Search Results (15)

Limulus amoebocyte lysate (LAL) assays have emerged as among the most effective approaches for detecting endotoxins and fungi in vitro since they were first tested 50 years ago. Although detailed protocols are publicly available, conventional LAL collection methods (3% sodium chloride) waste as much as 80% of the total LAL during blood accumulation, confirming the incompatibility of these methods with the lasting survival of the American horseshoe crab. For this reason, new implementations of blood collection–suspension buffer combinations are critical. Here, we evaluated the ability of different blood collection solutions to inhibit exocytosis and subsequently treated the cells with CaCl₂ to stimulate exocytosis and improve the yield of LAL. Two test methods, chromogenic and turbidimetric tests for LAL activity, were evaluated. Crabs were bled during the bleeding season. The crab blood samples were collected with the following blood collection solutions: citric acid buffer, malic acid buffer, PBS buffer, and PBS–caffeine buffer. The cell pellets were washed with 3% NaCl and subsequently resuspended in LRW or CaCl₂ to facilitate degranulation. Both the chromogenic test and the turbidimetric assay were used to evaluate the LAL enzyme activity. Citric acid buffer, malic acid buffer, PBS buffer, and PBS–caffeine buffer blocked exocytosis, resulting in the high yields of LAL. There was no observable effect on the activity output of crab size via a chromogenic test with PBS–caffeine buffer during the bleeding season. This protocol substantially benefited prior processes, as the PBS–caffeine collection mixture decreased amoebocyte aggregation/clot formation during processing. Furthermore, we evaluated the specific biochemical parameters of PBS–caffeine-derived LAL. We developed an accessible, promising phosphate–caffeine-based blood collection buffer that prevents amoebocyte degranulation during blood collection, maximizing the LAL yield. Moreover, our analysis revealed that phosphate–caffeine-derived LAL is uniquely adaptable to compatibility with chromogenic and turbidimetric assay techniques. By employing this method for LAL blood extraction, our same-cost approach fostered significantly greater LAL yields, simultaneously ensuring a healthy limulus polyphemus population. Full article

Lipreading involves recognizing spoken words by analyzing the movements of the lips and surrounding area using visual data. It is an emerging research topic with many potential applications, such as human–machine interaction and enhancing audio-based speech recognition. Recent deep learning approaches integrate visual features from the mouth region and lip contours. However, simple methods such as concatenation may not effectively optimize the feature vector. In this article, we propose extracting optimal visual features using 3D convolution blocks followed by a ResNet-18, while employing a graph neural network to extract geometric features from tracked lip landmarks. To fuse these complementary features, we introduce a cross-attention mechanism that combines visual and geometric information to obtain an optimal representation of lip movements for lipreading tasks. To validate our approach for Arabic, we introduce the first large-scale Lipreading in the Wild for Arabic (LRW-AR) dataset, consisting of 20,000 videos across 100 word classes, spoken by 36 speakers. Experimental results on both the LRW-AR and LRW datasets demonstrate the effectiveness of our approach, achieving accuracies of 85.85% and 89.41%, respectively. Full article

Due to various historical events, in the Russian Federation, in addition to the radioactive waste storage facilities used in world practice, there are various nuclear and radiation hazardous facilities that require special procedures for monitoring and decommissioning. One of these facilities is the disposal site for LRW on the territory of the JSC Siberian Chemical Plant, where specially prepared waste is injected into sand reservoirs lying at depths of 300–350 m between clayey strata. This study examines in detail the features of the lithological and mineral composition of reservoir sands and aquitards. The processes of environmental transformation in reservoir sands, which lead to changes in the composition and structure of rocks, were characterized. These processes manifest themselves in the form of the development of leaching zones and their “healing” with newly formed smectite, the destruction of terrigenous grains, including the development of cracks, and the growth of newly formed smectite in the pore space of reservoirs. The forms of occurrence and localization of authigenic smectite formed as a result of technogenic impact are described. It has been shown that, despite the obvious impact of highly reactive solutions accompanying liquid radioactive waste, the insulating properties of the geological environment are maintained and even improved to some extent. Full article

