Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparation and Some Properties of Protein Hydrolysate from Broiler Esophagus

The production of protein hydrolysate from esophagus of broiler from poultry processing waste was studied. The esophagus is composed of 13.91% protein, 82.77% moisture, 0.85% fat, 2.15% carbohydrate and 0.32% ash. The pigment and fat removal by washing for 15 minutes with 0.3, 0.5 and 0.7% sodium bicarbonate (NaHCO3) solution compared with water (control) showed that when the NaHCO3 concentration increased the redness (a*) and fat content of chicken esophagus decreased. The redness of sample washed by 0.3 and 0.5% NaHCO3 was not significantly different while a significant (p<0.05) higher fat reduction was observed at 0.5%NaHCO3. Therefore washing with 0.5% NaHCO3 solution was adopted as raw material preparation for hydrolysis study using Alcalase and Papain at 55 and 65 o C for 1 h. At the same concentration (0.1-0.9% w/w) Papain exhibited higher efficiency than Alcalase. Alcalase of 0.3% was selected to study the effect of hydrolysis time on degree of hydrolysis (DH). The results suggested that digestion for 17, 50 and 85 min resulted in the protein hydrolysis with DH of 6, 14 and 22% respectively. The compositions of all three DH level hydrolysates were 78.75-86.85% protein, 6.46-7.45% moisture, 0.760. 84% fat and 3.16-3.99% ash. The higher DH caused the higher solubility but lower emulsifying activity index, emulsion stability index, foaming capacity and foaming stability of protein hydrolysate from broiler esophagus.
CpG island methylation of genes accumulates during the adenoma progression step of the multistep pathogenesis of colorectal cancer

Genetic alterations occur during the adenoma‐carcinoma sequence of colon cancer formation and drive the initiation and progression of colon cancer formation. The aberrant methylation of genes is an alternate, epigenetic mechanism for silencing tumor suppressor genes in colon cancer. The aim of this study was to determine on a global and gene‐specific level the role of CpG island methylation in the initiation and progression of colon cancer. Consequently, we assessed the frequency of gene methylation in tumors representative of the commonly recognized histological steps of the adenoma‐carcinoma progression sequence through the analysis of eight genes previously identified to be methylated in colon cancer, MGMT, HLTF, MLH1, p14ARF, CDKN2A, TIMP3, THBS1, and CDH1. We observed that the proportion of tumors carrying methylated alleles increased from adenomas to adenocarcinomas but that the proportion of tumors with methylated alleles was not different between adenocarcinomas and metastases (69% versus 90%, P = 0.01 and 90% versus 81%, P > 0.05). The most substantial difference occurred between early and advanced adenomas (47% versus 84%, P = 0.018). Furthermore, we observed that the frequency of gene methylation at the different steps of the progression sequence varied between genes. Thus, the aberrant methylation of genes appears to increase most significantly during the progression of early adenomas to advanced adenomas, and the frequency of specific gene methylation at the different steps of the adenoma‐carcinoma progression sequence varies in a gene‐specific fashion. © 2006 Wiley‐Liss, Inc.
Pay Me Later: Inside Debt and its Role in Managerial Compensation

Though widely used in executive compensation, inside debt has been almost entirely overlooked by prior work. We initiate this research by studying CEO pension arrangements in 237 large capitalization firms. Among our findings are that CEO compensation exhibits a balance between debt and equity incentives; the balance shifts systematically away from equity and toward debt as CEOs grow older; annual increases in pension entitlements represent about 10% of overall CEO compensation, and about 13% for CEOs aged 61–65; CEOs with high debt incentives manage their firms conservatively; and pension compensation influences patterns of CEO turnover and cash compensation.
Caregiving networks-using a network approach to identify missed opportunities.

