In this paper, an alternative approach in operational modal analysis is presented, utilizing image processing technique and transmissibility functions. Imaging sensors do not impose additional mass on the structure due to their non-contact nature, while transmissibility functions, independent of excitation type, can directly extract mode shapes. The innovation of this research lies in combining these two techniques to record dynamic responses and identify modal properties. To capture the temporal response history from video signals, the block-matching method with sub-pixel accuracy was employed. Validation was conducted by recording the response of the tip of a cantilevered steel beam subjected to impact excitation, using a high-speed camera and a laser vibrometer, simultaneously. The RMSE plots in the time domain and the PSD in the frequency domain indicate high accuracy of this method. Using this approach, the displacement time histories of various points on the structure were extracted from the video signals, and the modal properties, including natural frequencies, damping ratios, and mode shapes, were identified using the transmissibility matrix method. The results obtained from the proposed method were compared with the stochastic subspace identification (SSI) method and analytical solutions. The findings reveal the accuracy of the modal identification approach introduced in this article. The highest relative error in estimating the natural frequencies of the first and second modes, compared to the values from the laser method, are 0.19% and 0.13%, respectively, and in comparison to the analytical values, they are 0.34% and 1.5%, respectively.

This study was carried out to determine untreated and roasted soybean meal dry matter and crude protein (CP) degradation characteristics by using nylon bags and SDS-PAGE techniques. There were significant differences (P<0.05) between the effective rumen degradability values of untreated and roasted soybean meal CP at different rumen outflow rates. From the slab gel analysis, soybean meal proteins are composed of two major components,  b-conglycinin and glycinin, accounting for approximately 31 and 38.8 percent of the total meal protein, respectively. Both proteins are multisubunits. The molecular weights of a’, a and b subunits of b-conglycinin were 90.5, 71.5 and 55.2 kDa and for acidic and basic of glycinin were 37.6, 19.8 kDa. Electrophoretic and densitometric analysis of untreated soybean meal protein residues revealed that conglycinin a and a subunits were degraded completely within 2 h, whereas the β subunit (12 h) of β -conglycinin as well as the acidic (24 h) and basic (48 h) polypeptide components of glycinin were more resistant to degradation. In roasted soybean meal, b -conglycinin subunits were not affected, but the degradation of glycinin decreased effectively. There were significant differences (P<0.05) between crude protein digestibility of untreated and roasted soybean meal. In conclusion, soybean meal proteins can be effectively protected from degradation in the rumen by roasting at 125°C for 15 min.

In traditional speech processing, feature extraction and classification were conducted as separate steps. The advent of deep neural networks has enabled methods that simultaneously model the relationship between acoustic and phonetic characteristics of speech while classifying it directly from the raw waveform. The first convolutional layer in these networks acts as a filter bank. To enhance interpretability and reduce the number of parameters, researchers have explored the use of parametric filters, with the SincNet architecture being a notable advancement. In SincNet's initial convolutional layer, rectangular bandpass filters are learned instead of fully trainable filters. This approach allows for modeling with fewer parameters, thereby improving the network's convergence speed and accuracy. Analyzing the learned filter bank also provides valuable insights into the model's performance. The reduction in parameters, along with increased accuracy and interpretability, has led to the adoption of various parametric filters and deep architectures across diverse speech processing applications. This paper introduces different types of parametric filters and discusses their integration into various deep architectures. Additionally, it examines the specific applications in speech processing where these filters have proven effective.

Objective: To determine true and apparent ileal amino acid digestibility of wheat (Mahdavi cultivar), autoclaved wheat and spaghetti by product. Design: Completely randomized design.Animals: One hundred and twenty one - day old broiler chickens.Procedure: Chickens were categorized into five groups:basal diet, bosal diet plus wheat (50: 50%), basal diet plus auto claved wheat (50:50%), basal diet plus spaghetti by product (50:50%) and protein free diet. Chromic oxide was included in all diets as an indigestible marker. Birds were fed for 7 days ad libitum and on day 35 fasted for 24 hours and then allowed to consume their respective diets for one hour. After then birds were killed by CO2, body cavity opened, ileum removed and digesta gently flushed using strile distilled water. The apparent and true digestibility of amino acid in the test ingredients were estimated by means of basal/test diet. Difference method.Results: The apparent and true amino acid digestibility's of test ingredients were significantly different (P<0.01).Autoclaving of wheat increases its amino acid digestibilities (P<0.01). Among test ingredients, average ileal amino acid digestibility of spaghetti by product was higher than wheat and wheat autoclaved but was lower than those values of basal diet (P<0.01). Coefficient of amino acids digestibility within an ingredient had significant difference (P<0.01). The difference between true and apparent values was significant (P<0.01).Clinical implication: Autoclaving and heat processing of spaghetti production increase wheat amino acid digestibilities. Poultry nutritionist and broiler producers can use these digestibility coefficient values for precision feed formulation.