This study investigated the agriculture risks and opportunities in a fragile watershed, the Lanyang River Watershed (LRW) in Northeastern Taiwan, under the current situation of climate change. Agriculture in the LRW is a traditional sector, highly vulnerable to climate change, and is a declining economic sector due to the trend of trade liberalization of agriculture. At present, the government of Taiwan encourages local farmers to transform towards recreational farm types. Leisure agriculture operators have successfully transitioned their tilling to a business model of recreational farming. A telephone survey of leisure agriculture operators was applied with a three-stage approach to obtain their opinions. The results showed that climate change may entail risks for agriculture in watersheds. Transformation to leisure agriculture can enhance farm adaptation and increase farm income. The long-term implementation of slope- and geology-based land classification and land use planning can protect the watershed, especially from extreme weather, while enhancing water and soil conservation efforts, and bolstering climate resilience. Innovative agricultural practices offer viable solutions, including greenhouse farming for high-economic-value crops, leisure agriculture, organic farming, and ecotourism. These strategies can rejuvenate the LRW’s agriculture industry, foster ecological tourism, and provide opportunities for traditional farmers to thrive in this highly climate-fragile area. The implications of this case study are that appropriate responses can improve local climate resilience, and that correspondingly well-designed adaptation measures can transform threats and risks into new opportunities. Full article

This article presents a study of the synthesis and characterization of new biphasic hybrid composite materials consisting of intercalated complexes (ICC) of natural mineral bentonite with copper hexaferrocyanide (phase I), which are incorporated into the bulk of the polymer matrix (phase II). It has been established that the sequential modification of bentonite with copper hexaferrocyanide and introduction of acrylamide and acrylic acid cross-linked copolymers into its volume by means of in situ polymerization promote the formation of a heterogeneous porous structure in the resulting hybrid material. The sorption abilities of prepared hybrid composite toward radionuclides of liquid radioactive waste (LRW) have been studied, and the mechanism for binding radionuclide metal ions with the components of the hybrid composition have been described. Full article

The present work describes the results of the removal of cesium by sorbents of various classes from highly mineralized alkaline solutions simulating the clarified phase of storage tanks with high-level radioactive waste (HLW) of the Mayak Production Association. Within the scope of the performed works, inorganic sorbents of the Clevasol^® and Fersal brands, as well as resorcinol-formaldehyde ion-exchange resins (RFRs: RFR-i, RFR-Ca, and Axionit RCs), were used. The sorbents’ characteristics under both static and dynamic conditions are presented. The Fersal sorbent has demonstrated the best sorption characteristics in the series of sorbents under study. The disadvantage of inorganic sorbents is the loss of mechanical strength upon cesium desorption, which complicates their repeated use. It has been demonstrated that RFRs, despite their lower selectivity towards cesium and adsorption capacity, can be used many times in repeated sorption-desorption cycles. The latter makes RFRs more technologically attractive in terms of the total volume of decontaminated HLW. However, RFRs tend to be oxidized during storage, which results in the formation of carboxyl groups and a decrease in sorption characteristics—this must be further taken into account in the real processes of liquid radioactive waste (LRW) management. Full article

This paper studies various deep learning models for word-level lip-reading technology, one of the tasks in the supervised learning of video classification. Several public datasets have been published in the lip-reading research field. However, few studies have investigated lip-reading techniques using multiple datasets. This paper evaluates deep learning models using four publicly available datasets, namely Lip Reading in the Wild (LRW), OuluVS, CUAVE, and Speech Scene by Smart Device (SSSD), which are representative datasets in this field. LRW is one of the large-scale public datasets and targets 500 English words released in 2016. Initially, the recognition accuracy of LRW was 66.1%, but many research groups have been working on it. The current the state of the art (SOTA) has achieved 94.1% by 3D-Conv + ResNet18 + {DC-TCN, MS-TCN, BGRU} + knowledge distillation + word boundary. Regarding the SOTA model, in this paper, we combine existing models such as ResNet, WideResNet, WideResNet, EfficientNet, MS-TCN, Transformer, ViT, and ViViT, and investigate the effective models for word lip-reading tasks using six deep learning models with modified feature extractors and classifiers. Through recognition experiments, we show that similar model structures of 3D-Conv + ResNet18 for feature extraction and MS-TCN model for inference are valid for four datasets with different scales. Full article

