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Due to their excellent physicochemical properties, carbon-based nanomaterials (CBNs) have attracted considerable attention for multiple applications, including electronics, optoelectronics, photonics and biomedicine. An active area of research is related to their potential exploitation at the skin level, mainly as wearable and stretchable electronic devices for health-care monitoring, cosmetics, sunscreens, but also in the field of regenerative medicine for wound healing. These applications and the potential occupational exposure to CBNs during their manufacturing can lead to a significant skin contact as one of the major but underestimated exposure routes for humans, raising concern for possible adverse effects. This issue motivated an up-to-date revision of the available toxicological data on the effects of CBNs (fullerenes, carbon-nanotubes, graphene-based materials, carbon nano-onions and carbon nano-horns) after cutaneous exposure. The review is focused on the main adverse outcomes at the skin level (irritation, corrosion, sensitization, phototoxicity and relevant mechanisms) as available evidences useful to address human health risk issues related to CBNs. Currently, toxicity data on CBNs are very scarce, representing only 3.8% of total publications on CBN-based skin applications. Among all CBNs, the main data are available for fullerenes and carbon-nanotubes, with very scanty or no information for the others. Although some of them (e.g., fullerenes or some kinds of carbon-nanotubes) appear skin biocompatible, available toxicological data are not sufficient to fully characterize the hazard posed at the cutaneous level. Therefore, toxicological studies on CBN skin applications need to be implemented, enabling their wide and safe use.

Objectives Castration is any action, surgical or chemical, by which an individual loses use of the gonads, most commonly referring to loss of the testicles. Reference to elective castration has been, according to Diodorus, as old as the human record itself, first being practiced in pharaonic Egypt. Castration has been practiced as a means to produce eunuchs, a punitive measure in military and secular courts, and a source of trophy-taking in warfare. The role of castration in the control of advanced and metastatic prostate cancer became a well recognized standard of care in the mid-20th century earning Nobel Prizes for its pioneers. Our aim was to better understand the history of human castration and its transformation from an instrument of terror to a standard and sometimes life-saving urological treatment. Methods A literature review on human castration was performed through Medline, PubMed, the Gutenburg Project, and Google Scholar searching words “castration”, “eunuch”, “orchiectomy” and “androgen deprivation”. We accessed the public archives of the British Museum (London) and digital classical libraries as cited. Reports were collected to create a timeline. Results First reports of human castration date back to the 21st century (BCE) in the ancient city of Lagash, Sumeria when used for the creation of court eunuchs. Castration figured prominently in most ancient cultures from myth to jurisprudence. The god Uranus was castrated by his son, Cronus (Saturn), with an adamantine sickle, throwing the severed gonads into the sea. There is at least conjectural evidence of castration on medical, criminal, and even volitional grounds from pharaonic and classical history through medieval and modern times. Primitive medical observations recognized the different phenotypes of pre-pubertal and post-pubertal eunuchs especially on the voice which may account for the popularity of some castrati in the history of choral music. Castration was a well-established procedure in the domestication of animals for millennia but it was only in 1941 that Charles Huggins and others first demonstrated the effects of bilateral orchiectomy in the control of prostate cancer. Medical castration, now with special androgen receptor inhibitors, continues to be a mainstay in the management of metastatic and hormone refractory prostate cancer. Conclusions Medical or surgical castration plays an important role in the modern management of advanced prostate cancer. Castration has existed in human cultures for thousands of years, although its true prevalence is unknown, accounted for in the folklore and sparse records typical of ancient times.