BACKGROUND AND OBJECTIVE: Varicocele is one of the causes of male infertility. It changes with temperature and drainage of testicular veins that due to spermatogenesis disturbance and decrease of fertility in these patients. However varicocelectomy is a treatment for varicocele, but there are other methods of treating this disease including assisted reproductive technology (ART), Sperm processing and swim up. METHODS: This interventional study was performed on 155 cases in fertility and infertility Center of Babol University of medical sciences in 2004. Sperm parameters in varicocele patients was assessed before and after sperm processing. FINDINGS: The mean age of patients was 31.8 years. Sperm motility before sperm processing in grade III and IV was 53.9% and 12.9%, respectively but after sperm processing in grade III and IV changed to 78.7% and 56.8%, respectively. Total motility before sperm processing was 40 % and changed after processing to 80%. CONCLUSION: The results show that with sperm processing and collection of appropriate sperms, we are able to increase fertility.

Tomato seeds are the main component of tomato pulp and considered as an excellent source of edible oils, protein, and essential amino acids. Tomato seeds can be used as an important source of protein for human nutrition. The purpose of present study was to evaluate the effect of heat treatment on functional properties of tomato seed flour. The functional properties studied included water absorption capacity, oil absorption capacity, emulsification, foaming capacity and solubility. Isoelectric point of sample was around pH 4, while the highest solubility was observed around pH 12. The lowest value for all functional properties was observed at isoelectric point, which can be due decreased protein solubility at this point. Emulsion and foam properties of tomato seeds were desirable and therefore it can be used in some food formulation. Tomato seeds had some essential amino acid like phenylalanine, glutamic acid, aspartic acid, lysine and tryptophan.

The aim of this study was to determine and compare in situ biohydrogenation (BH) fatty acids in three forms of soybeans and linseed (raw, extruded and roasted). Nylon bags (5×10 cm) containing 4 g of raw, extruded or roasted soybeans or raw, extruded or roasted linseed were incubated in the rumen of fistulated ewes for 4, 8, 12 and 24 hours. Results for linoleic acid (C18: 2) showed that the extent of BH only in 4h of incubation was significantly higher than other times of incubation in raw linseed (P 0. 05). Proportions of linoleic acid (C18: 2) were significantly higher for raw compared to extruded and roasted soybeans for 8 and 12 hours of incubation (P 0. 05). Amounts of trans-C18: 1 (octadecadienoic acid) in all 4 times of ruminal incubation were similar between each three forms of linseed (P 0. 05). But proportions of this fatty acid in roasted soybeans were significantly lower than raw and extruded soybeans in 12 h of incubation (P 0. 05). No significant difference was observed for extent of linolenic acid (C18: 3) BH between three different forms of linseed and soybeans (P 0. 05). Differences were not significant between produced cis-9, trans-11 conjugated linoleic acid (CLA) in three forms of linseeds in all times of incubation (P 0. 05), but amounts of CLA in 12 and 24 hours of incubation were significantly higher for extruded soybeans (P 0. 05). Propor-tions of stearic acid (C18: 0) for the three forms of linseed (raw, extruded and roasted) in all hours of incu-bation showed no significant difference (P 0. 05). The amount of C18: 0 after 24 h of incubation was sig-nificantly higher for raw soybeans (P 0. 05). According to the results, heat processing had better effects on the preservation of linoleic acid compared to linolenic acid in soybeans and linseeds against rumen BH.

The analysis of heat transfer in the channel in many types of heat exchangers, such as electric cooling equipment, solar collectors, heat exchanger systems, high-performance boilers, gas turbine blade coolers, etc., is the basis of the design, construction, and optimization. Controlling heat transfer to increase the rate of heat transfer in such systems by improving the cooling method is an effective energy engineering from the point of saving energy. Increasing the heat transfer performance in the scales of macro and microchannels is crucial. The use of expanded surfaces in the channel is a practical method to increase the heat transfer coefficient. In the upcoming article, the smart design of a two-dimensional nanofluid heat exchanger has been studied numerically in order to achieve optimal performance conditions in terms of heat transfer rate, the amount of deposition of nanoparticles in the structure of the exchanger, as well as the fluid pressure drop while passing through it. It can be seen that the geometric structure optimized by the combination of genetic algorithm and computational fluid dynamics of this channel causes an increase of 1.14% in the enthalpy of the passing nanofluid, a decrease of 11.21% in the pressure drop of the passing nanofluid, and a reduction of 8.44% percentage in the deposition of nanoparticles inside the channel and a total increase of 24.82% in the fitting function defined in terms of these three variables, compared to the channel designed in previous studies. Therefore, this optimal channel has a higher heat transfer rate with a pressure drop and a lower amount of nanoparticle deposition compared to the previous channel, which proves the ability of the genetic algorithm with computational fluid dynamics in the optimal design of all types of heat exchangers.