Extensive Monitoring Research Articles

Occurrence of Goniozus legneri (Hymenoptera: Bethylidae) and its association to lepidopteran pests in Northern cultivated oasis of Mendoza province, Argentina

Goniozus legneri Gordh (Hymenoptera: Bethylidae) is a larval ectoparasitoid of lepidopterans, with a worldwide history as a biocontrol agent of various agricultural pests. By means of extensive monitoring, this wasp was found in four distant districts of Mendoza province parasitizing three lepidopteran pests: Lobesia botrana (Den. et Shiff.) in grapevine, Ectomyelois ceratoniae (Zeller) in walnut and “espinillo” (Vachellia caven (Molina) Seigler et Ebinger) and Cydia pomonella (L.) in walnut. To corroborate the parasitoid species identification and to analyze its population viability in this region, studies of male genitalia and sexual crossings between wild and laboratory-reared wasps were conducted. Further, we report for the first time the natural host-parasitoid interaction of L. botrana with this parasitoid in vineyards from Argentina.

A time series based machine learning strategy for wastewater-based forecasting and nowcasting of COVID-19 dynamics

Monitoring COVID-19 infection cases has been a singular focus of many policy makers and communities. However, direct monitoring through testing has become more onerous for a number of reasons, such as costs, delays, and personal choices. Wastewater-based epidemiology (WBE) has emerged as a viable tool for monitoring disease prevalence and dynamics to supplement direct monitoring. The objective of this study is to intelligently incorporate WBE information to nowcast and forecast new weekly COVID-19 cases and to assess the efficacy of such WBE information for these tasks in an interpretable manner. The methodology consists of a time-series based machine learning (TSML) strategy that can extract deeper knowledge and insights from temporal structured WBE data in the presence of other relevant temporal variables, such as minimum ambient temperature and water temperature, to boost the capability for predicting new weekly COVID-19 case numbers. The results confirm that feature engineering and machine learning can be utilized to enhance the performance and interpretability of WBE for COVID-19 monitoring, along with identifying the different recommended features to be applied for short-term and long-term nowcasting and short-term and long-term forecasting. The conclusion of this research is that the proposed time-series ML methodology performs as well, and sometimes better, than simple predictions that assume available and accurate COVID-19 case numbers from extensive monitoring and testing. Overall, this paper provides an insight into the prospects of machine learning based WBE to the researchers and decision-makers as well as public health practitioners for predicting and preparing the next wave of COVID-19 or the next pandemic.

Graft dysfunction in compassionate use of genetically engineered pig-to-human cardiac xenotransplantation: a case report

A genetically engineered pig cardiac xenotransplantation was done on Jan 7, 2022, in a non-ambulatory male patient, aged 57 years, with end-stage heart failure, and on veno-arterial extracorporeal membrane oxygenation support, who was ineligible for an allograft. This report details our current understanding of factors important to the xenotransplantation outcome. Physiological and biochemical parameters critical for the care of all heart transplant recipients were collected in extensive clinical monitoring in an intensive care unit. To ascertain the cause of xenograft dysfunction, we did extensive immunological and histopathological studies, including electron microscopy and quantification of porcine cytomegalovirus or porcine roseolovirus (PCMV/PRV) in the xenograft, recipient cells, and tissue by DNA PCR and RNA transcription. We performed intravenous immunoglobulin (IVIG) binding to donor cells and single-cell RNA sequencing of peripheral blood mononuclear cells. After successful xenotransplantation, the graft functioned well on echocardiography and sustained cardiovascular and other organ systems functions until postoperative day 47 when diastolic heart failure occurred. At postoperative day 50, the endomyocardial biopsy revealed damaged capillaries with interstitial oedema, red cell extravasation, rare thrombotic microangiopathy, and complement deposition. Increased anti-pig xenoantibodies, mainly IgG, were detected after IVIG administration for hypogammaglobulinaemia and during the first plasma exchange. Endomyocardial biopsy on postoperative day 56 showed fibrotic changes consistent with progressive myocardial stiffness. Microbial cell-free DNA testing indicated increasing titres of PCMV/PRV cell-free DNA. Post-mortem single-cell RNA sequencing showed overlapping causes. Hyperacute rejection was avoided. We identified potential mediators of the observed endothelial injury. First, widespread endothelial injury indicates antibody-mediated rejection. Second, IVIG bound strongly to donor endothelium, possibly causing immune activation. Finally, reactivation and replication of latent PCMV/PRV in the xenograft possibly initiated a damaging inflammatory response. The findings point to specific measures to improve xenotransplant outcomes in the future. The University of Maryland School of Medicine, and the University of Maryland Medical Center.

