A review on mycotoxins and mycotoxicoses in ruminants and Equidae in South America.

Of the mycotoxicoses caused by molds contaminating grains or their byproducts, leukoencephalomalacia of horses and less frequently aflatoxicosis in cattle have been reported in South America. However, the most important group of mycotoxins in the region are those caused by fungi that infect forages and other types of plants and have regional distribution. In this group, ergotism is important, both caused by Claviceps purpurea infecting grains or by Epichloë coenophiala infecting Schedonorus arundinaceus. Other important mycotoxicoses are those caused by indole-diterpenes produced by Clavicipitaceous fungi including Claviceps paspali in Paspalum spp., Claviceps cynodontes in Cynodon dactylon, and by Periglandula a seed transmitted symbiont associated with the tremorgenic plant Ipomoea asarifolia. The latter is an important poisoning in the northeastern and northern Brazil. Other important mycotoxicoses are those caused by swainsonine containing plants. It was demonstrated that swainsonine contained in Ipomoea carnea var. fistulosa is produced by an epibiotic fungus of the order Chaetothyriales whose mycelia develop on the adaxial surface of the leaves. Swainsonine is also produced by the symbiotic, endobiotic fungi Alternaria section Undifilum spp., which is associated with Astragalus spp. in the Argentinian Patagonia causing poisoning. Another form of mycotoxicosis occurs in poisoning by Baccharis spp., mainly B. coridifolia, a very important toxic plant in South America that contains macrocyclic trichothecenes probably produced by an endophytic fungus that has not yet been identified. Pithomycotoxicosis caused by Pithomyces chartarum used to be an important mycotoxicosis in the region, mainly in cattle grazing improved pastures of legumes and grasses. Slaframine poisoning, diplodiosis and poisoning by barley contaminated by Aspergillus clavatus has been rarely diagnosed in Brazil, Uruguay and Argentina.

Clostridium spiroforme-associated enteric disease in domestic rabbits: a retrospective study of 32 cases in California, 1992-2019, and literature review.

Clostridium spiroforme has been associated with spontaneous and antibiotic-associated enteric disease (C. spiroforme-associated enteric disease, CSAED) in rabbits, which is clinically characterized by anorexia, diarrhea, or sudden death. Diagnosis is usually based on gross and microscopic lesions, coupled with finding the characteristic coiled bacteria in intestinal smears. Isolation of C. spiroforme is often challenging, and a PCR protocol has been developed. We reviewed 32 cases of CSAED submitted for autopsy to the Davis, Tulare, and Turlock laboratories of CAHFS between 1992 and 2019. The reported gross findings were soiling of the perineum, tail, and/or hind legs with diarrhea (16 of 32); gastric (16 of 32), small intestinal (6 of 32), cecal (15 of 32), and/or colonic (4 of 32) distention with brown-to-green, watery content; and serosal hemorrhages in the cecum (15 of 32). The most common microscopic finding was necrotizing enteritis (19 of 32), followed by cecal mucosal or submucosal edema (8 of 32), necrotizing or pleocellular typhlitis (6 of 32), necrotizing or heterophilic typhlocolitis (6 of 32), and cecal transmural hemorrhages (5 of 32). In all 32 rabbits, typical helically coiled, gram-positive bacilli were observed in fecal or intestinal smears. C. spiroforme was isolated from the intestinal content of 2 of 24 rabbits and detected by PCR assay in 8 of 8 rabbits.

A Critical Review of the Propagation Models Employed in LoRa Systems.

