns and growth traits (body length, weight, and condition factor) in beluga. Considering the important role of IGF-I as a probable candidate gene affecting growth related traits, these marker sites should be studied more in larger sample sizes and also in other regions of the gene

The Effect of Experience on Recognition of Mother’s Voice in Preterm Infants

Background: According to existing theories, supportive cares provided through specific kinds of stimuli affect the growth, development and neurobehavioral functioning of preterm infants. Some of the studies indicate that the fetal heart rate response to mother’s voice begins in the week 32 of pregnancy. However, the fact that whether preterm infant is able to recognize mother’s live voice from the voice of a stranger woman is unknown. Objectives: The present study aimed to compare the effects of mother’s voice and a stranger’s voice on the heart rate of preterm infants hospitalized in a neonatal intensive care unit (NICU). Methods: In a clinical trial study, 66 preterm infants hospitalized in the NICU were randomly assigned into three groups of 22 (i.e. mother’s voice and stranger’s voice groups and a silent group). The infants’ heart rates were recorded by a monitoring system in all of the three groups each five minutes for 30 minutes overall (10 minutes before, during and after the intervention) in three consecutive days. Both one-way and repeated measures analysis of variance were used to analyze the data in terms of significant differences. Also, the chi-square test and analysis of variance were used to compare the demographic variables of the groups. Results: The heart rate of the infants in the mother’s voice group, stranger’s voice group and the silent group were 133.99 � 2.72, 134.26 � 2.43 and 137.94 � 2.92 per minutes, respectively (P > 0.588) and changed to 143.42 � 2.85, 133.22 � 2.15 and 138.28 � 2.21, respectively (P = 0.016). Moreover, the infants’ heart rates were respectively 136.87�3.38, 132.68�2.22 and 138.19�2.65 per minutes, 10 minutes after the intervention (P > 0.345). Conclusions: No significant difference was found between the mean heart rates of the three groups neither before, nor 10 minutes after the intervention. However, a significant difference was observed among the three groups during the intervention. Therefore, we can conclude that the preterm infants can recall and differentiate their mothers’ voice from the voice of a stranger. Then, an opportunity can be provided during the developmental care for the infants to hear their mothers’ voice

Assimilation of Freeze - Thaw Observations into the NASA Catchment Land Surface Model

The land surface freeze-thaw (F-T) state plays a key role in the hydrological and carbon cycles and thus affects water and energy exchanges and vegetation productivity at the land surface. In this study, we developed an F-T assimilation algorithm for the NASA Goddard Earth Observing System, version 5 (GEOS-5) modeling and assimilation framework. The algorithm includes a newly developed observation operator that diagnoses the landscape F-T state in the GEOS-5 Catchment land surface model. The F-T analysis is a rule-based approach that adjusts Catchment model state variables in response to binary F-T observations, while also considering forecast and observation errors. A regional observing system simulation experiment was conducted using synthetically generated F-T observations. The assimilation of perfect (error-free) F-T observations reduced the root-mean-square errors (RMSE) of surface temperature and soil temperature by 0.206 C and 0.061 C, respectively, when compared to model estimates (equivalent to a relative RMSE reduction of 6.7 percent and 3.1 percent, respectively). For a maximum classification error (CEmax) of 10 percent in the synthetic F-T observations, the F-T assimilation reduced the RMSE of surface temperature and soil temperature by 0.178 C and 0.036 C, respectively. For CEmax=20 percent, the F-T assimilation still reduces the RMSE of model surface temperature estimates by 0.149 C but yields no improvement over the model soil temperature estimates. The F-T assimilation scheme is being developed to exploit planned operational F-T products from the NASA Soil Moisture Active Passive (SMAP) mission

Evaluation of diagnostic value of soluble urokinase-type plasminogen activator receptor in sepsis

Background: Sepsis is one of the most important causes of morbidity and mortality in the intensive care units (ICUs). It is difficult to accurately differentiate sepsis from similar diseases rapidly. Therefore, it becomes critical to identify any biomarker with the ability of differentiation between sepsis and nonsepsis conditions. The urokinase plasminogen activator receptor has been implicated as an important factor in regulation of leukocyte adhesion and migration. Objectives: In this study, we evaluated the value of soluble urokinase plasminogen activator receptor (suPAR), erythrocyte sedimentation (ESR), and C-reactive protein (CRP) serum levels in terms of their value for sepsis diagnosis in ICU patients. Patients and Methods: We enrolled 107 ICU patients; 40 with sepsis, 43 with systemic inflammatory response syndrome, and 24 as control group. Serum soluble urokinase plasminogen activator receptor, ESR, white blood cell (WBC), and CRP levels were measured on the day of admission. Results: The group with sepsis had higher suPAR, ESR, and CRP levels compared with the group with noninfectious systemic inflammatory response syndrome (SIRS) (P = 0.01, 0.00 and 0.00, respectively). CRP concentrations and ESR were higher in the sepsis group than in the non-SIRS group (P = 0.00 and 0.00, respectively). In a receiver-operating characteristic curve analysis, ESR, CRP and suPAR had an area under the curve larger than 0.65 (P = 0.00) in distinguishing between septic and noninfectious SIRS patients. CRP, ESR and suPAR had a sensitivity of 87, 71 and 66 and a specificity of 59, 76 and 74 respectively in diagnosing infection in SIRS. Conclusions: The diagnostic values of CRP and ESR were better than suPAR and WBC count in patients with sepsis. © 2015, Infectious Diseases and Tropical Medicine Research Center