Long-term static and dynamic monitoring to failure scenarios assessment in steel truss railway bridges: A case study

The latest studies on failures in steel truss-type bridges found that they are highly vulnerable to damage and thus prone to potential local or total collapse. Many authors recommend monitoring the critical elements in the existing steel truss-type bridges in real time to anticipate any failures in local members. Although mechanical strain is the most frequently used variable for this purpose, this method also happens to be the most expensive monitoring strategy. This paper describes a case study of failure scenarios assessment in a steel truss-type railway bridge after extensive long-term monitoring conducted by the authors, based on measuring vertical deflections and modal frequencies. The structure has both an isostatic and a hyperstatic configuration, and was assessed by means of a combination of: (i) long-term monitoring results, and (ii) a finite element analysis to simulate several failure scenarios. A sensitivity study of the different failure scenarios has been carried out, identifying those that can be detected. The results are used to define practical recommendations for failure detection by measuring vertical deflections and modal frequencies.

Deucravacitinib: The First FDA-Approved Oral TYK2 Inhibitor for Moderate to Severe Plaque Psoriasis.

The objective of this study was to review the safety and efficacy of deucravacitinib, a tyrosine kinase 2 (TYK2) inhibitor for moderate to severe plaque psoriasis. Literature was reviewed from MEDLINE and Clinicaltrials.gov up to December 2022 using the terms "deucravacitinib" and "BMS-986165." Relevant articles in English relating to the pharmacodynamics, pharmacokinetics, efficacy, and safety of deucravacitinib were included. A total of 6 trial results were included. Deucravacitinib showed clinical efficacy across all the phase II and III clinical trials. Excluding the long-term extension study, there were 2248 subjects across all studies, with 63.2% of patients receiving deucravacitinib 6 mg daily. Of these subjects, the average proportion achieving a PASI 75 (a reduction of greater than 75% in the Psoriasis Area and Severity Index) at week 16 was 65.1%. Patients receiving deucravacitinib 6 mg once daily had a higher rate of achieving both PASI 75 response and a Static Physician's Global Assessment (sPGA) score of 0 or 1, compared with oral apremilast 30 mg twice daily. The safety profile of deucravacitinib includes mild adverse events (AEs), most commonly nasopharyngitis, with serious AEs reported ranging from 1.35% to 9.5%. While many available therapies for moderate to severe plaque psoriasis rely on an injectable dosage form or extensive monitoring, deucravacitinib can potentially reduce patient medication-related burden. This review summarizes the efficacy and safety of oral deucravacitinib for the treatment of severe plaque psoriasis. Deucravacitinib shows a consistent efficacy and safety profile as the first oral TYK2 inhibitor approved for adult patients with moderate to severe plaque psoriasis who are eligible for systemic therapy or phototherapy treatment.

A Rapid and Easy Way for National Forest Heights Retrieval in China Using ICESat-2/ATL08 in 2019