LoRa systems are emerging as a promising technology for wireless sensor networks due to their exceptional range and low power consumption. The successful deployment of LoRa networks relies on accurate propagation models to facilitate effective network planning. Therefore, this review explores the landscape of propagation models supporting LoRa networks. Specifically, we examine empirical propagation models commonly employed in communication systems, assessing their applicability across various environments such as outdoor, indoor, and within vegetation. Our investigation underscores the prevalence of logarithmic decay in most empirical models. In addition, we survey the relationship between model parameters and environmental factors, clearing their nuanced interplay. Analyzing published measurement results, we extract the log-distance model parameters to decipher environmental influences comprehensively. Drawing insights from published measurement results for LoRa, we compare them with the model's outcomes, highlighting successes and limitations. We additionally explore the application of multi-slope models to LoRa measurements to evaluate its effectiveness in enhancing the accuracy of path loss prediction. Finally, we propose new lines for future research in propagation modelling to improve empirical models.

Gingival squamous cell carcinoma in 2 lions under managed care.

Neoplasia is one of the main causes of euthanasia in geriatric captive nondomestic felids. However, few studies have examined oral tumors in these animals. We describe here the clinicopathologic features of gingival squamous cell carcinoma (SCC) in 2 lions (Panthera leo) from separate zoologic collections. In both cases, the lions had a history of sialorrhea, bloody oral discharge, and anorexia. Autopsy findings in both lions were similar and were characterized by poorly circumscribed, friable, and bloody gingival masses with grossly apparent invasion of the mandibular bone; a pathologic fracture was observed in 1 case. Histologically, the masses consisted of poorly circumscribed, unencapsulated, densely cellular proliferations of neoplastic epithelial cells arranged in irregular islands, cords, and anastomosing trabeculae with formation of keratin pearls, which, coupled with positive immunohistochemistry for pancytokeratin, were diagnostic for SCC. Although no metastases were found in either animal, both lions were ultimately euthanized because of poor prognosis.

Fibrinonecrotic enteritis and orchitis associated with Salmonella enterica subsp houtenae infection in a short-tailed boa (Boa constrictor amarali).

Salmonella enterica subsp houtenae has been recovered from a wide variety of species, including reptiles, and has been linked to important clinical manifestations in snakes and lizards. We describe a case of concomitant fibrinonecrotic enteritis and orchitis associated with S. enterica subsp houtenae infection in a short-tailed boa (Boa constrictor amarali). At necropsy, the mucosa of the large intestine was covered by a focally extensive fibrinonecrotic exudate (diphtheritic pseudomembrane). The left testicle was enlarged, firm and diffusely expanded by a thick fibrinous yellow exudate. Polymerase chain reaction and conclusive antigenic testing indicated that the bacteria isolated from the lesions were S. enterica subsp houtenae, and the virulence genes InvA, slyA, stn and spvC were identified. This report reinforces that, although S. enterica subsp houtenae has been isolated from asymptomatic reptiles, it has the potential to cause life-threatening disease in snakes.

EvacuAI: An Analysis of Escape Routes in Indoor Environments with the Aid of Reinforcement Learning.

There is only a very short reaction time for people to find the best way out of a building in a fire outbreak. Software applications can be used to assist the rapid evacuation of people from the building; however, this is an arduous task, which requires an understanding of advanced technologies. Since well-known pathway algorithms (such as, Dijkstra, Bellman-Ford, and A*) can lead to serious performance problems, when it comes to multi-objective problems, we decided to make use of deep reinforcement learning techniques. A wide range of strategies including a random initialization of replay buffer and transfer learning were assessed in three projects involving schools of different sizes. The results showed the proposal was viable and that in most cases the performance of transfer learning was superior, enabling the learning agent to be trained in times shorter than 1 min, with 100% accuracy in the routes. In addition, the study raised challenges that had to be faced in the future.

Botnet Detection and Mitigation Model for IoT Networks Using Federated Learning.

