TASKED: Transformer-based Adversarial learning for human activity recognition using wearable sensors via Self-KnowledgE Distillation

Wearable sensor-based human activity recognition (HAR) has emerged as a principal research area and is utilized in a variety of applications. Recently, deep learning-based methods have achieved significant improvement in the HAR field with the development of human-computer interaction applications. However, they are limited to operating in a local neighborhood in the process of a standard convolution neural network, and correlations between different sensors on body positions are ignored. In addition, they still face significant challenging problems with performance degradation due to large gaps in the distribution of training and test data, and behavioral differences between subjects. In this work, we propose a novel Transformer-based Adversarial learning framework for human activity recognition using wearable sensors via Self-KnowledgE Distillation (TASKED), that accounts for individual sensor orientations and spatial and temporal features. The proposed method is capable of learning cross-domain embedding feature representations from multiple subjects datasets using adversarial learning and the maximum mean discrepancy (MMD) regularization to align the data distribution over multiple domains. In the proposed method, we adopt the teacher-free self-knowledge distillation to improve the stability of the training procedure and the performance of human activity recognition. Experimental results show that TASKED not only outperforms state-of-the-art methods on the four real-world public HAR datasets (alone or combined) but also improves the subject generalization effectively.Comment: 17 pages, 5 figures, Submitted to Knowledge-Based Systems, Elsevier. arXiv admin note: substantial text overlap with arXiv:2110.1216

Learning from the Best: Contrastive Representations Learning Across Sensor Locations for Wearable Activity Recognition

We address the well-known wearable activity recognition problem of having to work with sensors that are non-optimal in terms of information they provide but have to be used due to wearability/usability concerns (e.g. the need to work with wrist-worn IMUs because they are embedded in most smart watches). To mitigate this problem we propose a method that facilitates the use of information from sensors that are only present during the training process and are unavailable during the later use of the system. The method transfers information from the source sensors to the latent representation of the target sensor data through contrastive loss that is combined with the classification loss during joint training. We evaluate the method on the well-known PAMAP2 and Opportunity benchmarks for different combinations of source and target sensors showing average (over all activities) F1 score improvements of between 5% and 13% with the improvement on individual activities, particularly well suited to benefit from the additional information going up to between 20% and 40%.Comment: Presented at Ubicomp/ISWC 202

Unsupervised Statistical Feature-Guided Diffusion Model for Sensor-based Human Activity Recognition

Recognizing human activities from sensor data is a vital task in various domains, but obtaining diverse and labeled sensor data remains challenging and costly. In this paper, we propose an unsupervised statistical feature-guided diffusion model for sensor-based human activity recognition. The proposed method aims to generate synthetic time-series sensor data without relying on labeled data, addressing the scarcity and annotation difficulties associated with real-world sensor data. By conditioning the diffusion model on statistical information such as mean, standard deviation, Z-score, and skewness, we generate diverse and representative synthetic sensor data. We conducted experiments on public human activity recognition datasets and compared the proposed method to conventional oversampling methods and state-of-the-art generative adversarial network methods. The experimental results demonstrate that the proposed method can improve the performance of human activity recognition and outperform existing techniques

Avaliação de meio para produção de esporos e crescimento radial de Phytophthora cactorum

Six media were compared for sporangial production and radial growth of Phytophthora cactorum (Lebert & Cohn) Schroeter. The media included: frozen lima bean agar (FLB), clarified V-8 juice agar (V-8 juice), fresh potato dextrose agar (PDA), Difco corn meal agar (DCM), Difco lima bean agar (DLB), and a semi-synthetic medium (GN) containing salts, thiamine, glucose and nitrate. Sporangial production was greatest on FLB, followed by V-8 juice; all isolates consistently produced more sporangia on these two media than on the other media tested. Sporangial production was substantially less on DCM, while DLB, PDA, and GN gave very poor sporangial production. The best radial growth occurred on DLB, followed by V-8 juice, FLB, DCM, PDA, and GN, respectively. There was no significant difference in radial growth on V-8 juice and DLB, nor on V-8 juice and FLB; however, growth was significantly less (P=0.05) on all other media.Seis meios de cultura foram avaliados em sua eficiência para produzir esporângios de Phytophthora cactorum (Lebert & Cohn) Schroeter. Os meios incluíram: Feijão-lima-ágar (FLB) gelado; suco V-8-ágar clarificado (suco V-8); batata-dextrose-ágar (PDA) fresco; Farinha de milho-ágar, da Difco (DCM); Feijão-lima-ágar, da Difco (DLB); e um meio semi-sintético (GN) contendo sais, tiamina, glucose e nitrato. A produção de esporângios foi maior em FLB, seguido por suco V-8; todos os isolados de Phytophthora cactorum produziram consistentemente mais esporângios nestes dois meios. A produção de esporângios foi substancialmente menor em DCM, enquanto que em DLB, PDA e GN foi mínima. O maior crescimento radial do fungo ocorreu em DLB, seguido por suco V-8, FLB, DCM, PDA e GN, respectivamente. Não houve diferença significativa (P=0,05) no crescimento radial em suco V-8 e DLB, nem em suco V-8, e FLB; entretanto, o crescimento foi significativamente menor (P=0,05) em todos os outros meios de cultura