OBJECTIVES This study demonstrates the added value to caregiving research by using a multi-informant social network approach within the context of Alzheimer's disease and related dementia. METHOD Sixty-six informants from 24 families enumerated caregiving network members in 2012. Comparisons were made between networks based on a single informant versus multiple informants in terms of network composition and caregiving roles, core-periphery structure, and identification of "missed opportunities" in recruitment. RESULTS On average, each informant beyond the index enumerated 6.2 new members, resulting in about 10 new members per family network when the multiple-informant approach is used. Compared with index informants' networks, multi-informant networks showed an 85% increase in identification of direct care providers (1.71 compared with 3.42) and a 48% increase in identification of those involved in care decision making (3.33 compared with 4.92). Informants from the same network generally showed agreement in reported participation in caregiving activities. However, the reports of non-participation in these roles were less consistent among the informants. Resulting structure indicated a core caregiving network (M = 6.12 members), with semi-peripheral and peripheral members (M = 5.19 and M = 14.83 members, respectively). DISCUSSION Results suggest that an iterative, targeted sampling approach with at least three informants allows for a more comprehensive assessment of caregiving processes. Applying this approach in future research will greatly enhance our knowledge and better inform future interventions to facilitate family adaptation.
The Brain's Default Network

Thirty years of brain imaging research has converged to define the brain's default network—a novel and only recently appreciated brain system that participates in internal modes of cognition. Here we synthesize past observations to provide strong evidence that the default network is a specific, anatomically defined brain system preferentially active when individuals are not focused on the external environment. Analysis of connectional anatomy in the monkey supports the presence of an interconnected brain system. Providing insight into function, the default network is active when individuals are engaged in internally focused tasks including autobiographical memory retrieval, envisioning the future, and conceiving the perspectives of others. Probing the functional anatomy of the network in detail reveals that it is best understood as multiple interacting subsystems. The medial temporal lobe subsystem provides information from prior experiences in the form of memories and associations that are the building blocks of mental simulation. The medial prefrontal subsystem facilitates the flexible use of this information during the construction of self‐relevant mental simulations. These two subsystems converge on important nodes of integration including the posterior cingulate cortex. The implications of these functional and anatomical observations are discussed in relation to possible adaptive roles of the default network for using past experiences to plan for the future, navigate social interactions, and maximize the utility of moments when we are not otherwise engaged by the external world. We conclude by discussing the relevance of the default network for understanding mental disorders including autism, schizophrenia, and Alzheimer's disease.
Combining Web Usage Mining and Fuzzy Inference for Website Personalization

Personalization tailors a user’s interaction with the Web information space based on information gathered about them. Declarative user information such as manually entered profiles continue to raise privacy concerns and are neither scalable nor flexible in the face of very active dynamic Web sites and changing user trends and interests. One way to deal with this problem is through a complete automated Web personalization system. Such a system can be based on Web usage mining to discover Web usage profiles, followed by a recommendation system that can respond to the users’ individual interests. Significant amounts of error and uncertainty can permeate all the stages of Web personalization. Therefore, we present a fast and intuitive approach to provide Web recommendations using a fuzzy inference engine with rules that are automatically derived from prediscovered user profiles. We perform extensive simulations with real data to study the effect of different parametrization options, and to empirically compare the performance of the proposed approach with that of collaborative filtering and nearest-profile based recommendation strategies. This paper’s main contributions are: The proposal of a profile based fuzzy recommendation engine with extensive empirical comparison of different fuzzy input membership derivation and parametrization options, and comparison with approaches based on collaborative filtering and nearest profile recommendations. The proposed fuzzy recommendation method achieves high coverage compared to K-NN and nearest-profile recommendations despite slightly lower precision. Finally, we note that fuzzy recommendations are very intuitive, deal with natural overlap in user interests, and are very low in cost compared to collaborative filtering: They are extremely faster and require much lower main memory at recommendation time (no need to store or compare to a large number of instances). This makes fuzzy recommendations suitable for real time recommendations in a live setting on today's most active and huge websites.
Effect of nerve cell currents on MRI images in snail ganglia