Continuous and extensive monitoring of forest height is essential for estimating forest above-ground biomass and predicting the ability of forests to absorb CO2. In particular, forest height at the national scale is an important indicator reflecting the national forestry economic construction, environmental governance, and ecological balance. However, the lack of inventory data restricts large-scale monitoring of forest height to some extent. Conducting manual surveys of forest height for large-scale areas would be labor-intensive and time-consuming. The successful launch of the new generation of spaceborne light detection and ranging (LiDAR) (The Ice, Cloud, and Land Elevation Satellite-2/the Advanced Topographic Laser Altimeter System, ICESat-2/ATLAS) has brought new opportunities for national-scale forestry resource surveys. This paper explores a method to survey national forest canopy height from the new generation of ICESat-2/ATLAS data. In view of the sparse sampling and little overlap between repeated spaceborne LiDAR data, a strategy for assessing the overall change of canopy height for large scales is provided. Some spatially continuous ancillary data were used to assist ICESat-2/ATLAS data to generate a wall-to-wall (spatially continuous) forest canopy height map in China by using the machine learning approach and then quantifying the analysis of forest canopy height in various provinces. The results show that there is a good correlation between the model forest height and the verification data, with a root mean squared error (RMSE) of 3.30 m and a coefficient of determination (R2) of 0.87. This indicates that the method for retrieving national forest canopy height is reliable. There are some limitations in areas with lower vegetation coverage or complex topography which need additional filtering or terrain correction to achieve higher accuracy in measuring forest canopy height. Our analysis suggests that ICESat-2/ATLAS data can achieve the retrieval of national forest height at an overall level, and it would be feasible to use ICESAT-2/ATLAS products to estimate forest canopy height change for large-scale areas.

Industrial and Environmental Disaster Risk Assessment for Hazardous Materials in Balikpapan City, East Kalimantan, Indonesia

Industrial disasters may cause massive public health problems, as they create large environmental damage and major loss of life. Balikpapan City has experienced a large oil spill which caused an industrial and environmental disaster: five fishermen died, various public health problems arose, and damage to environmental wildlife and ecosystems occurred. The objective of this study was to evaluate the industrial and environmental disaster risk related to hazardous material (hazmat) in Balikpapan. The research method involved the use of a semi-quantitative risk analysis with an originally organized checklist, a risk matrix, and a Geographic Information System (GIS) analysis. The results suggested that the risk score in Balikpapan’s City is 32 (MEDIUM; the dominant types of hazmat were flammables and corrosives). The major sectors contributing to the risk appeared to be the mining, energy, and oil and gas industries, with a medium risk (average risk score 33), while one clean water industry showed a low risk (risk score 24) using the checklist and risk matrix. According to the results from the GIS mapping, the areas t the highest risks appeared to be located within Balikpapan City coastal regions. The industries and the government of Balikpapan must be prepared for industrial and environmental disasters by educating competent major hazmat responders and ensuring a large spills response equipment, extensive environmental monitoring and measurement, procedures to deal with major fire and explosions and adequate disaster communication and coordination.

Intelligent dual-drive DNA nanosensor for ultrasensitive detection of prostate cancer-related circulating microRNA-200c

Rapid and accurate detection of the dynamic changes of prostate cancer-related miRNAs in peripheral blood is of great significance for prostate monitoring. Herein, we constructed an intelligent dual-drive DNA nanosensor (DD-DNS) for molecularly determination of microRNA-200c (miR-200c), a potential monitoring marker for diagnosis and treatment of prostate cancer. Unlike common detection technologies, the most distinctive feature of DD-DNS is the ingenious combination of enzyme-catalyzed chain amplification reaction and non-enzyme-catalyzed chain replacement reaction to realize the complementation of performance and improvement of detection capability. This improvement can significantly improve the detection sensitivity and environmental adaptability, which is more conducive to the detection of actual samples. In the presence of miR-200c, miR-200c activates the polymerase/nickase cycle reaction, resulting in exponential levels of cycle primers being produced. As a programmed process, cyclic primers catalyze the hairpin assembly reaction to achieve a surge in fluorescence signals. As a novel amplification strategy, the detection limit of this method can reach 5.5 fM, which fully meets the requirements of clinical quantitative analysis. Thus, miRNA detection technology based on DD-DNS shows superior detection performance and stability, which is conducive to carrying out extensive disease screening and treatment monitoring in a variety of complex situations.

Prioritization of micropollutants based on removal effort in drinking water purification treatment

Abstract A main focus of water managers with regard to micropollutants is the protection of aquatic ecology. However, micropollutants also have the potential to affect the production of clean drinking water. In this paper, we propose to consider the removal effort when assessing micropollutants with an ‘Effort Index’ (EI). Assessments using the EI show which micropollutants need more extensive monitoring or abatement because of their difficulty to be removed using low-effort water purification treatment techniques. For water containing mixtures of micropollutants, the averaged EI values can indicate overall water quality. Data on the removal by different purification treatment techniques are not necessarily available for all micropollutants. Therefore, a set of data-driven indicative removal rules is derived to quantify the relation between micropollutant properties and different drinking water treatment techniques. The indicative removal rules provide a rough indication of removability. As an illustration, the water quality of the river Rhine is evaluated between 2000 and 2018. The EI value shows that the Rhine contains increasingly more difficult-to-remove micropollutants. In total, 18 of those are labeled as particularly difficult-to-remove chemicals. These micropollutants are suggested as candidates for abatement to lower the required effort in drinking water production.

