Developing the procedure-enhanced model of ginger-infused sesame oil based on its flavor and functional properties.

Ginger-infused sesame oil enriches the nutrition and provides enhanced flavor for the foods. An original processing procedure and module for evaluation were established in this study, using different raw materials (Guangdong and Chu ginger) and treatments (ginger powder, extract, and both). The quality, functionality, and flavor of the infused oils were evaluated. Ginger-infused sesame oil contained 0.58-3.22 µg/g of 6-gingerol, 0.21-0.88 µg/g of 6-shogaol. The number range of volatile compounds from 48 to 55 identified by gas chromatography-mass spectrometry varies depending on different process procedures. Agglomerative hierarchical clustering analysis revealed the flavor profiles were clustered by different varieties, while gingerol and phytosterol was by different treatments. In conclusion, sesame oil was an appropriate carrier for gingerol and phytosterol, which are characterized by higher antioxidant capacities (p < 0.05). These results show the benefits of developing infused oil products with enhanced functional and sensory properties.

Discussion on the Differences in Aroma Components in Different Fragrant Rice Varieties during Storage.

Rice (Oryza sativa L.) is an important food crop in Taiwan, among which fragrant rice is highly regarded for its special aroma when cooked. During the storage of fragrant rice, the aroma components will change, which will affect the aroma quality of fragrant rice. Therefore, headspace solid-phase microextraction (HS-SPME) was used in this study, combined with gas chromatography and gas chromatography-mass spectrometry, to analyze the difference in the aroma components of Taikeng No. 4 (TK4), Tainung No. 71 (TN71), Kaohsiung No. 147 (KH147), and Taichung No. 194 (TC194) fragrant rice. A total of 28 aroma components were identified in the four varieties of fragrant rice, and the main components were all Nonanal. Among them, TK4 contains a very high content of hydrocarbons, including Tridecane and Dodecane; TN71, KH147, and TC194 contain mainly aldehydes such as Nonanal and Hexanal. During different storage times, the contents of alcohols, monoterpenes, aromatic aldehydes, and furans increased with storage time, while the content of aliphatic aldehydes decreased with storage time. After storage, the fragrant rice samples showed a tendency for the total volatile component content to decrease, with the most pronounced reduction observed in Nonanal content.

Heterogeneous Domain Adaptation With Adversarial Neural Representation Learning: Experiments on E-Commerce and Cybersecurity.

Learning predictive models in new domains with scarce training data is a growing challenge in modern supervised learning scenarios. This incentivizes developing domain adaptation methods that leverage the knowledge in known domains (source) and adapt to new domains (target) with a different probability distribution. This becomes more challenging when the source and target domains are in heterogeneous feature spaces, known as heterogeneous domain adaptation (HDA). While most HDA methods utilize mathematical optimization to map source and target data to a common space, they suffer from low transferability. Neural representations have proven to be more transferable; however, they are mainly designed for homogeneous environments. Drawing on the theory of domain adaptation, we propose a novel framework, Heterogeneous Adversarial Neural Domain Adaptation (HANDA), to effectively maximize the transferability in heterogeneous environments. HANDA conducts feature and distribution alignment in a unified neural network architecture and achieves domain invariance through adversarial kernel learning. Three experiments were conducted to evaluate the performance against the state-of-the-art HDA methods on major image and text e-commerce benchmarks. HANDA shows statistically significant improvement in predictive performance. The practical utility of HANDA was shown in real-world dark web online markets. HANDA is an important step towards successful domain adaptation in e-commerce applications.

Analysis of Volatile Compounds from Different Parts of Houttuynia cordata Thunb.

Houttuynia cordata Thunb. is a medicinal and edible plant that has been commonly used in traditional Chinese medicine since ancient times. This study used headspace solid-phase microextraction (HS-SPME) and direct injection, combined with gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS), to identify the volatile compounds in H. cordata. Extraction from different parts of the plant using different extraction techniques for the identification of volatile compounds were determined. A total of 93 volatile components were analyzed in the leaves, stems, rhizomes, and whole plant samples of H. cordata. The leaves contained more (Z)-3-hexenal, ß-myrcene, (Z)-ß-ocimene, and (4E,6E)-allo-ocimene; the stems contained more geranyl acetate and nerolidol; and rhizomes contained more α-pinene, ß-pinene, limonene, 2-undecanone, and decanoyl acetaldehyde. Among them, the essential oil extracted by HS-SPME could produce more monoterpenes, while direct injection could obtain higher contents of aliphatic ketones, terpene esters, sesquiterpenes, and was more conducive to the extraction of 2-undecanone and decanoyl acetaldehyde.