To confirm the correlation between post-void residual urine ratio (PVR-R) and BOO diagnosed by pressure-flow studies (PFS) in males with lower urinary tract symptoms (LUTS) and to develop a clinical nomogram.A consecutive series of patients aged 45 years or older with non-neurogenic LUTS were prospectively enrolled. Patients underwent standard diagnostic assessment for BOO including International Prostatic Symptoms Score, uroflowmetry, urodynamic studies, suprapubic ultrasound of the prostate, and ultrasound measurements of the bladder wall thickness (BTW). PVR-R was defined as follows: PVR-R = (PVR/total Bladder Volume [BV]) × 100). Logistic regression analysis was used to investigate predictors of pathological bladder emptying (BOO) defined as Schafer II. A nomogram to predict BOO based on the multivariable logistic regression model was then developed.Overall 335 patients were enrolled. Overall, 131/335 (40%) presented BOO on PFS. In a multivariable logistic age-adjusted regression model BWT (odds ratio [OR]: 2.21 per mm; 95% confidence interval [CI], 1.57-3.09; p = 0.001), PVR-R (OR: 1.02 per %; 95% CI, 1.01-1.03; p = 0.034) and prostate volume (OR: 0.97 per mL; 95% CI, 0.95-0.98; p = 0.001) were significant predictors for BOO. The model presented an accuracy of 0.82 and a clinical net benefit in the range of 10-90%.The present study confirms the important role of PVR-ratio in the prediction of BOO. For the first time, we present a clinical nomogram including PVR-ratio for the prediction of BOO.

The report lifts the curtain on the Brazilian data workers involved in global AI production chains. They do 'micro-tasks' to generate and annotate data for machine learning, while also checking algorithmic outputs and occasionally, taking the place of failing automation. They use international digital labor platforms through which they execute on-demand tasks, mostly for AI producers located in the Global North. As platform workers, they are paid by piecework and have no long-term commitment to the buyers of their outputs. Some highlights:- Three out of five Brazilian data workers are women, while in most other previously-surveyed countries, women are a minority (one in three or less). - 9 reais (1.73 euros) per hour is the average amount earned on platforms.- There are at least 54 micro-working platforms operating in Brazil.- One third of Brazilian data workers have no other source of income, and depend on microworking platforms for subsistence.- Two out of five Brazilian data workers are (apart from this activity) unemployed, without professional activity, or in informality. In Brazil, platform microwork arises out of widespread unemployment and informalization of work.- Three out of five of data workers have completed undergraduate education, although they mostly do repetitive and unchallenging online data tasks, suggesting some form of skill mismatch.- The worst microtasks involve moderation of violent and pornographic contents on social media, as well as data training in tasks that workers may find uncomfortable or weird, such as taking pictures of dog poop in domestic environments to train data for "vacuuming robots".- Workers' main grievances are linked to uncertainty, lack of transparency, job insecurity, fatigue and lack of social interaction on platforms.

International audience; Today’s artificial intelligence, largely based on data-intensive machine learning algorithms, relies heavily on the digital labour of invisibilized and precarized humans-in-the-loop who perform multiple functions of data preparation, verification of results, and even impersonation when algorithms fail. Using original quantitative and qualitative data, the present article shows that these workers are highly educated, engage significant (sometimes advanced) skills in their activity, and earnestly learn alongside machines. However, the loop is one in which human workers are at a disadvantage as they experience systematic misrecognition of the value of their competencies and of their contributions to technology, the economy, and ultimately society. This situation hinders negotiations with companies, shifts power away from workers, and challenges the traditional balancing role of the salary institution.

