Facial Fracture Injury Criteria from Night Vision Goggle Impact.

INTRODUCTION: Military personnel extensively use night vision goggles (NVGs) in contemporary scenarios. Since NVGs may induce or increase injuries from falls or vehicular accidents, biomechanical risk assessments would aid design goal or mitigation strategy development.METHODS: This study assesses injury risks from NVG impact on cadaver heads using impactors modeled on the PVS-14 NVG. Impacts to the zygoma and maxilla were performed at 20° or 40° angles. Risks of facial fracture, neurotrauma, and neck injury were assessed. Acoustic sensors and accelerometers assessed time of fracture and provided input variables for injury risk functions. Injuries were assessed using the Abbreviated Injury Scale (AIS); injury severity was assessed using the Rhee and Donat scales. Risk functions were developed for the input variables using censored survival analyses.RESULTS: The effects of impact angle and bone geometry on injury characteristics were determined with loading area, axial force, energy attenuation, and stress at fracture. Probabilities of facial fracture were quantified through survival analysis and injury risk functions. These risk functions determined a 50% risk of facial bone fracture at 1148 N (axial force) at a 20° maxillary impact, 588 N at a 40° maxillary impact, and 677 N at a 20° zygomatic impact. A cumulative distribution function indicates 769 N corresponds to 50% risk of fracture overall.DISCUSSION: Results found smaller impact areas on the maxilla are correlated with higher angles of impact increasing risk of facial fracture, neck injuries are unlikely to occur before fracture or neurotrauma, and a potential trade-off mechanism between fracture and brain injury.Davis MB, Pang DY, Herring IP, Bass CR. Facial fracture injury criteria from night vision goggle impact. Aerosp Med Hum Perform. 2023; 94(11):827-834.

Fast updating feedback from piriform cortex to the olfactory bulb relays multimodal reward contingency signals during rule-reversal.

While animals readily adjust their behavior to adapt to relevant changes in the environment, the neural pathways enabling these changes remain largely unknown. Here, using multiphoton imaging, we investigated whether feedback from the piriform cortex to the olfactory bulb supports such behavioral flexibility. To this end, we engaged head-fixed mice in a multimodal rule-reversal task guided by olfactory and auditory cues. Both odor and, surprisingly, the sound cues triggered cortical bulbar feedback responses which preceded the behavioral report. Responses to the same sensory cue were strongly modulated upon changes in stimulus-reward contingency (rule reversals). The re-shaping of individual bouton responses occurred within seconds of the rule-reversal events and was correlated with changes in the behavior. Optogenetic perturbation of cortical feedback within the bulb disrupted the behavioral performance. Our results indicate that the piriform-to-olfactory bulb feedback carries reward contingency signals and is rapidly re-formatted according to changes in the behavioral context.

High-throughput sequencing of single neuron projections reveals spatial organization in the olfactory cortex.

In most sensory modalities, neuronal connectivity reflects behaviorally relevant stimulus features, such as spatial location, orientation, and sound frequency. By contrast, the prevailing view in the olfactory cortex, based on the reconstruction of dozens of neurons, is that connectivity is random. Here, we used high-throughput sequencing-based neuroanatomical techniques to analyze the projections of 5,309 mouse olfactory bulb and 30,433 piriform cortex output neurons at single-cell resolution. Surprisingly, statistical analysis of this much larger dataset revealed that the olfactory cortex connectivity is spatially structured. Single olfactory bulb neurons targeting a particular location along the anterior-posterior axis of piriform cortex also project to matched, functionally distinct, extra-piriform targets. Moreover, single neurons from the targeted piriform locus also project to the same matched extra-piriform targets, forming triadic circuit motifs. Thus, as in other sensory modalities, olfactory information is routed at early stages of processing to functionally diverse targets in a coordinated manner.

Developing a Trauma-Informed and Recovery-Oriented Alternative to 'Aggression Management' Training for a Metropolitan and Rural Mental Health Service.