Machine learning-based soft-sensor development for road quality classification

Vibrations in road vehicles cause several harmful effects, health problems can occur for the passengers, and mechanical damage can occur to the vehicle components. Given the health, safety, and financial issues that arise, keeping the road network in good condition and detecting road defects as early as possible requires an extensive monitoring system. Related to this, our study presents the development of hardware and software for a low-cost, multi-sensor road quality monitoring system for passenger vehicles. The developed monitoring system can classify road sections according to their quality parameters into four classes. In order to detect vibrations in the vehicle, accelerometers and gyroscope sensors are installed at several points. Then, a machine learning-based soft-sensor development is introduced. Besides noise filtering, each data point is resampled by spatial frequency to reduce the velocity dependence. Subsequently, a decision tree-based classification model is trained using features from the power spectrum and principal component analysis. The classification algorithm is validated and tested with measurement data in a real-world environment. In addition to reviewing the accuracy of the model, we examine the correlation of the data measured in the cabin and on the suspension to see how much additional information is provided by the sensor on the axle.

Optical assessment of the spatial variation in total soil carbon using laser-induced breakdown spectroscopy

Soil carbon storage is a substantial factor in the global carbon cycle. Carbon sequestration in agricultural soils, and the assessment and validation of soil carbon storage, are crucial for the mitigation of agricultural greenhouse gas emissions and for steering towards sustainable farming practices. Enforcement and verification of carbon sequestration policies, methods, and models require extensive soil carbon monitoring capability. However, current conventional laboratory-based methods for soil carbon estimation are laborious, expensive, and time-consuming. In this work, we have developed a compact, robust, and field-capable experimental device based on laser-induced breakdown spectroscopy (LIBS) for the rapid assessment of total soil carbon content and its spatial distribution in mineral soils. The carbon content quantification was performed using a spectral line of carbon at a wavelength of 193.1 nm emitted from the laser-induced plasma plume. The LIBS measurements were performed on soil samples collected from 28 different locations and various depths (up to 1 m) of a test field cultivated with a forage legume (red clover - Trifolium pratense, L.) and grass (Timothy - Phleum pratense, L.) mixture in eastern Finland. A calibration model was established based on a limited and randomly chosen sample set and validated by comparing soil carbon estimates obtained from various locations in the test field using the dry combustion (LECO) method. Further, we demonstrate here the usefulness of LIBS methodology for mapping three-dimensional carbon distribution at the test field. We emphasize here that the calibration model can be generalized to other sample areas under similar soil type with a relative error of less than 10 % and possesses potential for fast on-site determination of spatial variation in total soil carbon, reducing substantially the need of time-consuming sample processing in laboratory. Therefore, LIBS enables frequent and extensive spatial and temporal soil carbon mapping and has the potential to become part of the future carbon monitoring network.

The role of MIBG scan in the diagnosis of pheochromocytoma.