The Internet of Things (IoT) introduces significant security vulnerabilities, raising concerns about cyber-attacks. Attackers exploit these vulnerabilities to launch distributed denial-of-service (DDoS) attacks, compromising availability and causing financial damage to digital infrastructure. This study focuses on mitigating DDoS attacks in corporate local networks by developing a model that operates closer to the attack source. The model utilizes Host Intrusion Detection Systems (HIDS) to identify anomalous behaviors in IoT devices and employs network-based intrusion detection approaches through a Network Intrusion Detection System (NIDS) for comprehensive attack identification. Additionally, a Host Intrusion Detection and Prevention System (HIDPS) is implemented in a fog computing infrastructure for real-time and precise attack detection. The proposed model integrates NIDS with federated learning, allowing devices to locally analyze their data and contribute to the detection of anomalous traffic. The distributed architecture enhances security by preventing volumetric attack traffic from reaching internet service providers and destination servers. This research contributes to the advancement of cybersecurity in local network environments and strengthens the protection of IoT networks against malicious traffic. This work highlights the efficiency of using a federated training and detection procedure through deep learning to minimize the impact of a single point of failure (SPOF) and reduce the workload of each device, thus achieving accuracy of 89.753% during detection and increasing privacy issues in a decentralized IoT infrastructure with a near-real-time detection and mitigation system.

Towards automatic EEG cyclic alternating pattern analysis: a systematic review.

This study conducted a systematic review to determine the feasibility of automatic Cyclic Alternating Pattern (CAP) analysis. Specifically, this review followed the 2020 Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines to address the formulated research question: is automatic CAP analysis viable for clinical application? From the identified 1,280 articles, the review included 35 studies that proposed various methods for examining CAP, including the classification of A phase, their subtypes, or the CAP cycles. Three main trends were observed over time regarding A phase classification, starting with mathematical models or features classified with a tuned threshold, followed by using conventional machine learning models and, recently, deep learning models. Regarding the CAP cycle detection, it was observed that most studies employed a finite state machine to implement the CAP scoring rules, which depended on an initial A phase classifier, stressing the importance of developing suitable A phase detection models. The assessment of A-phase subtypes has proven challenging due to various approaches used in the state-of-the-art for their detection, ranging from multiclass models to creating a model for each subtype. The review provided a positive answer to the main research question, concluding that automatic CAP analysis can be reliably performed. The main recommended research agenda involves validating the proposed methodologies on larger datasets, including more subjects with sleep-related disorders, and providing the source code for independent confirmation.

Outbreaks of dermatopathy caused by Tephrosia noctiflora intoxication in Brazilian cattle.

This study aims to update the knowledge concerning the intoxication by Tephrosia noctiflora in Brazilian cattle herds by reporting new cases of intoxication in lactating cows, their calves and bulls and highlight the epidemiology, clinical signs, pathogenesis, gross, and microscopic lesions. The morbidity and mortality of this intoxication in the farms studied was low. Gross lesions in all affected cattle consisted of dermatitis with hyperpigmentation, crusts, ulceration, erythema, and lichenification in the skin of limbs, ventral abdomen, perianal and perineal areas of lactating calves and adult cattle. Microscopically, the main lesion observed consisted of severe dermatitis with parakeratotic hyperkeratosis, papillated proliferation, and diffuse, accentuated lymphoplasmacytic inflammatory infiltrate in the epidermis and dermis. The presence of skin lesions mainly in the limbs and ventral abdomen of cattle implies the pathogenesis of intoxication is related to a primary contact dermatitis, and the occurrence of similar lesions on the skin of nursing calves reinforces this hypothesis. The putative toxins of T. noctiflora have been thought to be rotenoids. Additional work is needed to define better if these compounds are the main toxin responsible for the dermatopathy observed in these herds.

Comparative morphofunctional analysis of axial skeleton excluding the skull of primates based on the anatomical, radiographic, and tomographic description of the black-striped capuchin (Sapajus libidinosus Spix, 1823).