Context Coronavirus disease 2019 (COVID-19) pandemic has caused increased interest in the application of telehealth to provide care without exposing patients and physicians to the risk of contagion. The urological literature on the topic is sparse. Objective To perform a systematic review of the literature and evaluate all the available studies on urological applications of telehealth. Evidence acquisition After registration on PROSPERO, we searched PubMed and Scopus databases to collect any kind of studies evaluating any telehealth interventions in any urological conditions. The National Toxicology Program/Office of Health Assessment and Translation Risk of Bias Rating Tool for Human and Animal Studies was used to estimate the risk of bias. A narrative synthesis was performed. Evidence synthesis We identified 45 studies (11 concerning prostate cancer [PCa], three hematuria management, six urinary stones, 14 urinary incontinence [UI], five urinary tract infections [UTIs], and six other conditions), including 12 randomized controlled trials. The available literature indicates that telemedicine has been implemented successfully in several common clinical scenarios, including the decision-making process following a diagnosis of nonmetastatic PCa, follow-up care of patients with localized PCa after curative treatments, initial diagnosis of hematuria, management diagnosis and follow-up care of uncomplicated urinary stones and uncomplicated UTIs, and initial evaluation, behavioral therapies, and pelvic floor muscle training in UI patients, as well as follow-up care after surgical treatments of stress urinary incontinence or pelvic organ prolapse. The methodological quality of most of the reports was good. Conclusions Telehealth has been implemented successfully in selected patients with PCa, UI, pelvic organ prolapse, uncomplicated urinary stones, and UTIs. Many urological conditions are suitable for telehealth, but more studies are needed on other highly prevalent urological malignant and benign conditions. Likely, the COVID-19 pandemic will give a significant boost to the use of telemedicine. More robust data on long-term efficacy, safety, and health economics are necessary. Patient summary The diffusion of coronavirus disease 2019 (COVID-19) infections has recently increased the interest in telehealth, which is the adoption of telecommunication to deliver any health care activity. The available literature indicates that telemedicine has been adopted successfully in selected patients with several common clinical urological conditions, including prostate cancer, uncomplicated urinary stones, uncomplicated urinary infections, urinary incontinence, or pelvic organ prolapse. Likely, the COVID-19 pandemic will give a significant boost to the use of telemedicine, but more robust data on long-term efficacy, safety, and costs are necessary., Take Home Message The available literature indicates that telemedicine has been adopted successfully in selected patients with several common clinical urological conditions, including prostate cancer, uncomplicated urinary stones, uncomplicated urinary infections, urinary incontinence, or pelvic organ prolapse. Likely, the coronavirus disease 2019 (COVID-19) pandemic will give a significant boost to the use of telemedicine, but more robust data on long-term efficacy, safety, and costs are necessary.

Context The coronavirus disease 2019 (COVID-19) pandemic raised concerns about the safety of laparoscopy due to the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diffusion in surgical smoke. Although no case of SARS-CoV-2 contagion related to surgical smoke has been reported, several international surgical societies recommended caution or even discouraged the use of a laparoscopic approach. Objective To evaluate the risk of virus spread due to surgical smoke during surgical procedures. Evidence acquisition We searched PubMed and Scopus for eligible studies, including clinical and preclinical studies assessing the presence of any virus in the surgical smoke from any surgical procedure or experimental model. Evidence synthesis We identified 24 studies. No study was found investigating SARS-CoV-2 or any other coronavirus. About other viruses, hepatitis B virus was identified in the surgical smoke collected during different laparoscopic surgeries (colorectal resections, gastrectomies, and hepatic wedge resections). Other clinical studies suggested a consistent risk of transmission for human papillomavirus (HPV) in the surgical treatments of HPV-related disease (mainly genital warts, laryngeal papillomas, or cutaneous lesions). Preclinical studies showed conflicting results, but HPV was shown to have a high risk of transmission. Conclusions Although all the available data come from different viruses, considering that the SARS-CoV-2 virus has been shown in blood and stools, the theoretical risk of virus diffusion through surgical smoke cannot be excluded. Specific clinical studies are needed to understand the effective presence of the virus in the surgical smoke of different surgical procedures and its concentration. Meanwhile, adoption of all the required protective strategies, including preoperative patient nasopharyngeal swab for COVID-19, seems mandatory. Patient summary In this systematic review, we looked at the risk of virus spread from surgical smoke exposure during surgery. Although no study was found investigating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or any other coronavirus, we found that the theoretical risk of virus diffusion through surgical smoke cannot be excluded.