Chemical Properties of Peanut Oil from Arachis hypogaea L. 'Tainan 14' and Its Oxidized Volatile Formation.

Arachis hypogaea L. 'Tainan 14' has purple skin characteristics. This study investigated the effects of different materials (shelled or unshelled peanuts) and temperatures (120 or 140 °C) on the properties of extracted peanut oil. The results show that its antioxidant components (total flavonoid, α−tocopherol, and γ-tocopherol) and oxidative stability were mainly affected by the roasting temperature (p < 0.05). Fifty-eight volatile compounds were identified by peanut oil oxidation and divided into three main groups during the roasting process using principal component analysis. The volatile formation changes of different materials and temperatures were assessed by agglomerative hierarchical clustering analysis. These results provide useful reference information for peanut oil applications in the food industry.

Effects of Different Extraction Methods on Vanilla Aroma.

To establish the analytic conditions for examining the aroma quality of vanilla pods, we compared different extraction methods and identified a suitable option. We utilized headspace solid-phase microextraction (HS-SPME), steam distillation (SD), simultaneous steam distillation (SDE) and alcoholic extraction combined with gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS) to identify volatile components of vanilla pods. A total of 84 volatile compounds were identified in this experiment, of which SDE could identify the most volatile compounds, with a total of 51 species, followed by HS-SPME, with a total of 28 species. Ten volatile compounds were identified by extraction with a minimum of 35% alcohol. HS-SPME extraction provided the highest total aroma peak areas, and the peak areas of aldehydes, furans, alcohols, monoterpenes and phenols compounds were several times higher than those of the other extraction methods. The results showed that the two technologies, SDE and HS-SPME, could be used together to facilitate analysis of vanilla pod aroma.

New Insights on Volatile Components of Vanilla planifolia Cultivated in Taiwan.

Vanilla (Vanilla planifolia) is a precious natural flavoring that is commonly used throughout the world. In the past, all vanilla used in Taiwan was imported; however, recent breakthroughs in cultivation and processing technology have allowed Taiwan to produce its own supply of vanilla. In this study, headspace solid-phase microextraction (HS-SPME) combined with GC-FID and GC-MS was used to analyze the volatile components of vanilla from different origins produced in Taiwan under different cultivation and processing conditions. The results of our study revealed that when comparing different harvest maturities, the composition diversity and total volatile content were both higher when the pods were matured for more than 38 weeks. When comparing different killing conditions, we observed that the highest vanillin percentage was present after vanilla pods were killed three times in 65 °C treatments for 1 min each. From the experiment examining the addition of different strains, the PCA results revealed that the volatiles of vanilla that was processed with Dekkera bruxellensis and Bacillus subtilis was clearly distinguished from which obtained by processing with the other strains. Vanilla processed with B. subtilis contained 2-ethyl-1-hexanol, and this was not detected in other vanillas. Finally, when comparing the vanillin percentage from seven different regions in Taiwan, vanilla percentage from Taitung and Taoyuan Longtan were the highest.

Headspace Solid-Phase Microextraction Analysis of Volatile Components in Peanut Oil.

Peanut oil is favored by consumers due to its rich nutritional value and unique flavor. This study used headspace solid-phase microextraction (HS-SPME) combined with gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS) to examine the differences in the peanut oil aroma on the basis of variety, roasting temperatures, and pressing components. The results revealed that the optimal conditions for extracting peanut oil were achieved through the use of 50/30 µm DVB/CAR/PDMS fibers at 60 °C for 50 min. The primary compounds present in peanut oil were pyrazines. When peanuts were roasted, the temperature raised from 120 °C to 140 °C and the content of aldehydes in peanut oil increased; however, the content of aldehydes in No. 9 oil at 160 °C decreased. The components of peanut shell oil varied depending on the peanut variety. The most marked difference was observed in terms of the main compound at the two roasting temperatures. This compound was a pyrazine, and the content increased with the roasting temperature in hekei oils. When the roasting temperature was lower, No. 9 oil contained more fatty acid oxidation products such as hexanal, heptanal, and nonanal. When the roasting temperature increased, No. 9 oil contained more furfural and 5-methylfurfural. Heren oil was easier to oxidize and produced nonanal that possessed a fatty aroma.

Magnoliae Flos Essential Oil as an Immunosuppressant in Dendritic Cell Activation and Contact Hypersensitivity Responses.