For clinicians working in mental health services, 'aggression management' training is generally prioritised, and often mandated. Traditional 'aggression management' training has the potential to reinforce the perception that violence and aggression are inevitable, and thus defensive and coercive practices are needed. This paper outlines the principles and processes that underpinned the development of two training programs designed as recovery-oriented and trauma-informed alternatives to traditional 'aggression management' training. The focus of the paper is on exploring how 'aggression management' training can be aligned with best practice principles. The programs were developed in a metropolitan and rural mental health service and aimed to reduce the need for defensive and coercive practices by promoting therapeutic engagement. A key feature of both programs is an orientation towards safety rather than risk. By embedding the principles of recovery and trauma-informed care in their development and orienting training towards enhancing safety, clinicians are provided with a new way of conceptualising and responding to 'aggression'. Experiential methods in the delivery of the training, and the co-design and co-delivery with peer (consumer) educators were important in supporting attitudinal change. To promote safety, the language and content of training programs must reflect contemporary principles and approaches such as trauma-informed care and recovery. This paper illustrates that to be effective, these principles and approaches must not just be described, but modelled in the development, design, and delivery of the training.

Applying Machine Learning Approaches to Suicide Prediction Using Healthcare Data: Overview and Future Directions.

Objective: Early identification of individuals who are at risk for suicide is crucial in supporting suicide prevention. Machine learning is emerging as a promising approach to support this objective. Machine learning is broadly defined as a set of mathematical models and computational algorithms designed to automatically learn complex patterns between predictors and outcomes from example data, without being explicitly programmed to do so. The model's performance continuously improves over time by learning from newly available data. Method: This concept paper explores how machine learning approaches applied to healthcare data obtained from electronic health records, including billing and claims data, can advance our ability to accurately predict future suicidal behavior. Results: We provide a general overview of machine learning concepts, summarize exemplar studies, describe continued challenges, and propose innovative research directions. Conclusion: Machine learning has potential for improving estimation of suicide risk, yet important challenges and opportunities remain. Further research can focus on incorporating evolving methods for addressing data imbalances, understanding factors that affect generalizability across samples and healthcare systems, expanding the richness of the data, leveraging newer machine learning approaches, and developing automatic learning systems.

Alcohol Use Disorder in the Age of Technology: A Review of Wearable Biosensors in Alcohol Use Disorder Treatment.

Biosensors enable observation and understanding of latent physiological occurrences otherwise unknown or invasively detected. Wearable biosensors monitoring physiological constructs across a wide variety of mental and physical health conditions have become an important trend in innovative research methodologies. Within substance use research, explorations of biosensor technology commonly focus on identifying physiological indicators of intoxication to increase understanding of addiction etiology and to inform treatment recommendations. In this review, we examine the state of research in this area as it pertains to treatment of alcohol use disorders specifically highlighting the gaps in our current knowledge with recommendations for future research. Annually, alcohol use disorders affect approximately 15 million individuals. A primary focus of existing wearable technology-based research among people with alcohol use disorders is identifying alcohol intoxication. A large benefit of wearable biosensors for this purpose is they provide continuous readings in a passive manner compared with the gold standard measure of blood alcohol content (BAC) traditionally measured intermittently by breathalyzer or blood draw. There are two primary means of measuring intoxication with biosensors: gait and sweat. Gait changes have been measured via smart sensors placed on the wrist, in the shoe, and mobile device sensors in smart phones. Sweat measured by transdermal biosensors detects the presence of alcohol in the blood stream correlating to BAC. Transdermal biosensors have been designed in tattoos/skin patches, shirts, and most commonly, devices worn on the ankle or wrist. Transdermal devices were initially developed to help monitor court-ordered sobriety among offenders with alcohol use disorder. These devices now prove most useful in continuously tracking consumption throughout clinical trials for behavioral treatment modalities. More recent research has started exploring the uses for physical activity trackers and physiological arousal sensors to guide behavioral interventions for relapse prevention. While research has begun to demonstrate wearable devices' utility in reducing alcohol consumption among individuals aiming to cutdown on their drinking, monitoring sustained abstinence in studies exploring contingency management for alcohol use disorders, and facilitating engagement in activity-based treatment interventions, their full potential to further aid in understanding of, and treatment for, alcohol use disorders has yet to be explored.

Computational and experimental characterization of the novel ECM glycoprotein SNED1 and prediction of its interactome.