The frequent occurrence of marine dinoflagellates producing palytoxin (PLTX) or okadaic acid (OA) raises concern for the possible co-presence of these toxins in seafood, leading to additive or synergistic adverse effects in consumers. Thus, the acute oral toxicity of PLTX and OA association was evaluated in mice: groups of eight female CD-1 mice were administered by gavage with combined doses of PLTX (30, 90 or 270 μg/kg) and OA (370 μg/kg), or with each individual toxin, recording signs up to 24 h (five mice) and 14 days (three mice). Lethal effects occurred only after PLTX (90 or 270 μg/kg) exposure, alone or combined with OA, also during the 14-day recovery. PLTX induced scratching, piloerection, abdominal swelling, muscle spasms, paralysis and dyspnea, which increased in frequency or duration when co-administered with OA. The latter induced only diarrhea. At 24 h, PLTX (90 or 270 μg/kg) and OA caused wall redness in the small intestine or pale fluid accumulation in its lumen, respectively. These effects co-occurred in mice co-exposed to PLTX (90 or 270 μg/kg) and OA, and were associated with slight ulcers and inflammation at forestomach. PLTX (270 μg/kg alone or 90 μg/kg associated with OA) also decreased the liver/body weight ratio, reducing hepatocyte glycogen (270 μg/kg, alone or combined with OA). No alterations were recorded in surviving mice after 14 days. Overall, the study suggests additive effects of PLTX and OA that should be considered for their risk assessment as seafood contaminants.

Background: Stent Encrustation is an uncommon event (13%) with a significant impact in patients' management. Aim of our study was to evaluate the available grading systems for encrusted stents. Methods: A retrospective analysis of encrusted stents was performed in four Italian centers between 2006 and 2020. Encrusted stents were classified according to four classifications: the Forgotten Encrusted Calcificated (FECal) score, the Kidney Ureter Bladder (KUB) score, the Visual Grading for Ureteral Encrusted Stent Classification and the Encrustation Burden Score (EBS). Classifications were evaluated to predict complex surgery defined as: long operative time (>60min); need of more than one surgery; need of a percutaneous approach. The scores were compared with Receiver Operating Characteristic (ROC) analysis as predictors of complex surgery. Results: 77 patients were evaluated with a median age of 62 years (65/70). Overall FECal score >2 was present in 45/77 (58%) patients, median KUB score was 9 (6/14) and severe EBS was found in 47/77 (63%) patients. Patients were managed with cystolithotripsy in 13/77 (17%), with ureteroscopy in 58/77 (75%) and with Percutaneous Nephrolithotomy (PCNL) in 6/77 (8%). Overall, 6/77 (8%) patients required a second intervention to remove the encrusted stent. All classifications predicted the need of complex surgery. On ROC analysis KUB score presented a better accuracy in predicting complex surgery compared to FECal, V-GUES and encrusted burden. Conclusions: KUB score, FECal score, V-GUES score and encrustation burden accurately predict the need of a complex surgery. KUB showed to be superior to other classifications according to our results.

We prove a new probabilistic formula for the gradient of the Dirichlet semigroup associated with a class of hypoelliptic operators in a bounded subset of $${\mathbb {R}}^d$$ R d .

The widespread use of deep learning techniques for creating realistic synthetic media, commonly known as deepfakes, poses a significant threat to individuals, organizations, and society. As the malicious use of these data could lead to unpleasant situations, it is becoming crucial to distinguish between authentic and fake media. Nonetheless, though deepfake generation systems can create convincing images and audio, they may struggle to maintain consistency across different data modalities, such as producing a realistic video sequence where both visual frames and speech are fake and consistent one with the other. Moreover, these systems may not accurately reproduce semantic and timely accurate aspects. All these elements can be exploited to perform a robust detection of fake content. In this paper, we propose a novel approach for detecting deepfake video sequences by leveraging data multimodality. Our method extracts audio-visual features from the input video over time and analyzes them using time-aware neural networks. We exploit both the video and audio modalities to leverage the inconsistencies between and within them, enhancing the final detection performance. The peculiarity of the proposed method is that we never train on multimodal deepfake data, but on disjoint monomodal datasets which contain visual-only or audio-only deepfakes. This frees us from leveraging multimodal datasets during training, which is desirable given their lack in the literature. Moreover, at test time, it allows to evaluate the robustness of our proposed detector on unseen multimodal deepfakes. We test different fusion techniques between data modalities and investigate which one leads to more robust predictions by the developed detectors. Our results indicate that a multimodal approach is more effective than a monomodal one, even if trained on disjoint monomodal datasets.

