Optimization of Mixed Solid-state Fermentation of Soybean Meal by Lactobacillus Species and Clostridium butyricum

Soybean meal is the main vegetable protein source in animal feed. Soybean meal contains several anti-nutritional factors, which directly affect digestion and absorption of soy protein, thereby reducing growth performance and value in animals. Fermented soybean meal is rich in probiotics and functional metabolites, which facilitates soybean protein digestion, absorption and utilization in piglets. However, the mixed solid-state fermentation (SSF) conditions of soybean meal remain to be optimized. In this study, we investigated the optimal parameters for SSF of soybean meal by Lactobacillus species and Clostridium butyricum. The results showed that two days of fermentation was sufficient to increase the viable count of bacteria, lactic acid levels and degradation of soybean protein in fermented soybean meal at the initial moisture content of 50%. The pH value, lowering sugar content and oligosaccharides in fermented soybean meal, was significantly reduced at the initial moisture content of 50% after two days of fermentation. Furthermore, the exogenous proteases used in combination with probiotics supplementation were further able to enhance the viable count of bacteria, degradation of soybean protein and lactic acid level in the fermented soybean meal. In addition, the pH value and sugar content in fermented soybean meal were considerably reduced in the presence of both proteases and probiotics. Furthermore, the fermented soybean meal also showed antibacterial activity against Staphylococcus aureus and Escherichia coli. These results together suggest that supplementation of both proteases and probiotics in SSF improves the nutritional value of fermented soybean meal and this is suitable as a protein source in animal feed

Time-Selective RNN for Device-Free Multi-Room Human Presence Detection Using WiFi CSI

Human presence detection is a crucial technology for various applications, including home automation, security, and healthcare. While camera-based systems have traditionally been used for this purpose, they raise privacy concerns. To address this issue, recent research has explored the use of channel state information (CSI) approaches that can be extracted from commercial WiFi access points (APs) and provide detailed channel characteristics. In this thesis, we propose a device-free human presence detection system for multi-room scenarios using a time-selective conditional dual feature extract recurrent Network (TCD-FERN). Our system is designed to capture significant time features with the condition on current human features using a dynamic and static (DaS) data preprocessing technique to extract moving and spatial features of people and differentiate between line-of-sight (LoS) path blocking and non-blocking cases. To mitigate the feature attenuation problem caused by room partitions, we employ a voting scheme. We conduct evaluation and real-time experiments to demonstrate that our proposed TCD-FERN system can achieve human presence detection for multi-room scenarios using fewer commodity WiFi APs

Development of Rifampicin-Indocyanine Green-Loaded Perfluorocarbon Nanodroplets for Photo-Chemo-Probiotic Antimicrobial Therapy

Acne vulgaris, generally resulted from overgrowth of Propionibacterium acnes (P. acnes), is one of the most difficult-to-treat facial dermatoses and more than 90% of adolescents experienced the disease worldwide. Because the innate non-lymphoid immune system cannot effectively eliminate excessive P. acnes from the skin surface, so far the therapy of acne vulgaris is still mainly dependent on antibiotic treatment. However, long-term or overdose of antibiotics may initiate microbial drug resistance and/or generate unexpected side effects that seriously hamper the use of antibiotics in the clinic. To overcome the aforementioned challenges, the novel rifampicin (RIF)-indocyanine green (ICG)-loaded perfluorocarbon (PFC) nanodroplets (RIPNDs) that may offer combined photo-, chemo-, and probiotic efficacies to P. acnes eradication were developed in this study. The RIPND was first characterized as a sphere-like nanoparticle with surface charge of −20.9 ± 2.40 mV and size of 240.7 ± 6.73 nm, in which the encapsulation efficiencies of RIF and ICG were 54.0 ± 10.5% and 95.0 ± 4.84%, respectively. In comparison to the freely dissolved ICG, the RIPNDs conferred an enhanced thermal stability to the entrapped ICG, and were able to provide a comparable hyperthermia effect and markedly increased production of singlet oxygen under near infrared (NIR; 808 nm, 6 W/cm2) exposure. Furthermore, the RIPNDs were able to induce fermentation of S. epidermidis but not P. acnes, indicating that the RIPNDs may serve as a selective fermentation initiator for the target probiotics. Based on the microbial population index analyses, P. acnes with 1 × 106 cells/mL can be completely eradicated by 12-h co-culture with S. epidermidis fermentation products followed by treatment of RIPNDs (≥20-μM ICG/3.8-μM RIF) + NIR for 5 min, whereby the resulted microbial mortality was even higher than that caused by using 16-fold enhanced amount of loaded RIF alone. Overall these efforts show that the RIPNDs were able to provide improved ICG stability, selective fermentability to S. epidermidis, and enhanced antimicrobial efficacy compared to equal dosage of free RIF and/or ICG, indicating that the developed nanodroplets are highly potential for use in the clinical anti-P. acne treatment with reduced chemotoxicity