The extracellular matrix (ECM) is a complex meshwork of proteins and an essential component of multicellular life. We have recently reported the characterization of a novel ECM protein, SNED1, and showed that it promotes breast cancer metastasis and regulates craniofacial development. However, the mechanisms by which it does so remain unknown. ECM proteins exert their functions by binding to cell surface receptors and interacting with other ECM proteins, actions that we can predict using knowledge of protein's sequence, structure, and post-translational modifications. Here, we combined in-silico and in-vitro approaches to characterize the physico-chemical properties of SNED1 and infer its putative functions. To do so, we established a mammalian cell system to produce and purify SNED1 and its N-terminal fragment, which contains a NIDO domain, and demonstrated experimentally SNED1's potential to be glycosylated, phosphorylated, and incorporated into an insoluble ECM. We also determined the secondary and tertiary structures of SNED1 and its N-terminal fragment and obtained a model for its NIDO domain. Using computational predictions, we identified 114 proteins as putative SNED1 interactors, including the ECM protein fibronectin. Pathway analysis of the predicted SNED1 interactome further revealed that it may contribute to signaling through cell surface receptors, such as integrins, and participate in the regulation of ECM organization and developmental processes. Last, using fluorescence microscopy, we showed that SNED1 forms microfibrils within the ECM and partially colocalizes with fibronectin. Altogether, we provide a wealth of information on an understudied yet important ECM protein with the potential to decipher its pathophysiological functions.

Perspectives of diabetes educators and dental hygienists regarding strategies to improve oral health for people with diabetes.

Aims: This study aims to explore the opinions of dental hygienists and diabetes educators on improving oral health for people with diabetes. Methods: Registered dental hygienists (RDHs) and certified diabetes educators (CDEs) who provided written responses to the same open-ended question from two state-wide mailing surveys (one for RDHs and the other for CDEs) "what more can you tell us to help improve oral health for people with diabetes?" were included in this study. The surveys were sent to all RDHs (n=2237) and CDEs (n=250) in the state of South Carolina, United States. Results: Of the 1125 valid returned questionnaires from both surveys, 474 provided written responses to this question. Qualitative analysis revealed three main themes from participants' written responses which were: Education (3 subthemes: resources for patients, educate the public, and professional practice resources), interprofessional collaborative care (3 subthemes: role of medical and dental professionals in oral health promotion for people with diabetes, and role of dental and diabetes professional organizations, and companies in the oral healthcare industry), and dental insurance. Conclusions: The three themes that emerged are interrelated indicating that strategies to improve oral health for people with diabetes are multi-faceted.

Pan-Cancer Analysis of the Genomic Alterations and Mutations of the Matrisome.

The extracellular matrix (ECM) is a master regulator of all cellular functions and a major component of the tumor microenvironment. We previously defined the "matrisome" as the ensemble of genes encoding ECM proteins and proteins modulating ECM structure or function. While compositional and biomechanical changes in the ECM regulate cancer progression, no study has investigated the genomic alterations of matrisome genes in cancers and their consequences. Here, mining The Cancer Genome Atlas (TCGA) data, we found that copy number alterations and mutations are frequent in matrisome genes, even more so than in the rest of the genome. We also found that these alterations are predicted to significantly impact gene expression and protein function. Moreover, we identified matrisome genes whose mutational burden is an independent predictor of survival. We propose that studying genomic alterations of matrisome genes will further our understanding of the roles of this compartment in cancer progression and will lead to the development of innovative therapeutic strategies targeting the ECM.

Mind the gaps: identifying opportunities in mental health assessment and mental health certificate completion in rural and remote NSW, Australia.

OBJECTIVE: This study aimed to examine the quality of mental health certificate (MHC) completion in rural and remote New South Wales, to include the determination of those identified as mentally ill or mentally disordered, and subsequent processes thereafter. METHODS: MHCs were collected from April 2016 to March 2017. A de-identified review was undertaken and audited for completion of mandatory criteria. Data were separated by three groups of completing health practitioners, and descriptive and inferential statistics calculated to assess for differences between groups. RESULTS: A total of 277 MHCs were included. Local medical officers were significantly more likely to: have longer assessment periods, indicate mentally disordered rather than mentally ill, and to have the mental health certificate revoked upon reassessment at a declared mental health facility, than their psychiatry or accredited person peers. They were also significantly less likely to complete documentation relating to behaviour personally assessed or observed by others. CONCLUSION: This study identified inconsistencies in documentation completion between groups, highlighting training opportunities for non-mental health specialists, particularly mental health assessment and lawful detention requirements. Attention to this is warranted within medical training syllabuses, post-graduate training and support programs.