Biogenic Volatile Organic Compounds (BVOCs) emitted from the terrestrial ecosystem into the Earth's atmosphere are an important component of atmospheric chemistry. Due to the scarcity of measurement, a reliable enhancement of BVOCs emission maps can aid in providing denser data for atmospheric chemical, climate, and air quality models. In this work, we propose a strategy to super-resolve coarse BVOC emission maps by simultaneously exploiting the contributions of different compounds. To this purpose, we first accurately investigate the spatial inter-connections between several BVOC species. Then, we exploit the found similarities to build a Multi-Image Super-Resolution (MISR) system, in which a number of emission maps associated with diverse compounds are aggregated to boost Super-Resolution (SR) performance. We compare different configurations regarding the species and the number of joined BVOCs. Our experimental results show that incorporating BVOCs' relationship into the process can substantially improve the accuracy of the super-resolved maps. Interestingly, the best results are achieved when we aggregate the emission maps of strongly uncorrelated compounds. This peculiarity seems to confirm what was already guessed for other data-domains, i.e., joined uncorrelated information are more helpful than correlated ones to boost MISR performance. Nonetheless, the proposed work represents the first attempt in SR of BVOC emissions through the fusion of multiple different compounds., 5 pages, 4 figures, 1 table, accepted at EURASIP-EUSIPCO 2023

Purpose To investigate the effects of different antibiotic prophylaxis regimens in patients with diabetes mellitus (DM) candidates to trans-rectal ultrasound-guided prostate biopsy (TRUSPB). Methods 143 outpatients with DM who underwent TRUSPB during the period 2018–2020 were selected from a cohort of 1150 patients in 3 different institutions. Exclusion criteria were allergies, concomitant anti-platelet therapies and uncontrolled DM. Different antibiotic prophylaxis regimens were adopted. Bacterial resistance levels to fluoroquinolones into the different communities were also collected. Univariable and multivariable binomial logistic regression analyses were used to assess the odds ratio (OR) with 95% confidence intervals (CIs) testing the risk of infective complications' occurrence after adjusting for clinical covariates. Results Overall, DM patients were significantly associated with infective complications' occurrence (p 37 °C were found in 9.1% and 1.5% (p Conclusion Fluoroquinolones were active in antibiotic prophylaxis of diabetic patients who had undergone to TRUSPB independently from the level of bacterial resistance found in the community. These results conflict with the recent European warning and support the Japanese and American guidelines on the topic.

The widespread diffusion of synthetically generated content is a serious threat that needs urgent countermeasures. As a matter of fact, the generation of synthetic content is not restricted to multimedia data like videos, photographs or audio sequences, but covers a significantly vast area that can include biological images as well, such as western blot and microscopic images. In this paper, we focus on the detection of synthetically generated western blot images. These images are largely explored in the biomedical literature and it has been already shown they can be easily counterfeited with few hopes to spot manipulations by visual inspection or by using standard forensics detectors. To overcome the absence of publicly available data for this task, we create a new dataset comprising more than 14K original western blot images and 24K synthetic western blot images, generated using four different state-of-the-art generation methods. We investigate different strategies to detect synthetic western blots, exploring binary classification methods as well as one-class detectors. In both scenarios, we never exploit synthetic western blot images at training stage. The achieved results show that synthetically generated western blot images can be spot with good accuracy, even though the exploited detectors are not optimized over synthetic versions of these scientific images. We also test the robustness of the developed detectors against post-processing operations commonly performed on scientific images, showing that we can be robust to JPEG compression and that some generative models are easily recognizable, despite the application of editing might alter the artifacts they leave.