We performed extracellular potential recording with dissected snail ganglia inside an MRI scanner to investigate correlation between neuronal activity and MR image intensity. To increase neuronal activity we applied a nitric oxide donor, sodium-nitrosocystein, to the ganglia. The MR image intensity change in the ganglia region is correlated with the neuronal activity and was up to 5.49±1.94%. Since the snail has non-magnetic hemocyanins as oxygen carrying protein, it seems that the image intensity change is mainly due to the local magnetic fields produced by the neuronal currents.
How to effectively use topic models for software engineering tasks? An approach based on Genetic Algorithms

Information Retrieval (IR) methods, and in particular topic models, have recently been used to support essential software engineering (SE) tasks, by enabling software textual retrieval and analysis. In all these approaches, topic models have been used on software artifacts in a similar manner as they were used on natural language documents (e.g., using the same settings and parameters) because the underlying assumption was that source code and natural language documents are similar. However, applying topic models on software data using the same settings as for natural language text did not always produce the expected results. Recent research investigated this assumption and showed that source code is much more repetitive and predictable as compared to the natural language text. Our paper builds on this new fundamental finding and proposes a novel solution to adapt, configure and effectively use a topic modeling technique, namely Latent Dirichlet Allocation (LDA), to achieve better (acceptable) performance across various SE tasks. Our paper introduces a novel solution called LDA-GA, which uses Genetic Algorithms (GA) to determine a near-optimal configuration for LDA in the context of three different SE tasks: (1) traceability link recovery, (2) feature location, and (3) software artifact labeling. The results of our empirical studies demonstrate that LDA-GA is able to identify robust LDA configurations, which lead to a higher accuracy on all the datasets for these SE tasks as compared to previously published results, heuristics, and the results of a combinatorial search.
Effect of rumen-protected methionine on productionand composition of early lactating Shami goatsmilk and growth performance of their kids

Abstract. This study was conducted at the Agricultural Research Station of the University of Jordan in the Jordan valley to evaluate the effect of supplementing rumen-protected methionine to early lactating Shami goats on milk production, composition, fatty acid profile, and growth performance of their kids. Twenty-four fresh lactating Shami goats were randomly assigned into three dietary treatment groups (eight each) in a completely randomized design. Diets were a control with no supplements or supplemented with either 2.5, or 5.0 g/head/d rumenprotected methionine. The experiment started exactly after kidding and lasted for 60 days thereafter. Production variables studied were milk production, milk composition, body weights, feed intake, kids weaning weight, and milk fatty acids. Daily milk production and energy corrected milk were not affected by protected me thionine supplementation. Milk Percentages of fat, protein, total solids, and casein were also not affected by protected methionine supplementation. Likewise, fat and protein yields were not different among dietary treatments of protected methionine. No differences in milk fatty acids composition were observed by supplementing rumen protected methionine in the experiment. Feed intake, feed to milk ratio, and final body weight of dams were not changed among treatments. No differences were observed in weaning weights, average daily gain, and milk to gain ratio of kids born to dams in the experiment regardless to sex of kids. In conclusion, results indicated that supplementing rumen protected methionine to dairy goats diet did not improve their milking performance, the composition of their milk, or growth performance of their kids.
Improvement of an Automatic HPLC System for Nitropolycyclic Aromatic Hydrocarbons: Removal of an Interfering Peak and Increase in the Number of Analytes