Audio-visual speech recognition (AVSR) is one of the most promising solutions for reliable speech recognition, particularly when audio is corrupted by noise. Additional visual information can be used for both automatic lip-reading and gesture recognition. Hand gestures are a form of non-verbal communication and can be used as a very important part of modern human–computer interaction systems. Currently, audio and video modalities are easily accessible by sensors of mobile devices. However, there is no out-of-the-box solution for automatic audio-visual speech and gesture recognition. This study introduces two deep neural network-based model architectures: one for AVSR and one for gesture recognition. The main novelty regarding audio-visual speech recognition lies in fine-tuning strategies for both visual and acoustic features and in the proposed end-to-end model, which considers three modality fusion approaches: prediction-level, feature-level, and model-level. The main novelty in gesture recognition lies in a unique set of spatio-temporal features, including those that consider lip articulation information. As there are no available datasets for the combined task, we evaluated our methods on two different large-scale corpora—LRW and AUTSL—and outperformed existing methods on both audio-visual speech recognition and gesture recognition tasks. We achieved AVSR accuracy for the LRW dataset equal to 98.76% and gesture recognition rate for the AUTSL dataset equal to 98.56%. The results obtained demonstrate not only the high performance of the proposed methodology, but also the fundamental possibility of recognizing audio-visual speech and gestures by sensors of mobile devices. Full article

The efficiency of the removal of Cs-137 radionuclides with porous and non-porous resorcinol–formaldehyde resins from alkaline solutions simulating the composition of real liquid radioactive waste (LRW) streams has been evaluated. Resins were synthesized through the polycondensation of resorcinol and formaldehyde in an alkaline medium at a molar ratio of 1.8/2.2 and a temperature of 210 °C. The Cs-137 distribution coefficients on RFRs in alkaline solutions simulating LRW were above 10³ mL/g under static sorption conditions. In a model solution with pH 11, the full dynamic sorption capacity of non-porous RFR was 0.178 mmol/g. The values of the full dynamic sorption capacities of porous RFRs were 0.274 and 1.035 mmol/g for resins obtained with calcium carbonate and toluene as templates, respectively. When the sizes of RFR beads increased two-fold, the volume until 5% cesium breakthrough decreased by 20–40%. The most pronounced beneficial effect of the RFR’s porosity was observed at flow rates from 25 to 50 BV/h. It was shown that the negative effect of metal cations on Cs-137 uptake increases in the following order: Na⁺ < Mg²⁺ < Ca²⁺ < K⁺. The number of bed volumes of LRW-simulating solution decontaminated with RFRs until 5% cesium breakthrough was above 450; that is higher than the value of known commercially available analogs. The latter shows that the developed RFRs are promising for application in technological schemes of alkaline LRW processing. Full article

Lip movements contain essential linguistic information. It is an important medium for studying the content of the dialogue. At present, there are many studies on how to improve the accuracy of lip language recognition models. However, there are few studies on the robustness and generalization performance of the model under various disturbances. Specific experiments show that the current state-of-the-art lip recognition model significantly drops in accuracy when disturbed and is particularly sensitive to adversarial examples. This paper substantially alleviates this problem by using Mixup training. Taking the model subjected to negative attacks generated by FGSM as an example, the model in this paper achieves 85.0% and 40.2% accuracy on the English dataset LRW and the Mandarin dataset LRW-1000, respectively. The correct recognition rates are improved by 9.8% and 8.3%, compared with the current advanced lip recognition models. The positive impact of Mixup training on the robustness and generalization of lip recognition models is demonstrated. In addition, the performance of the lip recognition classification model depends more on the training parameters, which increase the computational cost. The InvNet-18 network in this paper reduces the consumption of GPU resources and the training time while improving the model accuracy. Compared with the standard ResNet-18 network used in mainstream lip recognition models, the InvNet-18 network in this paper has more than three times lower GPU consumption and 32% fewer parameters. After detailed analysis and comparison in various aspects, it is demonstrated that the model in this paper can effectively improve the model’s anti-interference ability and reduce training resource consumption. At the same time, the accuracy is comparable with the current state-of-the-art results. Full article

A series of resorcinol–formaldehyde resins (RFR) samples for Cs-137 removal from liquid alkaline media have been synthesized. It has been demonstrated that the chemical stability as well as sorption characteristics are determined by the resorcinol/formaldehyde molar ratio and the solidification temperature. It has been also demonstrated that the sample synthesized at the resorcinol/formaldehyde molar ratio of 1.8/2.2 and solidified at 210 °C is characterized by the best sorption-selective characteristics and chemical stability. Under dynamic conditions, at feeding >1000 bed volumes of a model solution with pH > 13, the RFR 3-1 goes through six sorption cycles without noticeable changes in the sorption characteristics. The results are presented that demonstrate the possibility of RFR application in the decontamination of real LRW from Cs-137. Full article