Magnoliae Flos is a commonly used traditional medicinal material in Asia. It is used to treat sinusitis, nasal congestion, and hypersensitive skin. Because Magonlia Flos was described as an aromatic material in ancient Chinese texts, we hypothesized that its essential oil may be used to treat immune disorders. Dendritic cells (DCs), regarded as a major target of immunomodulators to control immune responses, play a critical role in the adaptive immune response. In this study, Magnoliae Flos essential oil (MFEO) decreased the production of the cytokines TNF-α, IL-6, and IL-12p70 in lipopolysaccharide (LPS)-stimulated DCs. It also suppressed the surface markers MHC II, CD80, and CD86 in LPS-stimulated DCs. Animal models demonstrated that the 2,4-Dinitro-1-fluorobenzene (DNFB) inducing a contact hypersensitivity response was inhibited following treatment with MFEO. In addition, MFEO inhibited the infiltration of T cells in the ears of DNFB-induced mice. To explore its bioactive compounds, the components of MFEO were analyzed using gas chromatography (GC) and GC-mass spectrometry. The results revealed that the major compounds in MFEO are camphor and 1,8-cineole. Additional DC bioassays confirmed that these compounds substantially suppressed cytokine production in LPS-induced DCs. Therefore, we demonstrated that MFEO exhibits an immunosuppressive effect both in vivo and in vitro, and camphor and 1,8-cineole may be the major components responsible for its immunosuppressive ability. The findings indicate that MFEO has the potential to be developed as a new immunosuppressant for excessive diseases.

Cypripedium subtropicum (Orchidaceae) employs aphid colony mimicry to attract hoverfly (Syrphidae) pollinators.

In Orchidaceae, pollination is mostly animal-mediated, and one-third of species have evolved a deceptive pollination mechanism without rewards. Cypripedium is a representative lineage of nonrewarding orchids restricted to temperate regions. Cypripedium subtropicum flowers are pollinated by hoverflies and have hairy tufts that visually resemble an aphid colony covered with honey dew. We recorded the behavior of hoverflies on the flowers, determined the breeding system of the species and the structure of hairy tufts, and investigated the roles of hairy tufts and floral volatiles in this specialized pollination by using pollination experiments, scanning electron microscopy, bioassays and chemical analyses. The white hairy tufts covering the sidelobes of the labellum provide edible rewards and serve as crucial visual lures for hoverflies. The flowers emit primarily (E)-ß-farnesene and a smaller amount of ß-pinene that were found to attract hoverflies. Our results suggest that C. subtropicum uses both visual mimicry of an aphid-colonized labellum with a reward and chemical mimicry of aphid alarm pheromones to attract hoverflies for pollination. This is the first described example of a rewarding mimicry system in plants, where the models are animals with their secretions and the reward is similar in nutrients to that of the model mimicked.

Analysis of Volatile Constituents in Platostoma palustre (Blume) Using Headspace Solid-Phase Microextraction and Simultaneous Distillation-Extraction.

Hsian-tsao (Platostoma palustre Blume) is a traditional Taiwanese food. It is admired by many consumers, especially in summer, because of its aroma and taste. This study reports the analysis of the volatile components present in eight varieties of Hsian-tsao using headspace solid-phase microextraction (HS-SPME) and simultaneous distillation-extraction (SDE) coupled with gas chromatography (GC) and gas chromatography-mass spectrometry (GC/MS). HS-SPME is a non-heating method, and the results show relatively true values of the samples during flavor isolation. However, it is a kind of headspace analysis that has the disadvantage of a lower detection ability to relatively higher molecular weight compounds; also, the data are not quantitative, but instead are used for comparison. The SDE method uses distillation 2 h for flavor isolation; therefore, it quantitatively identifies more volatile compounds in the samples while the samples withstand heating. Both methods were used in this study to investigate information about the samples. The results showed that Nongshi No. 1 had the highest total quantity of volatile components using HS-SPME, whereas SDE indicated that Taoyuan Mesona 1301 (TYM1301) had the highest volatile concentration. Using the two extraction methods, 120 volatile components were identified. Fifty-six volatile components were identified using HS-SPME, and the main volatile compounds were α-pinene, ß-pinene, and limonene. A total of 108 volatile components were identified using SDE, and the main volatile compounds were α-bisabolol, ß-caryophyllene, and caryophyllene oxide. Compared with SDE, HS-SPME sampling extracted a significantly higher amount of monoterpenes and had a poorer detection of less volatile compounds, such as sesquiterpenes, terpene alcohols, and terpene oxide.

Lime (Citrus aurantifolia (Christm.) Swingle) Essential Oils: Volatile Compounds, Antioxidant Capacity, and Hypolipidemic Effect.