e15064 Background: Pheochromocytoma is an uncommon adrenal medulla tumor. Metaiodobenzylguanidine (MIBG) scintigraphy is the current gold standard functional imaging method for evaluating pheochromocytoma, due to its excellent 100% specificity, 80% sensitivity, and general availability. In addition to establishing an extension evaluation and monitoring medication efficacy, MIBG scintigraphy is essential to confirm the diagnosis of suspected pheochromocytoma, especially when there is a tumor-like adrenal mass whose etiology is to be determined and biopsy is contraindicated given the risk of catecholamine discharge with hypertensive flare and the risk of bleeding. Our aims are to determine the efficacy of scintigraphy in the diagnosis of pheochromocytoma by examining the epidemiological characteristic and uptake patterns of the disease. Methods: In a retrospective analysis from January 2010 to December 2020, we examined pheochromocytoma patients medical records who had been referred for MIBG scintigraphy to the regional western Algerian Nuclear Medicine department at the University Hospital Center of Tlemcen. Prior to a progressive intravenous injection of 40–80 MBq of l-MIBG, patients underwent preparation (discontinuation of interfering drugs with I-MIBG especially antihypertensive treatment, thyroid blocking, and hydration). Imaging acquisition was carried out 48 and 72 hours later. Results: Fifty patients with probable pheochromocytoma (sex ratio = 0,78; mean age = 43 [17-74] years) completed I-MIBG scintigraphy prior to adrenalectomy. The MIBG scan has a high specificity and positive predictive value (100%). It confirms the presence of pheochromocytoma in 21 cases (42%), even if the metanephrine is normal in a patient with a non-secreting pheochromocytoma. In 18 cases, the main pattern is a single, homogenous, and intense intra-abdominal uptake. For the three remaining patients, a voluminous and heterogeneous uptake with a photopenic center that was associated to a necrotic adrenal mass larger than 10 cm in size, seen on abdominal Computerized Tomography (CT). In this retrospective analysis, no cases of metastatic or multiple diseases were documented. The sensitivity and negative predictive value are 84% and 86%, respectively. In 29 patients (58%), the scan reveals no abnormalities in uptake. This is attributed, in part, to 30% false positive biology (sampling conditions of urinary and/or plasmatic metanephrines and/or normetanephrines), 20% false positive CT imaging (differential diagnosis of adrenal mass: benign or malignant adrenal nodule), and 8% false negative MIBG scintigraphy (subcentimetric, cystic and necrotic lesion). Conclusions: Due to its exceptional specificity, robust sensitivity, and whole-body staging, MIBG scintigraphy—along with biology and morphology imaging—is a crucial noninvasive diagnostic method for the management of pheochromocytoma prior to adrenalectomy.

Account aggregator ecosystem: A step towards revolutionising digital lending in India

An essential contributor to a nation’s economic success is providing individuals with access to established financial systems. India, through innovative use of digital finance infrastructure, aka India Stack, provided as a public good, removes obstacles in offering financial products to the unbanked and underbanked. The three pillars of the India Stack are: the identity rail (Aadhaar), the payment rail (universal payment interface) and the data-sharing rail of account aggregators (AAs). The next phase in the India Stack is the Open Credit Enablement Network (OCEN), which promises to transform the digital lending industry by shifting the business model from asset-based to cash-flow-based lending. OCEN is a standard set of application programming interfaces (APIs) that pull data based on customer consent from financial information providers and offers it to financial information users to decide on credit requests. AA manages consent on behalf of the customer using data empowerment and protection architecture (DEPA). The rest of the paper explains the interoperability and portability features of the AA ecosystem, the pricing model that the AA can adopt for a sustainable business model, describes the current state of the AA ecosystem in terms of consents provided and fulfilled and concludes with the use cases of OCEN in credit extension and continuous loan monitoring.

Adoption and feeding of fieldfare nestlings and fledglings by European blackbird.

Interspecific adoption is an intriguing topic in behavioral and evolutionary ecology. As it is a rare phenomenon, seldom documented in the literature, reports of interspecific adoption based on solid data are particularly valuable. A long-term and extensive monitoring programme involving a local population of European blackbirds (Turdus merula, hereafter blackbird) has yielded, among other things, observations of alloparental behavior exhibited by blackbirds toward fieldfare (Turdus pilaris) nestlings (a single nest, the first-ever record) and fledglings (12 cases in all). We discuss the observations in the context of the available literature.

Adaptive evolution to the natural and anthropogenic environment in a global invasive crop pest, the cotton bollworm

The cotton bollworm, Helicoverpa armigera, is set to become the most economically devastating crop pest in the world, threatening food security and biosafety as its range expands across the globe. Key to understanding the eco-evolutionary dynamics of H.armigera, and thus its management, is an understanding of population connectivity and the adaptations that allow the pest to establish in unique environments. We assembled a chromosome-scale reference genome and re-sequenced 503 individuals spanning the species range to delineate global patterns of connectivity, uncovering a previously cryptic population structure. Using a genome-wide association study (GWAS) and cell line expression of major effect loci, we show that adaptive changes in a temperature- and light-sensitive developmental pathway enable facultative diapause and that adaptation of trehalose synthesis and transport underlies cold tolerance in extreme environments. Incorporating extensive pesticide resistance monitoring, we also characterize a suite of novel pesticide and Bt resistance alleles under selection in East China. These findings offer avenues for more effective management strategies and provide insight into how insects adapt to variable climatic conditions and newly colonized environments.