In 2002, Agrawal and Kiernan defined six basic requirements, including preventing illegal watermark embedding and authentication, reversibility, robustness, and others, which must be satisfied when a reversible watermark is designed for relational databases. To meet these requirements, in this paper, a lossless watermarking scheme for a categorical relational database called LRW-CRDB (lossless robust watermarking for categorical relational databases) is proposed. In our LRW-CRDB scheme, the database owner needs to generate two secret embedding keys, K₁ and K₂, in advance. Then, two reference sets are generated based on two different secret embedding keys and a symmetry-based data hiding strategy, and then these are used for the watermark embedding phases. Experimental results confirmed that our LRW-CRDB scheme successfully detects 100% of hidden watermarks, even when more than 95% of the watermarked relational database has been deleted. In other words, the robustness of our proposed LRW-CRDB scheme outperforms other existing schemes under a variety of possible attacks, such as alteration, sorting, deletion, and mix-match attacks. Full article

Lupins (Lupinus spp.) are an ancient yet important legume crop. In Europe, the protein-rich seeds serve as livestock feed and have the potential to be a healthy vegetarian component of human diets. In some regions in north-eastern Europe, lupins are heavily damaged by two Curculionidae species, the lupin root weevils (LRWs) Charagmus gressorius (syn. Sitona gressorius) and Ch. griseus (syn. S. griseus). Narrow-leaved lupins (L. angustifolius) and white lupins (L. albus) are most affected. The weevils feed on lupin leaves, whereas their larvae feed on root nodules. Therefore, the larvae cause major root damage by creating lacerations that allow soil-borne plant pathogens to enter the plant tissue. These infestations lead to considerable yield losses and markedly reduced N-fixation of the root nodules. This review summarises the current knowledge on the origin, geographical distribution, and biology of these rarely described weevils. It focuses on management strategies, including preconceived insecticide use and potential ecological management methods, as key components of an integrated pest management programme against LRWs in Europe. Full article

Lip reading (LR) is the task of predicting the speech utilizing only the visual information of the speaker. In this work, for the first time, the benefits of alternating between spatiotemporal and spatial convolutions for learning effective features from the LR sequences are studied. In this context, a new learnable module named ALSOS (Alternating Spatiotemporal and Spatial Convolutions) is introduced in the proposed LR system. The ALSOS module consists of spatiotemporal (3D) and spatial (2D) convolutions along with two conversion components (3D-to-2D and 2D-to-3D) providing a sequence-to-sequence-mapping. The designed LR system utilizes the ALSOS module in-between ResNet blocks, as well as Temporal Convolutional Networks (TCNs) in the backend for classification. The whole framework is composed by feedforward convolutional along with residual layers and can be trained end-to-end directly from the image sequences in the word-level LR problem. The ALSOS module can capture spatiotemporal dynamics and can be advantageous in the task of LR when combined with the ResNet topology. Experiments with different combinations of ALSOS with ResNet are performed on a dataset in Greek language simulating a medical support application scenario and on the popular large-scale LRW-500 dataset of English words. Results indicate that the proposed ALSOS module can improve the performance of a LR system. Overall, the insertion of ALSOS module into the ResNet architecture obtained higher classification accuracy since it incorporates the contribution of the temporal information captured at different spatial scales of the framework. Full article

The problem of effective immobilization of liquid radioactive waste (LRW) is key to the successful development of nuclear energy. The possibility of using the magnesium potassium phosphate (MKP) compound for LRW immobilization on the example of nitric acid solutions containing actinides and rare earth elements (REE), including high level waste (HLW) surrogate solution, is considered in the research work. Under the study of phase composition and structure of the MKP compounds that is obtained by the XRD and SEM methods, it was established that the compounds are composed of crystalline phases—analogues of natural phosphate minerals (struvite, metaankoleite). The hydrolytic stability of the compounds was determined according to the semi-dynamic test GOST R 52126-2003. Low leaching rates of radionuclides from the compound are established, including a differential leaching rate of ²³⁹Pu and ²⁴¹Am—3.5 × 10⁻⁷ and 5.3 × 10⁻⁷ g/(cm²∙day). As a result of the research work, it was concluded that the MKP compound is promising for LRW immobilization and can become an alternative material combining the advantages of easy implementation of the technology, like cementation and the high physical and chemical stability corresponding to a glass-like compound. Full article