Background: The indication for extended pelvic lymph node dissection (ePLND) at the time of radical prostatectomy (RP) is based on nomograms predicting the risk of lymph node invasion (LNI). However, limited data are available on the comparison of these predictive models in high-risk prostate cancer (PC) patients. Therefore, we compared the accuracy of the most used nomograms (MSKCC, Briganti 2012, 2017, and 2019) in the setting of high-risk PC patients submitted to ePLND. Methods: 150 patients with high-risk PC disease treated from 2019 to 2022 were included. Before RP + ePLND, we assessed the MSKCC, Briganti 2012, 2017, and 2019 nomograms for each patient, and we compared the prediction of LNI with the final histopathological analysis of the ePLND using pathologic results as a reference. Results: LNI was found in 39 patients (26%), and 71.3% were cT2. The percentage of patients with estimated LNI risk above the cut-off was significantly higher in pN+ cases than in pN0 for all Briganti nomograms. The percentage of patients at risk of LNI, according to Briganti Nomogram (2012, 2017, and 2019), was significantly higher in pN+ cases than in pN0 (p < 0.04), while MSKCC prediction didn’t vary significantly between pN0 and pN+ groups (p = 0.2). All nomograms showed high sensitivity (Se > 0.90), low specificity (Sp < 0.20), and similar AUC (range: 0.526–0.573) in predicting pN+. Particularly, 74% of cases patients with MSKCC estimated risk > 7% showed pN0 compared to 71% with Briganti 2012 > 5%, 69% with Briganti 2017 > 7%, and 70% with Briganti 2019 > 7%. Conclusions: Despite the high-risk disease, in our patients treated with ePLND emerges a still high number of pN0 cases and a similar low specificity of nomograms in predicting LNI.

Background: Extensive research effort has been devoted to investigating the link between inflammation and PCa. However, this relationship remains unclear and controversial. The aim of our multi-center study was to investigate this association by histologically evaluating the distribution of PI and PCA in prostate biopsy cores from patients of eight referral centers in Italy. Results: We evaluated 2220 cores from 197 patients; all the frustules were re-evaluated by dedicated pathologists retrospectively. Pathologists assigned IRANI scores and determined the positions of PIs; pathologists also re-evaluated the presence of PCa and relative ISUP grade. PCa was recorded in 749/2220 (33.7%). We divided this sample into a PCa PI group (634/749 cores [84.7%]) and a non-PCa + PI group (1157/1471 cores [78.7%]). We observed a statistically significant difference in the presence of inflammation among cores with cancer (p < 0.01). Moreover, periglandular inflammation was higher in the cores with neoplasia, while stromal inflammation was higher in cores without neoplasia (38.5% vs. 31.1% and 55.4% vs. 63.5% p < 0.01). Conclusions: In our experience, there is evidence of an association between PI and PCa at a tissue level. Further studies are needed to confirm our findings and to identify patients who might benefit from target therapies to prevent PCa occurrence and/or progression.

Insufficient physical activity (PA) may be a shared risk factor for the development of both metabolic syndrome (MetS) and prostate cancer (PCa). To investigate this correlation and to develop a nomogram able to predict tumor diagnosis. Between 2016 and 2018, a consecutive series of men who underwent prostate biopsy at three institutions were prospectively enrolled. PA was self-assessed by patients through the Physical Activity Scale for the Elderly (PASE) questionnaire; MetS was assessed according to Adult Treatment Panel III criteria. A logistic regression analyses was used to identify predictors of PCa diagnosis and high-grade disease (defined as International Society of Uro-Pathology grade >2 tumors). A nomogram was then computed to estimate the risk of tumor diagnosis. A total of 291 patients were enrolled; 17.5% of them (n = 51) presented with MetS. PCa was diagnosed in 110 (38%) patients overall while 51 presented high-grade disease. At multivariable analysis, age (OR 1.04; 95%CI: 1.00–1.08; p = 0.048), prostate volume (PV) (OR 0.98; 95%CI: 0.79–0.99; p = 0.004), suspicious digital rectal examination (OR 2.35; 95%CI: 1.11–4.98; p = 0.02), total PSA value (OR 1.12; 95%CI: 1.05–1.2; p < 0.001), and PASE score (OR 0.99; 95%CI: 0.98–0.99; p = 0.01) were independent predictors of tumor diagnosis. The latter two also predicted high-grade PCa. MetS was not associated with PCa diagnosis and aggressiveness. The novel nomogram displayed fair discrimination for PCa diagnosis (AUC = 0.76), adequate calibration (p > 0.05) and provided a net benefit in the range of probabilities between 20% and 90%. reduced PA was associated with an increased risk of PCa diagnosis and high-grade disease. Our nomogram could improve the selection of patients scheduled for prostate biopsy at increased risk of PCa.