Comparative anatomy the basis for studies of evolution, and radiographic and tomographic aspects, as auxiliary methods in the investigation of anatomical particularities, reinforce evolutionary research. Therefore, the aim of this study was to describe the vertebrae, sternum, and ribs of the capuchin monkey (Sapajus libidinosus) by means of anatomical dissection and radiographic and tomographic images. To this purpose, four cadavers were used in the anatomical analysis and five living animals for the imaging exams. The bones were described and compared with data from other primates species found in literature. Student's t-test for independent samples was performed. The vertebral column of the comprises seven cervical, 13 or 14 thoracic, five or six lumbar, two or three sacral, and 23 or 24 caudal vertebrae. The atlas is characterized by three foramina on the wing. The seventh cervical vertebra had a transverse foramen in one specimen. The anticlinal vertebra is always the penultimate thoracic one, the ninth pair of ribs is always the last sternal pair, and the last two are buoyant. The sternal was composed of five or six sternebrae. The lumbar vertebrae showed a bifurcated spinous process. Three different sacral morphologies were observed. The structures identified macroscopically could be well determined through radiographic and tomographic images. S. libidinosus presented anatomical characteristics more similar to those of man and of platirrinos monkeys. The knowledge obtained by macroscopic anatomy and tomographic and radiological exams contributes significantly to comparative evolutionary studies.

Identification of orphan histidine kinases that impact sporulation and enterotoxin production by Clostridium perfringens type F strain SM101 in a pathophysiologically-relevant ex vivo mouse intestinal contents model.

When causing food poisoning or antibiotic-associated diarrhea, Clostridium perfringens type F strains must sporulate to produce C. perfringens enterotoxin (CPE) in the intestines. C. perfringens is thought to use some of its seven annotated orphan histidine kinases to phosphorylate Spo0A and initiate sporulation and CPE production. We previously demonstrated the CPR0195 orphan kinase, but not the putative CPR1055 orphan kinase, is important when type F strain SM101 initiates sporulation and CPE production in modified Duncan-Strong (MDS) sporulation medium. Since there is no small animal model for C. perfringens sporulation, the current study used diluted mouse intestinal contents (MIC) to develop an ex vivo sporulation model and employed this model to test sporulation and CPE production by SM101 CPR0195 and CPR1055 null mutants in a pathophysiologically-relevant context. Surprisingly, both mutants still sporulated and produced CPE at wild-type levels in MIC. Therefore, five single null mutants were constructed that cannot produce one of the previously-unstudied putative orphan kinases of SM101. Those mutants implicated CPR1316, CPR1493, CPR1953 and CPR1954 in sporulation and CPE production by SM101 MDS cultures. Phosphorylation activity was necessary for CPR1316, CPR1493, CPR1953 and CPR1954 to affect sporulation in those MDS cultures, supporting their identity as kinases. Importantly, only the CPR1953 or CPR1954 null mutants exhibited significantly reduced levels of sporulation and CPE production in MIC cultures. These phenotypes were reversible by complementation. Characterization studies suggested that, in MDS or MIC, the CPR1953 and CPR1954 mutants produce less Spo0A than wild-type SM101. In addition, the CPR1954 mutant exhibited little or no Spo0A phosphorylation in MDS cultures. These studies, i) highlight the importance of using pathophysiologically-relevant models to investigate C. perfringens sporulation and CPE production in a disease context and ii) link the CPR1953 and CPR1954 kinases to C. perfringens sporulation and CPE production in disease-relevant conditions.

Tyzzer disease in 19 preweaned orphaned kittens.

Clostridium piliforme, the agent of Tyzzer disease, has traditionally not been considered a major pathogen of cats. We queried the database of the Pathology Service of the Veterinary Medical Teaching Hospital, University of California-Davis, for kittens <6-mo-old autopsied between 2000-2021 that had colitis, hepatitis, and/or myocarditis; 37 cases met the search criteria. Sections of colon, liver, and heart from these 37 cats were stained with modified Steiner; 19 of 37 (51%) cases had intraepithelial, Steiner-positive rods compatible with C. piliforme in at least one organ, confirming Tyzzer disease. The affected age range was 7-42 d (median: 17.5 d). Eighteen were orphaned kittens. Colitis was the major lesion (18 of 19) followed by random hepatitis (11 of 19). Perianal dermatitis with intraepithelial stacked rods was seen in 2 of 19. Myocarditis was not evident in any of the cases. A PCR assay for C. piliforme on 10 selected cases using formalin-fixed, paraffin-embedded (FFPE) blocks was positive or suspected in colon (5 of 10), liver (5 of 10), and heart (1 of 10). The modified Steiner stain was more sensitive in the detection of bacteria than PCR on FFPE samples. Fifteen kittens had comorbidities. A weakened immune state caused by maternal, environmental, infectious, and/or nutritional causes is speculated to have contributed to disease onset. We found that Tyzzer disease is more common than previously believed in orphaned kittens and should be considered in kittens with colitis and/or hepatitis.