Syntheses, Structures, and Infrared Spectra of the Hexa(cyanido) Complexes of Silicon, Germanium, and Tin.

The rare octahedral EC6 coordination skeleton type is unknown for complexes with coordination centers consisting of group 14 elements. Here, the first examples of such EC6 species, the hexacoordinate homoleptic cyanido complexes E(CN)62-, E = Si, Ge, Sn, have been synthesized from element halides SiCl4, GeCl4 and SnF4 and isolated as salts with PPN counterions (PPN+ = (Ph3P)2N+) on a scale of 0.2-1 g. Characterization by spectroscopic techniques and by structure determination through single crystal crystallographic methods show that these pseudohalogen complexes have effective octahedral symmetry in solution and in the solid state. Infrared spectra obtained in solution reveal that the T1 u symmetric IR-active vibrations in all three complexes have unusually small oscillator strengths. The observed reluctance of Si(CN)62-, Ge(CN)62-, and Sn(CN)62- to form from chloro-precursors was rationalized in terms of Gibbs free energies, which were found by ab initio calculations at the CCSD(T)-F12b/aug-cc-pVTZ(-PP)-F12 level of theory to be small or even positive. The work demonstrates that E(CN)62- complexes of silicon, germanium and tin are in fact stable at room temperature and exist as well-defined units in the presence of noncoordinating counterions. The results add to our understanding of the chemistry of pseudohalogens and structure and bonding.

The in-silico characterization of the Caenorhabditis elegans matrisome and proposal of a novel collagen classification.

Proteins are the building blocks of life. While proteins and their localization within cells and sub-cellular compartments are well defined, the proteins predicted to be secreted to form the extracellular matrix - or matrisome - remain elusive in the model organism C. elegans. Here, we used a bioinformatic approach combining gene orthology and protein structure analysis and an extensive curation of the literature to define the C. elegans matrisome. Similar to the human genome, we found that 719 out of ~20,000 genes (~4%) of the C. elegans genome encodes matrisome proteins, including 181 collagens, 35 glycoproteins, 10 proteoglycans, and 493 matrisome-associated proteins. We report that 173 out of the 181 collagen genes are unique to nematodes and are predicted to encode cuticular collagens, which we are proposing to group into five clusters. To facilitate the use of our lists and classification by the scientific community, we developed an automated annotation tool to identify ECM components in large datasets. We also established a novel database of all C. elegans collagens (CeColDB). Last, we provide examples of how the newly defined C. elegans matrisome can be used for annotations and gene ontology analyses of transcriptomic, proteomic, and RNAi screening data. Because C. elegans is a widely used model organism for high throughput genetic and drug screens, and to study biological and pathological processes, the conserved matrisome genes may aid in identifying potential drug targets. In addition, the nematode-specific matrisome may be exploited for targeting parasitic infection of man and crops.

In-silico definition of the Drosophila melanogaster matrisome.

The extracellular matrix (ECM) is an assembly of hundreds of proteins that structurally supports the cells it surrounds and biochemically regulates their functions. Drosophila melanogaster has emerged as a powerful model organism to study fundamental mechanisms underlying ECM protein secretion, ECM assembly, and ECM roles in pathophysiological processes. However, as of today, we do not possess a well-defined list of the components forming the ECM of this organism. We previously reported the development of computational pipelines to define the matrisome - the ensemble of genes encoding ECM and ECM-associated proteins - of humans, mice, zebrafish and C. elegans. Using a similar approach, we report here that our pipeline has identified 641 genes constituting the Drosophila matrisome. We further classify these genes into different structural and functional categories, including an expanded way to classify genes encoding proteins forming apical ECMs. We illustrate how having a comprehensive list of Drosophila matrisome proteins can be used to annotate large proteomic datasets and identify unsuspected roles for the ECM in pathophysiological processes. Last, to aid the dissemination and usage of the proposed definition and categorization of the Drosophila matrisome by the scientific community, our list has been made available through three public portals: The Matrisome Project (http://matrisome.org), The FlyBase (https://flybase.org/), and GLAD (https://www.flyrnai.org/tools/glad/web/).

Cognitive-Behavioral Therapy for Insomnia to Reduce Chronic Migraine: A Sequential Bayesian Analysis.