Lime peels are mainly obtained from the byproducts of the juice manufacturing industry, which we obtained and used to extract essential oil (2.3%) in order to examine the antioxidant and hypolipidaemic effects. We identified 60 volatile compounds of lime essential oil (LEO) with GC/MS, of which the predominant constituents were limonene, γ-terpinene, and ß-pinene. Lime essential oil was measured according to the DPPH assay and ABTS assay, with IC50 values of 2.36 mg/mL and 0.26 mg/mL, respectively. This study also explored the protective effects of LEO against lipid-induced hyperlipidemia in a rat model. Two groups of rats received oral LEO in doses of 0.74 g/100 g and 2.23 g/100 g with their diets. Eight weeks later, we found that the administration of LEO improved the serum total cholesterol, triglyceride, low-density lipoprotein cholesterol, alanine aminotransferase, and aspartate transaminase levels in the hyperlipidemic rats (p < 0.05). Simultaneously, the LEO improved the health of the rats in terms of obesity, atherogenic index, and fatty liver.

Hidden Markov Model-Based Fall Detection With Motion Sensor Orientation Calibration: A Case for Real-Life Home Monitoring.

Falls are a major threat for senior citizens' independent living. Motion sensor technologies and automatic fall detection systems have emerged as a reliable low-cost solution to this challenge. We develop a hidden Markov model (HMM) based fall detection system to detect falls automatically using a single motion sensor for real-life home monitoring scenarios. We propose a new representation for acceleration signals in HMMs to avoid feature engineering and developed a sensor orientation calibration algorithm to resolve sensor misplacement issues (misplaced sensor location and misaligned sensor orientation) in real-world scenarios. HMM classifiers are trained to detect falls based on acceleration signal data collected from motion sensors. We collect a dataset from experiments of simulated falls and normal activities and acquired a dataset from a real-world fall repository (FARSEEING) to evaluate our system. Our system achieves positive predictive value of 0.981 and sensitivity of 0.992 on the experiment dataset with 200 fall events and 385 normal activities, and positive predictive value of 0.786 and sensitivity of 1.000 on the real-world fall dataset with 22 fall events and 2618 normal activities. Our system's results significantly outperform benchmark systems, which shows the advantage of our HMM-based fall detection system with sensor orientation calibration. Our fall detection system is able to precisely detect falls in real-life home scenarios with a reasonably low false alarm ratet.

A sequence-to-sequence model-based deep learning approach for recognizing activity of daily living for senior care.

Ensuring the health and safety of independent-living senior citizens is a growing societal concern. Researchers have developed sensor based systems to monitor senior citizens' Activity of Daily Living (ADL), a set of daily activities that can indicate their self-caring ability. However, most ADL monitoring systems are designed for one specific sensor modality, resulting in less generalizable models that is not flexible to account variations in real-life monitoring settings. Current classic machine learning and deep learning methods do not provide a generalizable solution to recognize complex ADLs for different sensor settings. This study proposes a novel Sequence-to-Sequence model based deep-learning framework to recognize complex ADLs leveraging an activity state representation. The proposed activity state representation integrated motion and environment sensor data without labor-intense feature engineering. We evaluated our proposed framework against several state-of-the-art machine learning and deep learning benchmarks. Overall, our approach outperformed baselines in most performance metrics, accurately recognized complex ADLs from different types of sensor input. This framework can generalize to different sensor settings and provide a viable approach to understand senior citizen's daily activity patterns with smart home health monitoring systems.

The Variation of Oncidium Rosy Sunset Flower Volatiles with Daily Rhythm, Flowering Period, and Flower Parts.

Oncidium is an important ornamental crop worldwide, and in recent years, the characteristics of the flower aroma have become a concern for breeders. This study used headspace solid-phase microextraction (HS-SPME) and gas chromatography/mass spectrometry (GC-MS) analysis of the volatile compounds to study the aroma characteristics of Onc. Rosy Sunset. A total of 45 compounds were identified, with the major compound being linalool. Onc. Rosy Sunset had the highest odor concentration from 10:00 to 12:00 and lowest from 20:00 to 24:00. The inflorescence emitted the highest quantities of volatile compounds during stages 3-6, which then decreased with the aging of the flowers. In Onc. Rosy Sunset, the sepals and petals were the major parts for the floral fragrance emission, in which linalool content was the highest, whereas the lip and column had a different composition of major volatile compounds, of which benzaldehyde, ß-myrcene, and ß-caryophyllene dominated.

Immunosuppressive Effect of Litsea cubeba L. Essential Oil on Dendritic Cell and Contact Hypersensitivity Responses.