Non-Destructive Banana Ripeness Detection Using Shallow and Deep Learning: A Systematic Review.

The ripeness of bananas is the most significant factor affecting nutrient composition and demand. Conventionally, cutting and ripeness analysis requires expert knowledge and substantial human intervention, and different studies have been conducted to automate and substantially reduce human effort. Using the Preferred Reporting Items for the Systematic Reviews approach, 1548 studies were extracted from journals and conferences, using different research databases, and 35 were included in the final review for key parameters. These studies suggest the dominance of banana fingers as input data, a sensor camera as the preferred capturing device, and appropriate features, such as color, that can provide better detection. Among six stages of ripeness, the studies employing the four mentioned stages performed better in terms of accuracy and coefficient of determination value. Among all the works for detecting ripeness stages prediction, convolutional neural networks were found to perform sufficiently well with large datasets, whereas conventional artificial neural networks and support vector machines attained better performance for sensor-related data. However, insufficient information on the dataset and capturing device, limited data availability, and exploitation of data augmentation techniques are limitations in existing studies. Thus, effectively addressing these shortcomings and close collaboration with experts to predict the ripeness stages should be pursued.

Probability and number of bruises in bovine carcasses according to animal type, handling and transport.

The aim of this study was to evaluate pre-slaughter risk factors on the probability of bruising and the number of bruises in different regions of the bovine carcass. The study evaluated the data from 4061 batches of slaughtered cattle, totalling 199,026 carcasses, from Hereford and Aberdeen Angus animals in crosses with continental European breeds and Zebu cattle. The factors that caused injury were sex, handling conditions (score), vehicle type, vehicle load density (kg/m2), travel time (minutes), travel distance (kilometres), physiological maturity (dentition), animal reactivity (score), and carcass fat (score). The type of vehicle had the greatest influence on the probability of carcass bruising and affected all carcass cuts. More bruising occurred in vehicles with a greater load capacity. A higher chance of bruising was seen in groups of older animals, those with an excitable temperament and, especially, in groups of females. Higher load densities during transport resulted in a greater chance of bruising occurring in all cuts except the hindquarters. Distance and travel time are unstable in the models, but also detrimental, increasing the probability of bruising and the number of bruises in the various cuts. The results of this study suggest that good practices in the welfare, handling and transport of the animals, as well as training the personnel responsible for their handling, should be adopted to minimise the risk of injury at different locations on the carcass.

Novel Comparative Study for the Detection of COVID-19 Using CT Scan and Chest X-ray Images.

The number of coronavirus disease (COVID-19) cases is constantly rising as the pandemic continues, with new variants constantly emerging. Therefore, to prevent the virus from spreading, coronavirus cases must be diagnosed as soon as possible. The COVID-19 pandemic has had a devastating impact on people's health and the economy worldwide. For COVID-19 detection, reverse transcription-polymerase chain reaction testing is the benchmark. However, this test takes a long time and necessitates a lot of laboratory resources. A new trend is emerging to address these limitations regarding the use of machine learning and deep learning techniques for automatic analysis, as these can attain high diagnosis results, especially by using medical imaging techniques. However, a key question arises whether a chest computed tomography scan or chest X-ray can be used for COVID-19 detection. A total of 17,599 images were examined in this work to develop the models used to classify the occurrence of COVID-19 infection, while four different classifiers were studied. These are the convolutional neural network (proposed architecture (named, SCovNet) and Resnet18), support vector machine, and logistic regression. Out of all four models, the proposed SCoVNet architecture reached the best performance with an accuracy of almost 99% and 98% on chest computed tomography scan images and chest X-ray images, respectively.