BACKGROUND: Insomnia is frequently comorbid with chronic migraine, and small trials suggest that cognitive-behavioral treatment of insomnia (CBTi) may reduce migraine frequency. This study endeavored to provide a quantitative synthesis of existing CBTi trials for adults with chronic migraine using Bayesian statistical methods, given their utility in combining prior knowledge with sequentially gathered data. METHODS: Completer analyses of 2 randomized trials comparing CBTi to a sham control intervention (Calhoun and Ford, 2007; Smitherman et al, 2016) were used to quantify the effects of a brief course of treatment on headache frequency. Change in headache frequency from baseline to the primary endpoint (6-8 weeks posttreatment) was regressed on group status using a Gaussian linear model with each study specified in the order of completion. To estimate the combined effect, posterior distributions from the Calhoun and Ford study were used as informative priors for conditioning on the Smitherman et al data. RESULTS: In a combined analysis of these prior studies, monthly headache frequency of the treatment group decreased by 6.2 days (95%CrI: -9.7 to -2.7) more than the control group, supporting an interpretation that there is a 97.5% chance that the treatment intervention is at least 2.7 days better than the control intervention. The analysis supports the hypothesis that at least for those who complete treatment, there is high probability that individuals who receive CBTi experience greater headache reduction than those who receive a control intervention equated for therapist time and out-of-session skills practice. CONCLUSION: Cognitive-behavioral interventions for comorbid insomnia hold promise for reducing headache frequency among those with chronic migraine. These findings add to a small but growing body of literature that migraineurs with comorbid conditions often respond well to behavioral interventions, and that targeting comorbidities may improve migraine itself.

Perceived triggers of primary headache disorders: A meta-analysis.

Objective To quantitatively synthesize extant literature on perceived triggers of primary headache disorders. Methods A meta-analytic review of headache trigger survey studies was conducted. Endorsement rates, assessment method, and headache and sample characteristics were extracted from included articles. Separate random-effects models were used to assess trigger endorsement rates and post-hoc meta-regressions examined potential moderator variables. Results 85 articles from 1958 to 2015 were included, involving 27,122 participants and querying 420 unique triggers (collapsed into 15 categories). Four-fifths (0.81; 95% CI .75 to .86) of individuals with migraine or tension-type headache endorsed at least one trigger. Rates increased with the number of categories queried (OR: 1.18, 1.08-1.30) and year of publication (OR: 1.04, 1.00-1.08). The triggers most commonly endorsed were stress (.58, .53-.63) and sleep (.41, .36-.47). Conclusions Extreme heterogeneity characterizes the headache trigger literature. Most individuals with a primary headache disorder perceive their attacks to be triggered by one or more precipitants, the most common of which are stress and sleep. However, trigger endorsement is influenced by method of assessment. Enhancing methodological consistency and prioritizing experimental studies would improve our understanding of headache triggers.

Alcohol Use as a Comorbidity and Precipitant of Primary Headache: Review and Meta-analysis.

PURPOSE OF REVIEW: In contrast to well-established relationships between headache and affective disorders, the role of alcohol use in primary headache disorders is less clear. This paper provides a narrative overview of research on alcohol use disorders (AUDs) in primary headache and presents a meta-analysis of the role of alcohol as a trigger (precipitant) of headache. RECENT FINDINGS: The majority of studies on AUDs in headache have failed to find evidence that migraine or tension-type headache (TTH) is associated with increased risk for AUDs or problematic alcohol use. The meta-analysis indicated that 22% (95% CI: 17-29%) of individuals with primary headache endorsed alcohol as a trigger. No differences were found between individuals with migraine (with or without aura) or TTH. Odds of endorsing red wine as a trigger were over 3 times greater than odds of endorsing beer. An absence of increased risk for AUDs among those with primary headache may be attributable to alcohol's role in precipitating headache attacks for some susceptible individuals. Roughly one fifth of headache sufferers believe alcohol precipitates at least some of their attacks. Considerable study heterogeneity limits fine-grained comparisons across studies and suggests needs for more standardized methods for studying alcohol-headache relationships and rigorous experimental designs.

Health Evaluation and Referral Assistant: A Randomized Controlled Trial of a Web-Based Screening, Brief Intervention, and Referral to Treatment System to Reduce Risky Alcohol Use Among Emergency Department Patients.