An automatic HPLC system for analyzing nitropolycyclic aromatic hydrocarbons (NPAHs, nitroarenes) in airborne particulates was previously described ( Anal. Chim. Acta , 2001 , 445 , 20). Some problems with this system were that it generated a peak originating from an ascorbic acid solution that elutes at a retention time close to that of 1,6-dinitropyrene (DNP), and that it was able to analyze only 1,3-, 1,6-, 1,8-DNPs and 1-nitropyrene (1-NP). Here, we describe an improved system that effectively removes the interfering peak by introducing an ODS column just after the pump for the ascorbic acid solution, and which is capable of analyzing several additional compounds (2-, 4-NPs, 2-nitrofluorene, 6-nitrochrysene, 7-nitrobenz[ a ]anthracene, 3-nitroperylene and 6-nitrobenzo[ a ]pyrene etc .). The improved sensitivities were achieved by concentrating the compounds in a benzene-ethanol extract from airborne particulates, by increasing the loading time of the sample solution from 20 to 38 min, and by increasing the flow rate of an ascorbic acid solution from 1.3 to 1.8 mL/min.
Scalable logo recognition in real-world images

In this paper we propose a highly effective and scalable framework for recognizing logos in images. At the core of our approach lays a method for encoding and indexing the relative spatial layout of local features detected in the logo images. Based on the analysis of the local features and the composition of basic spatial structures, such as edges and triangles, we can derive a quantized representation of the regions in the logos and minimize the false positive detections. Furthermore, we propose a cascaded index for scalable multi-class recognition of logos. For the evaluation of our system, we have constructed and released a logo recognition benchmark which consists of manually labeled logo images, complemented with non-logo images, all posted on Flickr. The dataset consists of a training, validation, and test set with 32 logo-classes. We thoroughly evaluate our system with this benchmark and show that our approach effectively recognizes different logo classes with high precision.
Enhanced microarray performance using low complexity representations of the transcriptome

Low abundance mRNAs are more difficult to examine using microarrays than high abundance mRNAs due to the effect of concentration on hybridization kinetics and signal-to-noise ratios. This report describes the use of low complexity representations (LCRs) of mRNA as the targets for cDNA microarrays. Individual sequences in LCRs are more highly represented than in the mRNA populations from which they are derived, leading to favorable hybridization kinetics. LCR targets permit the measurement of abundance changes that are difficult to measure using oligo(dT) priming for target synthesis. An oligo(dT)-primed target and three LCRs detect twice as many differentially regulated genes as could be detected by the oligo(dT)-primed target alone, in an experiment in which serum-starved fibroblasts responded to the reintroduction of serum. Thus, this target preparation strategy considerably increases the sensitivity of cDNA microarrays.
Marked decrease in the incidence and prevalence of hepatitis A in the Basque Country, Spain, 1986–2004

The aim of this study was to determine changes in the epidemiology of hepatitis A virus (HAV) infection in the Basque Country, Spain, and to evaluate their implications for vaccination strategies. A total of 1356 persons were enrolled in a study of the prevalence of anti-HAV in 2004 and compared with two previous studies (1986–1987 and 1992). The selection method and the characteristics of the population were similar in the three studies. A marked decline in the seroprevalence in all age groups (P<0·001) and in the incidence of cases/100000 inhabitants (from 38·0 in 1986–1988 to 2·9 in 2002–2004) were observed. The mean age of patients with hepatitis A increased from 17·7 years in 1986–1992 to 21·2 years in 1993–1998 and 25·3 years in 1999–2004 (P<0·001). Between 1997 and 2004, 20% of patients were hospitalized. The changes observed have occurred rapidly causing a change in the epidemiological pattern from middle-high endemicity (1986) to low endemicity (2004).
Deflection Reading Accuracy and Layer Thickness Accuracy in Backcalculation of Pavement Layer Moduli