A-phase index: an alternative view for sleep stability analysis based on automatic detection of the A-phases from the cyclic alternating pattern.

STUDY OBJECTIVES: Sleep stability can be studied by evaluating the cyclic alternating pattern (CAP) in electroencephalogram (EEG) signals. The present study presents a novel approach for assessing sleep stability, developing an index based on the CAP A-phase characteristics to display a sleep stability profile for a whole night's sleep. METHODS: Two ensemble classifiers were developed to automatically score the signals, one for "A-phase" and the other for "non-rapid eye movement" estimation. Both were based on three one-dimension convolutional neural networks. Six different inputs were produced from the EEG signal to feed the ensembles' classifiers. A proposed heuristic-oriented search algorithm individually tuned the classifiers' structures. The outputs of the two ensembles were combined to estimate the A-phase index (API). The models can also assess the A-phase subtypes, their API, and the CAP cycles and rate. RESULTS: Four dataset variations were considered, examining healthy and sleep-disordered subjects. The A-phase average estimation's accuracy, sensitivity, and specificity range was 82%-87%, 72%-80%, and 82%-88%, respectively. A similar performance was attained for the A-phase subtype's assessments, with an accuracy range of 82%-88%. Furthermore, in the examined dataset's variations, the API metric's average error varied from 0.15 to 0.25 (with a median range of 0.11-0.24). These results were attained without manually removing wake or rapid eye movement periods, leading to a methodology suitable to produce a fully automatic CAP scoring algorithm. CONCLUSIONS: Metrics based on API can be understood as a new view for CAP analysis, where the goal is to produce and examine a sleep stability profile.

Multiple Time Series Fusion Based on LSTM: An Application to CAP A Phase Classification Using EEG.

The Cyclic Alternating Pattern (CAP) is a periodic activity detected in the electroencephalogram (EEG) signals. This pattern was identified as a marker of unstable sleep with several possible clinical applications; however, there is a need to develop automatic methodologies to facilitate real-world applications based on CAP assessment. Therefore, a deep learning-based EEG channels' feature level fusion was proposed in this work and employed for the CAP A phase classification. Two optimization algorithms optimized the channel selection, fusion, and classification procedures. The developed methodologies were evaluated by fusing the information from multiple EEG channels for patients with nocturnal frontal lobe epilepsy and patients without neurological disorders. Results showed that both optimization algorithms selected a comparable structure with similar feature level fusion, consisting of three electroencephalogram channels (Fp2-F4, C4-A1, F4-C4), which is in line with the CAP protocol to ensure multiple channels' arousals for CAP detection. Moreover, the two optimized models reached an area under the receiver operating characteristic curve of 0.82, with average accuracy ranging from 77% to 79%, a result in the upper range of the specialist agreement and best state-of-the-art works, despite a challenging dataset. The proposed methodology also has the advantage of providing a fully automatic analysis without requiring any manual procedure. Ultimately, the models were revealed to be noise-resistant and resilient to multiple channel loss, being thus suitable for real-world application.

Identification of a Virulent Newcastle Disease Virus Strain Isolated from Pigeons (Columbia livia) in Northeastern Brazil Using Next-Generation Genome Sequencing.