High Spatiotemporal Model-Based Tracking and Environmental Risk-Exposure of Wastewater-Derived Pharmaceuticals across River Networks in Saxony, Germany

Wastewater treatment plants represent relevant point sources of environmental-adverse pharmaceuticals in river systems. Extensive monitoring and substance-routing models are crucial for environmental risk assessment and river planning. However, most current models assume long-term and large spatial averaged values of pharmaceutical consumption and river discharge flows. This study describes a detailed tracking of pharmaceutical occurrence across river networks with high spatiotemporal resolution to assist better environmental risk assessments. Using high spatiotemporal prescription data of four (pseudo-) persistent pharmaceuticals and river discharge characterization, an adjusted graph-theory-based model was implemented to efficiently evaluate the impact of the effluents of 626 wastewater treatment plants across nine river networks located in Saxony, Germany. Multisite calibration results demonstrated the model capability to satisfactorily predict daily pharmaceutical loads and concentrations with high spatial discretization. Based on minimal river dilution and mean predicted concentrations, the risk exposure revealed carbamazepine and ciprofloxacin as the most critical pharmaceuticals and Vereinigte Mulde as the most risk-exposed river network with up to 34.0% and 23.7% of its river length exceeding half and the total of ecotoxicological criteria, respectively. In comparison, other river networks showed less than 23.5% and 15.0% of their river lengths exceeding half and the total of ecotoxicological criteria of all four selected pharmaceuticals, respectively.

‘A factory of therapy’: accountability and the monitoring of psychological therapy in IAPT

Since the introduction of the Improving Access to Psychological Therapies (IAPT) programme in NHS England, psychological therapy has gained traction as ‘evidence-based’ and ‘effective’ in both clinical and economic terms. In the process, psychotherapeutic care has been reconstituted as highly manualised, standardised, and quantifiable. Drawing on anthropological fieldwork with mental health practitioners, this paper examines some common tensions that practitioners experience in their daily work where psychotherapy is sought within the framework of evidence-based medicine (EBM). For therapists working within IAPT, extensive monitoring and practices of accountability have come to undermine psychotherapeutic efforts to care for patients as ‘people’. As a result, many practitioners now feel that they are working in a ‘factory of therapy’ whereby psychological treatment is recast in the service of outcome measures, and by which critique of the IAPT service, as well as caring relations within it, have been precluded.

P371 CONFOUNDING CARDIAC MARKERS IN A CASE OF COVID–19 MYOCARDITIS

Abstract Background–Aim A man of 81 years, with previous coronary artery disease, unrecognized myocardial infarction, carrier of implanted pacemaker, presented to the cardiology department for a scheduled hospitalization to treat shortness of breath and symptoms of heart failure. There was no chest pain, ECG poorly assessable for pacemaker–induced rhythm, cardiac troponin I of 35,879 ng/L (cut–off 20). Suspecting an acute coronary syndrome (ACS), the patient undergoes immediate coronary angiography that does not showed any change compared to a previous examination. Meanwhile SARS–CoV–2 research in nasopharyngeal swab by RT–PCR was positive and after a few hours fever appears. Methods The authors discussed the case and extensive monitoring of cardiac markers and intensive evaluation of clinical parameters were activated. Troponin I HS, CK–MB, Myoglobin (Beckman Coulter DxI), CK, AST, LDH are determined by routine methods (Beckman Coulter AU700), Troponin T (cTnT–hs Roche Diagnostics) on (Roche Cobas 8000). Results All markers (except Troponin T) had the typical pattern of an ACS, in accordance with their characteristic half–life of an acute insult with development of a peak and subsequent decrease in a few days. The peaks recorded were cTnI 35,789 ng/L, CK–MB 72.6 ug/L, CK 800 U/L, AST 1,51U/L, Myoglobin 244 ng/ml, LDH 600 U/L, all at time 0. Troponin T was moderately increased at presentation (3700 ng/L, cut–off 10) followed by a peak of 3,872 after 2 hours stabilizing around 2,800 ng/L for the next days and decreasing after day 7. The final diagnosis was acute COVID–19–related myocarditis. Conclusions It has been described that the presentation of a SARS–CoV–2 infection can sometimes simulate a condition of ACS when there is an inflammatory involvement of the heart. In this case all the clinical data pointed towards an ischemic pathology which, however, was excluded in diagnostic imaging. A conclusive assessment with cardiac MRI was not possible due to the presence of the pacemaker, so the diagnosis was made as probable. Among the different markers, Troponin I was found to express a more intense signal and an earlier positive evolution than that of Troponin T. Our report highlights the different evolution of cardiac troponins in this disease.