BACKGROUND: Computer technologies hold promise for implementing alcohol screening, brief intervention, and referral to treatment (SBIRT). Questions concerning the most effective and appropriate SBIRT model remain. OBJECTIVE: The aim of this study was to evaluate the impact of a computerized SBIRT system called the Health Evaluation and Referral Assistant (HERA) on risky alcohol use treatment initiation. METHODS: Alcohol users (N=319) presenting to an emergency department (ED) were considered for enrollment. Those enrolled (n=212) were randomly assigned to the HERA, to complete a patient-administered assessment using a tablet computer, or a minimal-treatment control, and were followed for 3 months. Analyses compared alcohol treatment provider contact, treatment initiation, treatment completion, and alcohol use across condition using univariate comparisons, generalized estimating equations (GEEs), and post hoc chi-square analyses. RESULTS: HERA participants (n=212; control=115; intervention=97) did not differ between conditions on initial contact with an alcohol treatment provider, treatment initiation, treatment completion, or change in risky alcohol use behavior. Subanalyses indicated that HERA participants, who accepted a faxed referral, were more likely to initiate contact with a treatment provider and initiate treatment for risky alcohol use, but were not more likely to continue engaging in treatment, or to complete treatment and change risky alcohol use behavior over the 3-month period following the ED visit. CONCLUSIONS: The HERA promoted initial contact with an alcohol treatment provider and initiation of treatment for those who accepted the faxed referral, but it did not lead to reduced risky alcohol use behavior. Factors which may have limited the HERA's impact include lack of support for the intervention by clinical staff, the low intensity of the brief and stand-alone design of the intervention, and barriers related to patient follow-through, (eg, a lack of transportation or childcare, fees for services, or schedule conflicts). TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number (ISRCTN): NCT01153373; https://clinicaltrials.gov/ct2/show/NCT01153373 (Archived by WebCite at http://www.webcitation.org/6pHQEpuIF).

Synthesis of six-coordinate mono-, bis-, and tris(tetrazolato) complexes via [3 + 2] cycloadditions of nitriles to silicon-bound azido ligands.

A convenient synthetic route to poly(tetrazolato) silicon complexes is described based on the four reactive centres of the N-rich, highly endothermic tetraazides of the type Si(N3)4(L2). Hypercoordinate azido(tetrazolato) silicon complexes Si(N3)2(N4C-R)2(L2), R = CH3, C6H5, 4-C6H4CH3 (4a, 5, 6, 7) and Si(N3)2(N4C-L)2 (9, L = 2-C5H4N), L2 = 2,2'-bipyridine, 1,10-phenanthroline, with SiN6 skeletons were synthesised via multiple [3 + 2] dipolar cycloaddition reactions starting from Si(N3)4(L2) and a nitrile. The isolated new complexes were characterised by standard analytical methods, single crystal X-ray diffraction and differential scanning calorimetry (4a,b). Tetrazolato ligand linkage isomerism was observed for complex 4a. The crystallographically characterised methyl tetrazolato complexes and plausible configurational and linkage isomers were evaluated by DFT calculations at the B3LYP/6-311G(d,p) level.

Homoleptic Poly(nitrato) Complexes of Group 14 Stable at Ambient Conditions.

Using a novel approach in homoleptic nitrate chemistry, Sn(NO3)6(2-) (3c) as well as the previously unknown hexanitrato complexes Si(NO3)6(2-) (1c), Ge(NO3)6(2-) (2c) were synthesized from the element tetranitrates as salt-like compounds which were isolated and characterized using (1)H, (14)N, and (29)Si NMR and IR spectroscopies, elemental and thermal analyses, and single-crystal XRD. All hexanitrates are moderately air-sensitive at 298 K and possess greater thermal stability toward NO2 elimination than their charge-neutral tetranitrato congeners as solids and in solution. The complexes possess distorted octahedral coordination skeletons and adopt geometries that are highly symmetric (3c) or deformed (1c, 2c) depending on the degree of steric congestion of the ligand sphere. As opposed to the κ(2)O,O' coordination mode reported for Sn(NO3)4 previously,1 all nitrato ligands of 3c coordinate in κ(1)O mode. Six geometric isomers of E(NO3)6(2-) were identified as minima on the PES using DFT calculations at the B3LYP/6-311+G(d,p) level of which two were observed experimentally.