Litsea cubeba L., also named as Makauy, is a traditional herb and has been used as cooking condiment or tea brewing to treat diseases for aborigines. The present study was undertaken to explore the chemical compositions of the fruit essential oil of L. cubeba (LCEO) and the immunomodulatory effect of LCEO on dendritic cells and mice. The LCEO was analyzed using gas chromatography (GC) and gas chromatography/mass spectrometry (GC/MS) with direct injection (DI/GC) or headspace-solid phase microextraction (HS-SPME/GC). In total, 56 components were identified, of which 48 were detected by DI/GC and 49 were detected by HS-SPME/GC. The principal compounds were citral (neral and geranial). An immunosuppressive activity of LCEO was investigated with bone marrow-derived dendritic cells (DCs) which have a critical role to trigger the adaptive immunity. Additionally, the inhibitory effect of LCEO on immune response was elucidated by performing the contact hypersensitivity (CHS) responses in mice. Our results clearly showed that LCEO decreases the production of TNF-α and cytokine IL-12 in a dose-dependent manner in lipopolysaccharide (LPS)-stimulated DCs. CHS response and the infiltrative T cells were inhibited in the tested ears of the mice co-treated with LCEO. We demonstrate, for the first time, that the LCEO mainly containing citral exhibits an immunosuppressive effect on DCs and mice, indicating that LCEO can potentially be applied in the treatment of CHS, inflammatory diseases, and autoimmune diseases.

Characterization of Secondary Metabolites from Purple Ipomoea batatas Leaves and Their Effects on Glucose Uptake.

Ipomoea batatas has long been used in folk medicine for the treatment of hyperglycemia or as a food additive for the prevention of type 2 diabetes. However, neither the plant extract nor its active components have been evaluated systematically. In this work four crude extracts, including n-hexane- (IBH), 95% MeOH- (IBM), n-BuOH- (IBB), and H2O-soluble (IBW) fractions, were prepared by fractionation of a methanolic extract of purple I. batatas leaves. Twenty-four pure compounds 1-24 were then isolated by various chromatographic techniques and their structures identified from NMR and MS data. Glucose uptake assays in differentiated 3T3-L1 adipocytes and rat primary hepatocytes, as well as western blot analysis, were carried out to evaluate the antidiabetic activity of this species. The IBH crude fraction, with methyl decanoate (22) as a major and active compound, showed the greatest effect on glucose uptake, most likely via activation of Glut4 and regulation of the PI3K/AKT pathway. Quercetin 3-O-ß-d-sophoroside (1), quercetin (3), benzyl ß-d-glucoside (10), 4-hydroxy-3-methoxybenzaldehyde (12), and methyl decanoate (22) could be important components contributing to the antidiabetic effects. We conclude that purple I. batatas leaves have potential as an antidiabetic plant source and the active constituents 1, 3, 10, 12, and 22 are promising lead candidates for future investigation.

Epidemic model for information diffusion in web forums: experiments in marketing exchange and political dialog.

As social media has become more prevalent, its influence on business, politics, and society has become significant. Due to easy access and interaction between large numbers of users, information diffuses in an epidemic style on the web. Understanding the mechanisms of information diffusion through these new publication methods is important for political and marketing purposes. Among social media, web forums, where people in online communities disseminate and receive information, provide a good environment for examining information diffusion. In this paper, we model topic diffusion in web forums using the epidemiology model, the susceptible-infected-recovered (SIR) model, frequently used in previous research to analyze both disease outbreaks and knowledge diffusion. The model was evaluated on a large longitudinal dataset from the web forum of a major retail company and from a general political discussion forum. The fitting results showed that the SIR model is a plausible model to describe the diffusion process of a topic. This research shows that epidemic models can expand their application areas to topic discussion on the web, particularly social media such as web forums.

A research framework for pharmacovigilance in health social media: Identification and evaluation of patient adverse drug event reports.

Social media offer insights of patients' medical problems such as drug side effects and treatment failures. Patient reports of adverse drug events from social media have great potential to improve current practice of pharmacovigilance. However, extracting patient adverse drug event reports from social media continues to be an important challenge for health informatics research. In this study, we develop a research framework with advanced natural language processing techniques for integrated and high-performance patient reported adverse drug event extraction. The framework consists of medical entity extraction for recognizing patient discussions of drug and events, adverse drug event extraction with shortest dependency path kernel based statistical learning method and semantic filtering with information from medical knowledge bases, and report source classification to tease out noise. To evaluate the proposed framework, a series of experiments were conducted on a test bed encompassing about postings from major diabetes and heart disease forums in the United States. The results reveal that each component of the framework significantly contributes to its overall effectiveness. Our framework significantly outperforms prior work.