Synthesis and biological evaluation of mono and bis naphthalimides derivatives against SH-5Y-SY, human brain cancer cells

Naphthalimides (1H-benzo[de]isoquinoline-1,3-(2H)-diones) consists of a flat, generally π-deficient aromatic or heteroaromatic system and show strong hydrophobicity.1 These types of compounds with this moiety showed fluorescence and biological properties such as anticancer, antimicrobial, antitrypanosomal, analgesic, antioxidative and antiviral properties1-2 The naphthalimides compounds are also known to be very good DNA intercalators3, since the planar naphthalimido moiety binds by perpendicular insertion between the base pairs of the double helix of DNA.4 Previous work had already shown that mono and bis naphthalimido derivatives to exhibit strong activity against different cancer cell lines.5-6 Here in this work we would like to demonstrate that the alkyl chain i.e. the linker between the naphthalimido groups or the substituent attached at the end of the linker chain, do have an impact on the biological and DNA binding properties. The synthesis of new mono-naphthalimides derivatives involved the reaction with different aldehydes and with different length of alkyl chain. For the new bis-naphthalimides the reactions consist of an N-alkylation reaction between with different linkers and the corresponding O-tosyl alkylnaphthalimides. The biological activities of the newly synthesized compounds includes their ability to bind DNA, their toxicity against SH-5YSY human brain cancer cells in vitro, cell morphology and cellular uptake will also be presented.info:eu-repo/semantics/publishedVersio

Digital Extended Specimens: Enabling an Extensible Network of Biodiversity Data Records as Integrated Digital Objects on the Internet

The early twenty-first century has witnessed massive expansions in availability and accessibility of digital data in virtually all domains of the biodiversity sciences. Led by an array of asynchronous digitization activities spanning ecological, environmental, climatological, and biological collections data, these initiatives have resulted in a plethora of mostly disconnected and siloed data, leaving to researchers the tedious and time-consuming manual task of finding and connecting them in usable ways, integrating them into coherent data sets, and making them interoperable. The focus to date has been on elevating analog and physical records to digital replicas in local databases prior to elevating them to ever-growing aggregations of essentially disconnected discipline-specific information. In the present article, we propose a new interconnected network of digital objects on the Internet—the Digital Extended Specimen (DES) network—that transcends existing aggregator technology, augments the DES with third-party data through machine algorithms, and provides a platform for more efficient research and robust interdisciplinary discovery

Re-evaluation of neohesperidine dihydrochalcone (E 959) as a food additive

The present opinion deals with the re-evaluation of neohesperidine dihydrochalcone (E 959) when used as a food additive. It is obtained by catalytic hydrogenation of a flavanone - neohesperidine - which is naturally occurring and thus isolated by alcohol extraction in bitter oranges (Citrus aurantium). Based on in vivo data in rat, neohesperidine dihydrochalcone is likely to be absorbed, also in humans, and to become systemically available. It does not raise a concern regarding genotoxicity. The toxicity data set consisted of studies on subchronic and prenatal developmental toxicity. No human studies were available. The data set was considered sufficient to derive a new acceptable daily intake (ADI). Based on the weight of evidence (WoE) analysis, the Panel considered unlikely that neohesperidine dihydrochalcone would lead to adverse effects on health in animals in the dose ranges tested. The Panel also considered that a carcinogenicity study was not warranted and that the lack of human data did not affect the overall confidence in the body of evidence. The Panel derived an ADI of 20 mg/kg bodyweight (bw) per day based on a no observed adverse effect level (NOAEL) of 4,000 mg/kg bw per day from a 13-week study in rat, applying the standard default factors of 100 for inter- and intraspecies differences and of 2 for extrapolation from subchronic to chronic exposure. For the refined brand-loyal exposure assessment scenario, considered to be the most appropriate for the risk assessment, the exposure estimates at the mean ranged from < 0.01 to 0.09 mg/kg bw per day and at the 95th percentile (P95) from 0.01 to 0.24 mg/kg bw per day. Considering the derived ADI of 20 mg/kg bw per day, the exposure estimates were below the reference value in all age groups. Therefore, the Panel concluded that dietary exposure to the food additive neohesperidine dihydrochalcone (E 959) at the reported uses and use levels would not raise a safety concern