Biogenic Volatile Organic Compounds (BVOCs) play a critical role in biosphere-atmosphere interactions, being a key factor in the physical and chemical properties of the atmosphere and climate. Acquiring large and fine-grained BVOC emission maps is expensive and time-consuming, so most available BVOC data are obtained on a loose and sparse sampling grid or on small regions. However, high-resolution BVOC data are desirable in many applications, such as air quality, atmospheric chemistry, and climate monitoring. In this work, we investigate the possibility of enhancing BVOC acquisitions, further explaining the relationships between the environment and these compounds. We do so by comparing the performances of several state-of-the-art neural networks proposed for image Super-Resolution (SR), adapting them to overcome the challenges posed by the large dynamic range of the emission and reduce the impact of outliers in the prediction. Moreover, we also consider realistic scenarios, considering both temporal and geographical constraints. Finally, we present possible future developments regarding SR generalization, considering the scale-invariance property and super-resolving emissions from unseen compounds., Comment: 5 pages, 4 figures, 3 tables, accepted at IEEE-ICIP 2023

Scientific research is growingly increasingly reliant on "microwork" or "crowdsourcing" provided by digital platforms to collect new data. Digital platforms connect clients and workers, charging a fee for an algorithmically managed workflow based on Terms of Service agreements. Although these platforms offer a way to make a living or complement other sources of income, microworkers lack fundamental labor rights and basic safe working conditions, especially in the Global South. We ask how researchers and research institutions address the ethical issues involved in considering microworkers as "human participants." We argue that current scientific research fails to treat microworkers in the same way as in-person human participants, producing de facto a double morality: one applied to people with rights acknowledged by states and international bodies (e.g., the Helsinki Declaration), the other to guest workers of digital autocracies who have almost no rights at all. We illustrate our argument by drawing on 57 interviews conducted with microworkers in Spanish-speaking countries.

Tools to generate high quality synthetic speech signal that is perceptually indistinguishable from speech recorded from human speakers are easily available. Several approaches have been proposed for detecting synthetic speech. Many of these approaches use deep learning methods as a black box without providing reasoning for the decisions they make. This limits the interpretability of these approaches. In this paper, we propose Disentangled Spectrogram Variational Auto Encoder (DSVAE) which is a two staged trained variational autoencoder that processes spectrograms of speech using disentangled representation learning to generate interpretable representations of a speech signal for detecting synthetic speech. DSVAE also creates an activation map to highlight the spectrogram regions that discriminate synthetic and bona fide human speech signals. We evaluated the representations obtained from DSVAE using the ASVspoof2019 dataset. Our experimental results show high accuracy (>98%) on detecting synthetic speech from 6 known and 10 out of 11 unknown speech synthesizers. We also visualize the representation obtained from DSVAE for 17 different speech synthesizers and verify that they are indeed interpretable and discriminate bona fide and synthetic speech from each of the synthesizers.

Enhancing the resolution of Biogenic Volatile Organic Compound (BVOC) emission maps is a critical task in remote sensing. Recently, some Super-Resolution (SR) methods based on Deep Learning (DL) have been proposed, leveraging data from numerical simulations for their training process. However, when dealing with data derived from satellite observations, the reconstruction is particularly challenging due to the scarcity of measurements to train SR algorithms with. In our work, we aim at super-resolving low resolution emission maps derived from satellite observations by leveraging the information of emission maps obtained through numerical simulations. To do this, we combine a SR method based on DL with Domain Adaptation (DA) techniques, harmonizing the different aggregation strategies and spatial information used in simulated and observed domains to ensure compatibility. We investigate the effectiveness of DA strategies at different stages by systematically varying the number of simulated and observed emissions used, exploring the implications of data scarcity on the adaptation strategies. To the best of our knowledge, there are no prior investigations of DA in satellite-derived BVOC maps enhancement. Our work represents a first step toward the development of robust strategies for the reconstruction of observed BVOC emissions., Comment: 4 pages, 4 figures, 1 table, accepted at IEEE-IGARSS 2023