Newcastle disease virus (NDV), also known as avian paramyxoviruses 1 (APMV-1) is among the most important viruses infecting avian species. Given its widespread circulation, there is a high risk for the reintroduction of virulent strains into the domestic poultry industry, making the surveillance of wild and domestic birds a crucial process to appropriately respond to novel outbreaks. In the present study, we investigated an outbreak characterized by the identification of sick pigeons in a large municipality in Northeastern Brazil in 2018. The affected pigeons presented neurological signs, including motor incoordination, torticollis, and lethargy. Moribund birds were collected, and through a detailed histopathological analysis we identified severe lymphoplasmacytic meningoencephalitis with perivascular cuffs and gliosis in the central nervous system, and lymphoplasmacytic inflammation in the liver, kidney, and intestine. A total of five pigeons tested positive for NDV, as assessed by rRT-PCR targeted to the M gene. Laboratory virus isolation on Vero E6 cells confirmed infection, after the recovery of infectious NVD from brain and kidney tissues. We next characterized the isolated NDV/pigeon/PE-Brazil/MP003/2018 by next-generation sequencing (NGS). Phylogenetic analysis grouped the virus with other NDV class II isolates from subgenotype VI.2.1.2, including two previous NDV isolates from Brazil in 2014 and 2019. The diversity of aminoacid residues at the fusion F protein cleavage site was analyzed identifying the motif RRQKR↓F, typical of virulent strains. Our results all highlight the importance of virus surveillance in wild and domestic birds, especially given the risk of zoonotic NDV.

Anatomy applied to image diagnosis of the hind limb in the black-striped capuchin (Sapajus libidinosus Spix, 1823).

The knowledge of anatomy and imaging exams emerges as an important tool in the study of evolutionary processes of a species, in the elaboration of diagnosis, and the successful choice of the appropriate clinical and surgical procedures. Therefore, this study aims to describe the osteology of the hind limb of Sapajus libidinosus by means of gross, radiographic, and tomographic images. Four cadavers were used in the macroscopic analysis and five animals for the imaging exams, of which four were eventually euthanized and added to the macroscopic study. For imaging exams, they were kept anesthetized. All bones of the hind limb were documented, their structures were described, and compared with data in the literature from human and nonhuman primates. We have performed Student's t test for independent samples. There was no statistical difference between the sexes regarding the length of the hind limb bones. The coxal bone was largely well described using imaging methods. A small penile bone was present at the tip of the penis and it could be identified by all analysis methods. The femur, as well as the tibia and fibula, were not well portrayed in their proximal and distal epiphyses by radiography (Rx). However, they were well identified on tomography. No third trochanter was observed in the femur and the patella had a triangular shape. All the structures described by gross anatomy of the tarsus and metatarsus could be identified by Rx and tomography. More subtle structures, such as the popliteal notch on the tibia, and the gluteal tuberosity pectineal line and facies aspera on the coxal bone, were not identified by medical imaging. S. libidinosus presented anatomical characteristics that were similar to those of larger New World and Old World monkeys, including man. This suggests it's value as an experimental model for studies in recent primates.

Heuristic Optimization of Deep and Shallow Classifiers: An Application for Electroencephalogram Cyclic Alternating Pattern Detection.

Methodologies for automatic non-rapid eye movement and cyclic alternating pattern analysis were proposed to examine the signal from one electroencephalogram monopolar derivation for the A phase, cyclic alternating pattern cycles, and cyclic alternating pattern rate assessments. A population composed of subjects free of neurological disorders and subjects diagnosed with sleep-disordered breathing was studied. Parallel classifications were performed for non-rapid eye movement and A phase estimations, examining a one-dimension convolutional neural network (fed with the electroencephalogram signal), a long short-term memory (fed with the electroencephalogram signal or with proposed features), and a feed-forward neural network (fed with proposed features), along with a finite state machine for the cyclic alternating pattern cycle scoring. Two hyper-parameter tuning algorithms were developed to optimize the classifiers. The model with long short-term memory fed with proposed features was found to be the best, with accuracy and area under the receiver operating characteristic curve of 83% and 0.88, respectively, for the A phase classification, while for the non-rapid eye movement estimation, the results were 88% and 0.95, respectively. The cyclic alternating pattern cycle classification accuracy was 79% for the same model, while the cyclic alternating pattern rate percentage error was 22%.