Water-loss (intracellular) dehydration assessed using urinary tests, how well do they work? Diagnostic accuracy in older people

Background: Water-loss dehydration (hypertonic, hyperosmotic or intra-cellular dehydration) is due to insufficient fluid intake and distinct from hypovolemia due to excess fluid losses. It is associated with poor health outcomes such as disability and mortality in older people. Urine specific gravity (USG), color and urine osmolality have been widely advocated for screening for dehydration in older adults. Objective: To assess the diagnostic accuracy of urinary measures to screen for water-loss dehydration in older people.Design: This was a diagnostic accuracy study of people aged ≥65years taking part in the Dehydration Recognition In our Elders (DRIE, living in long-term care) or Dietary Strategies for Healthy Ageing in Europe (NU-AGE, living in the community) studies. The reference standard was serum osmolality, index tests included USG, urine color, osmolality, cloudiness, additional dipstick measures, ability to provide a urine sample, and volume of a random urine sample. Minimum useful diagnostic accuracy was set at sensitivity and specificity ≥70% or receiver operating characteristics plot area under the curve ≥0.70. Results: DRIE participants (67% women, mean age 86 years, n=162) had more limited cognitive and functional abilities than NU-AGE participants (64% women, mean age 70 years, n=151). 19% of DRIE and 22% of NU-AGE participants were dehydrated (serum osmolality >300mOsm/kg). Neither USG nor any other potential urinary tests were usefully diagnostic for water-loss dehydration. Conclusions: Although USG, urine color and urinary osmolality have been widely advocated for screening for dehydration in older adults, we show in the largest study to date that their diagnostic accuracy is too low to be useful and these measures should not be used to indicate hydration status in older people (either alone or as part of a wider tranche of tests). There is a need to develop simple, inexpensive and non-invasive tools for the assessment of dehydration in older people

A European research agenda for somatic symptom disorders, bodily distress disorders, and functional disorders: Results of an estimate-talk-estimate delphi expert study

Background: Somatic Symptom Disorders (SSD), Bodily Distress Disorders (BDD) and functional disorders (FD) are associated with high medical and societal costs and pose a substantial challenge to the population and health policy of Europe. To meet this challenge, a specific research agenda is needed as one of the cornerstones of sustainable mental health research and health policy for SSD, BDD, and FD in Europe. Aim: To identify the main challenges and research priorities concerning SSD, BDD, and FD from a European perspective. Methods: Delphi study conducted from July 2016 until October 2017 in 3 rounds with 3 workshop meetings and 3 online surveys, involving 75 experts and 21 European countries. EURONET-SOMA and the European Association of Psychosomatic Medicine (EAPM) hosted the meetings. Results: Eight research priorities were identified: (1) Assessment of diagnostic profiles relevant to course and treatment outcome. (2) Development and evaluation of new, effective interventions. (3) Validation studies on questionnaires or semi-structured interviews that assess chronic medical conditions in this context. (4) Research into patients preferences for diagnosis and treatment. (5) Development of new methodologic designs to identify and explore mediators and moderators of clinical course and treatment outcomes (6). Translational research exploring how psychological and somatic symptoms develop from somatic conditions and biological and behavioral pathogenic factors. (7) Development of new, effective interventions to personalize treatment. (8) Implementation studies of treatment interventions in different settings, such as primary care, occupational care, general hospital and specialty mental health settings. The general public and policymakers will benefit from the development of new, effective, personalized interventions for SSD, BDD, and FD, that will be enhanced by translational research, as well as from the outcomes of research into patient involvement, GP-patient communication, consultation-liaison models and implementation. Conclusion: Funding for this research agenda, targeting these challenges in coordinated research networks such as EURONET-SOMA and EAPM, and systematically allocating resources by policymakers to this critical area in mental and physical well-being is urgently needed to improve efficacy and impact for diagnosis and treatment of SSD, BDD, and FD across Europe