Parameter identification and range restriction through sensitivity analysis for a high-temperature heat injection test

In order to compensate for the variable mismatch between heat demand and heat production from renewable sources or waste heat, high-temperature aquifer thermal energy storage (HT-ATES) is a promising option. A reliable prediction of the energetic performance as well as thermal and hydraulic impacts of a HT-ATES requires a suitable model parameterization regarding the subsurface properties. In order to identify the subsurface parameters on which investigation efforts should be focused, we carried out an extensive sensitivity analysis of the thermal and hydraulic parameters for a high-temperature heat injection test (HIT) using numerical modeling of the governing coupled thermo-hydraulic processes. The heat injection test was carried out in a quaternary shallow aquifer using injection temperatures of about 75 °C over 5 days, accompanied by an extensive temperature monitoring. The sensitivity analysis is conducted for parameter ranges based on literature values, based on site investigation at the HIT site and based on a model calibrated to the measured temperature distribution following the heat injection. Comparing the parameter ranges thus obtained in this three-step approach allows to identify those parameters, for which model prediction uncertainty decreased most, which are also the parameters, that strongly affect the thermal behavior. The highest sensitivity is found for vertical and horizontal hydraulic conductivity as well as for groundwater flow velocity, indicating that investigation efforts for HT-ATES projects should focus on these parameters. Heat capacity and thermal conductivity have a smaller impact on the temperature distribution. Our work thus yields a consistent approach to identifying the parameters which can be best restricted by field investigations and subsequent model calibration. Focusing on these during field investigations thus enable improved model predictions of both HT-ATES operation and induced impacts.

Confessions of a baboon watcher: from inside to outside the paradigm

In this “tale” I summarize the major landmarks of my 50-year career watching wild olive baboons (Papio anubis). I review some major discoveries, like baboon hunting and baboon social strategies of competition and defense, that only a creature with a “mind” could manage. My efforts expanded beyond science to include community-based conservation because quite early on these baboons experienced many of the threats of the Anthropocene. My research expanded to include studying crop-raiding by naïve groups of baboons, the first scientific translocation of a primate species, and a detour to study the invasion of a non-indigenous cactus, Opuntia stricta. Throughout I worked with local communities to find solutions to problems that the baboons created, and also to develop new options for their livelihoods. As the baboon research became a long-term project, it depended on a team of Kenyan research assistants who made possible the simultaneous monitoring of up to six baboon troops as well as extensive ecological monitoring. Knowing the ecology, including the impact of the sedentarization of pastoralists in the area, meant we could interpret the process of invasion by a non-indigenous cactus for the first time. Ecological periods allowed comparisons of the same troop over time and different baboon groups during the same ecological phase. Although I began my work before hypothesis testing was the preferred approach, once the paradigm changed, I continued to study and learn what matters to baboons from their perspective. As a result of observing them for 50 years, the baboons showed me that evolution often does not work the way that I had been taught, and it took all my detours and studies to convince me that anecdotes, when they are systematic and comparative, are not stories to be discounted, but evidence, much like Darwin’s natural history. Natural history can reassemble the pieces that quantitative hypothesis testing has teased apart to provide its larger meaning. Today, the lone scientist, like me, is an anachronism because no one person has expertise in the many fields needed to understand and save the primates we care about.