Attention-based Learning for Sleep Apnea and Limb Movement Detection using Wi-Fi CSI Signals

Wi-Fi channel state information (CSI) has become a promising solution for non-invasive breathing and body motion monitoring during sleep. Sleep disorders of apnea and periodic limb movement disorder (PLMD) are often unconscious and fatal. The existing researches detect abnormal sleep disorders in impractically controlled environments. Moreover, it leads to compelling challenges to classify complex macro- and micro-scales of sleep movements as well as entangled similar waveforms of cases of apnea and PLMD. In this paper, we propose the attention-based learning for sleep apnea and limb movement detection (ALESAL) system that can jointly detect sleep apnea and PLMD under different sleep postures across a variety of patients. ALESAL contains antenna-pair and time attention mechanisms for mitigating the impact of modest antenna pairs and emphasizing the duration of interest, respectively. Performance results show that our proposed ALESAL system can achieve a weighted F1-score of 84.33, outperforming the other existing non-attention based methods of support vector machine and deep multilayer perceptron

Prediagnosis of Obstructive Sleep Apnea via Multiclass MTS

Obstructive sleep apnea (OSA) has become an important public health concern. Polysomnography (PSG) is traditionally considered an established and effective diagnostic tool providing information on the severity of OSA and the degree of sleep fragmentation. However, the numerous steps in the PSG test to diagnose OSA are costly and time consuming. This study aimed to apply the multiclass Mahalanobis-Taguchi system (MMTS) based on anthropometric information and questionnaire data to predict OSA. Implementation results showed that MMTS had an accuracy of 84.38% on the OSA prediction and achieved better performance compared to other approaches such as logistic regression, neural networks, support vector machine, C4.5 decision tree, and rough set. Therefore, MMTS can assist doctors in prediagnosis of OSA before running the PSG test, thereby enabling the more effective use of medical resources

Management and control of coccidiosis in poultry — A review

Poultry coccidiosis is an intestinal infection caused by an intracellular parasitic protozoan of the genus Eimeria. Coccidia-induced gastrointestinal inflammation results in large economic losses, hence finding methods to decrease its prevalence is critical for industry participants and academic researchers. It has been demonstrated that coccidiosis can be effectively controlled and managed by employing anticoccidial chemical compounds. However, as a result of their extensive use, anticoccidial drug resistance in Eimeria species has raised concerns. Phytochemical/herbal medicines (Artemisia annua, Bidens pilosa, and garlic) seem to be a promising strategy for preventing coccidiosis, in accordance with the “anticoccidial chemical-free” standards. The impact of herbal supplements on poultry coccidiosis is based on the reduction of oocyst output by preventing the proliferation and growth of Eimeria species in chicken gastrointestinal tissues and lowering intestinal permeability via increased epithelial turnover. This review provides a thorough up-to-date assessment of the state of the art and technologies in the prevention and treatment of coccidiosis in chickens, including the most used phytochemical medications, their mode of action, and the applicable legal framework in the European Union

VI-Band Follow-Up Observations of Ultra-Long-Period Cepheid Candidates in M31

The ultra-long period Cepheids (ULPCs) are classical Cepheids with pulsation periods exceeding $\approx 80$ days. The intrinsic brightness of ULPCs are ~1 to ~3 mag brighter than their shorter period counterparts. This makes them attractive in future distance scale work to derive distances beyond the limit set by the shorter period Cepheids. We have initiated a program to search for ULPCs in M31, using the single-band data taken from the Palomar Transient Factory, and identified eight possible candidates. In this work, we presented the VI-band follow-up observations of these eight candidates. Based on our VI-band light curves of these candidates and their locations in the color-magnitude diagram and the Period-Wesenheit diagram, we verify two candidates as being truly ULPCs. The six other candidates are most likely other kinds of long-period variables. With the two confirmed M31 ULPCs, we tested the applicability of ULPCs in distance scale work by deriving the distance modulus of M31. It was found to be $\mu_{M31,ULPC}=24.30\pm0.76$ mag. The large error in the derived distance modulus, together with the large intrinsic dispersion of the Period-Wesenheit (PW) relation and the small number of ULPCs in a given host galaxy, means that the question of the suitability of ULPCs as standard candles is still open. Further work is needed to enlarge the sample of calibrating ULPCs and reduce the intrinsic dispersion of the PW relation before re-considering ULPCs as suitable distance indicators.Comment: 13 pages, with 14 Figures and 4 Tables (one online table). AJ accepte