Accurate deflection readings must be obtained when using nondestructive testing (NDT) devices in order to obtain correct backcalculated layer moduli. This paper provides an analysis of the sources of deflection errors and illustrates through a series of examples how random deflection errors and random pavement thickness errors affect backcalculated moduli. The consequence of these errors is most pronounced in the backcalculated modulus of the surface course. The moduli of the base and subbase layers are also affected, and the subgrade moduli are only slightly affected by these errors. To some degree this outcome may be due to the bottom-to-top approach used by the backcalculation program MODCOMP2. The consequence of the variability of the backcalculated moduli on the required pavement overlay thickness was found to be minimal. This was due to the fact that, generally speaking, data errors which cause an overestimate of the base course modulus also cause an approximately equally significant, but opposite, underestimation of the surface course modulus. Thus, the needed overlay requirement remains nearly the same. The paper shows how certain falling weight deflectometer (FWD) calibration and testing procedures can be used to minimize deflection measurement errors. The accuracy of backcalculated moduli is shown to be determinable from the RMS error of the deflection fit. The examples provide an impression of the extent to which random layer thickness errors and deflection measurement errors will influence the ability to discern point-to-point variability of layer moduli for the specific pavement structure considered in this investigation. This provides a perspective from which the practical accuracy of the backcalculation approach can be judged.
SELECTION AND USE OF THE PROCEDURES FOR LABORATORY COMPACTION OF BITUMINOUS MIXTURES

The paper describes the laboratory compaction methods available to determine a reference density for bituminous mixtures. This reference density is to be used as a target for field compaction; specimens used for the determination of the performance related properties are compacted at this reference density. It also describes methods to characterize the compactibility of bituminous mixtures. It finally deals with the methods available to prepare the specimens to be used to measure the performance related properties. Reference is made to the relevant draft European standards. The gyratory compactor seems to have the best potential for the determination of the reference density, and the rolling wheel compaction for the preparation of the specimens for mechanical testing. (A) For the covering abstract see IRRD 896365.
Is there a relation between dental anxiety, fear and general psychological status?

Background Dental anxiety is a widespread problem in many populations. This problem can be a barrier to dental care and may lead to poor oral health. Dental anxiety may be related to psychological status. Aims The aim of the present study was to assess the levels of dental anxiety, dental fear, Beck Depression, and state-trait anxiety according to age, gender and education level in patients at the periodontology clinic in the Diyarbakır Mouth and Dental Health Center. Study Design A total of 231 patients (115 males, 116 females) filled out dental fear scale (DFS), dental anxiety scale (DAS), Beck Depression Inventory (BDI), state-trait anxiety inventory-state (STAI-S), and state-trait anxiety inventory–trait (STAI-T) questionnaires, and evaluations of DFS, DAS, BDI, STAI-S, and STAI-T were conducted according to age, gender, and education level. Results The mean DFS, DAS, BDI, STAI-T, and STAI –S were 45.64, 9.15, 13.16, 38.90, and 40.18, respectively. There was a significant association among DFS, DAS, BDI, STAI-S, and STAI-T (p < 0.05). These surveys scores were significantly higher in females than males (p < 0.05). The results of this study indicated that gender age and education level have important effects on DFS, DAS, BDI, STAI-S, and STAI-T (p < 0.05). Conclusion Dental anxiety and dental fear were found to be related to psychological status (BDI, STAI-S, and STAI-T) over time. There are some patients with unaddressed psychological distress.
Comparison of clinical characteristics in episodic and chronic obsessive–compulsive disorder

Our objective in this study was to compare the demographics and clinical characteristics of patients with episodic and chronic obsessive–compulsive disorder (OCD). We recruited 128 outpatients with a primary diagnosis of OCD according to DSM‐IV diagnostic criteria. The episodic (n=24) and chronic (n=104) OCD patient groups were compared with respect to demographic variables and scores from various psychiatric rating scales. The severity of compulsions was found to be significantly lower in the episodic OCD group than in the chronic OCD group. When the frequency of Axis I disorders was assessed in the two groups, bipolar disorder was found to have a significantly higher prevalence rate in the episodic OCD group than that in the chronic OCD group. The results of our study point to the possibility of an association between a subgroup of OCD with an episodic course and bipolar disorder. The evidence of such a relationship, which needs to be confirmed in a larger sample, might expand the scope of the clinical assessment and therapy of this subgroup of OCD. Depression and Anxiety 24:251–255, 2007. © 2006 Wiley‐Liss, Inc.