Simulation-based decision-making system for optimal mine production plan selection

Price uncertainty is one of the major uncertainties in the life of mine (LOM) planning process which can have a decisive effect on the overall profitability. Today’s mine planning software tools provide block-sequencing optimisation for a given static price assumption that is then used as a basis of managerial decision-making process. This paper proposes a complementary approach to this by introducing a simulation-based decision-making tool that, with the help of simulation, seeks for the optimal mine plan when a managerially estimated price development with minimum and maximum boundaries is used as a data input for the given period. To demonstrate the approach, a realistic gold mine case study is presented with five alternative and technically feasible mine plans calculated in a static optimiser from a commercial mine planning software package. These mine planning scenarios are then subjected to price uncertainty in simulation with and without a price trend assumption to highlight the effect of price on the mine’s expected performance. Based on the results, we derive and demonstrate a simulation-based system that automates the matching of optimal mine plan with the managerial insight of long-term price development.

Benefits and Challenges of SAAS CRM Over On-Premise CRM: A Review

No matter whatever that you may sell, managing your customers is important for the success of your business. This is where exactly choosing a CRM (Customer Relationship Management) comes into play. Choosing the best CRM system for your organization requires identifying your objectives and determining the main customer management problems that you need to resolve by adopting a CRM for your businesses. When looking for CRM (Customer Relationship Management) or ERP (Enterprise Resource Planning) software, you will find that there are different ways of implementation, including onpremise and SaaS aka software as a service. Both types can help take your business to new heights, but it is up to you to decide which type works best for you. So in this paper we are going to compare on-premise and SaaS CRM and will also look at the challenges faced by SaaS CRM. Keywords: CRM, On-Premise, SaaS, Cloud Computing, Cloud Services.

Prevalence of favourable anatomy for palatal emergence of an immediate implant in the maxillary central incisor post-extraction site.

The purpose of this study was to determine the prevalence of favourable anatomy for palatal emergence of an immediate flapless implant in the maxillary central incisor post-extraction site. Implants were virtually placed into maxillary central incisor sites using 3D implant planning software. Following a strict implant placement criteria to keep a safety distance to the buccal plate and other anatomical structures, sockets where assessed to determine their suitability for a palatally emerging implant. From 321 patients included in this study, 62.3% presented a suitable socket anatomy for an immediate implant to be placed with the angulation for a screw retained crown. In 29% of the cases, the implants had to be labially tilted to keep a minimum distance to the buccal plate. 8.7% were unsuitable for immediate implants due to anatomic limitations. The position and angulation for an implant in the maxillary central incisor socket should be carefully assessed preoperatively with 3D images, as many sites will not be candidates for a palatal emergence and thus, a screw retained restoration.

Integrating Synthetic Accessibility with AI-based Generative Drug Design

Generative models are frequently used for de novo design in drug discovery projects to propose new molecules. However, the question of whether or not the generated molecules can be synthesized is not systematically taken into account during generation, even though being able to synthesize the generated molecules is a fundamental requirement for such methods to be useful in practice. Methods have been developed to estimate molecule synthesizability, but, so far, there is no consensus on whether or not a molecule is synthesizable. In this paper we introduce the Retro-Score (RScore), which computes a synthetic feasibility score of molecules by performing a full retrosynthetic analysis through our data-driven synthetic planning software Spaya, and its dedicated API: Spaya-API (https://spaya.ai). After a comparison of RScore with other synthetic scores from the literature, we describe a pipeline to generate molecules that validate a list of targets while still being easy to synthesize. We further this idea by performing experiments comparing molecular generator outputs across a range of constraints and conditions. We show that the RScore can be learned by a Neural Network, which leads to a new score: RSPred. We demonstrate that using the RScore or RSPred as a constraint during molecular generation enables to obtain more synthesizable solutions, with higher diversity. The open-source Python code containing all the scores and the experiments can be found on https://github.com/iktos/generation-under-synthetic- constraint.

Integrating Synthetic Accessibility with AI-based Generative Drug Design

Generative models are frequently used for de novo design in drug discovery projects to propose new molecules. However, the question of whether or not the generated molecules can be synthesized is not systematically taken into account during generation, even though being able to synthesize the generated molecules is a fundamental requirement for such methods to be useful in practice. Methods have been developed to estimate molecule synthesizability, but, so far, there is no consensus on whether or not a molecule is synthesizable. In this paper we introduce the Retro-Score (RScore), which computes a synthetic feasibility score of molecules by performing a full retrosynthetic analysis through our data-driven synthetic planning software Spaya, and its dedicated API: Spaya-API (https://spaya.ai). After a comparison of RScore with other synthetic scores from the literature, we describe a pipeline to generate molecules that validate a list of targets while still being easy to synthesize. We further this idea by performing experiments comparing molecular generator outputs across a range of constraints and conditions. We show that the RScore can be learned by a Neural Network, which leads to a new score: RSPred. We demonstrate that using the RScore or RSPred as a constraint during molecular generation enables to obtain more synthesizable solutions, with higher diversity. The open-source Python code containing all the scores and the experiments can be found on https://github.com/iktos/generation-under-synthetic- constraint.

The Green Paths route planning software for exposure-optimised travel

Green Paths is a prototype of route planning software for finding exposure-optimised routes for active travel. It incorporates external data on environmental exposures, including traffic noise levels, air quality, and street-level greenery into the street and paths network produced by the OpenStreetMap project. Written in the Python programming language, the software applies a novel environmental impedance function in the least cost path routing to find exposure-optimised routes. Routes for externally defined origin-destination pairs can be queried via a RESTful API. The API returns alternative routes equipped with rich exposure data. The published version of the software has been applied in population level environmental exposure assessment and in an end-user-oriented web-based route planner application designed for use in the Helsinki Metropolitan Area.

A Comparative Analysis of the Piezoelectric Ultrasonic Appliance and Trephine Bur for Apical Location: An In Vitro Study

To compare and contrast the accuracy of piezoelectric ultrasonic insert (PUI) and trephine bur (TB) osteotomy site preparation techniques for apical location. (1) Material and methods: A total of 138 osteotomy site preparations were randomly distributed into one of two study groups. Group A: TB technique (n = 69) and B: PUI technique (n = 69). A preoperative cone-beam computed tomography scan and an intraoral scan were performed and uploaded to implant-planning software to plan the virtual osteotomy site preparations for apical location. Subsequently, the osteotomy site preparations were performed in the experimental models with both osteotomy site preparation techniques and a postoperative CBCT scan was performed and uploaded into the implant-planning software and matched with the virtually planned osteotomy site preparations to measure the deviation angle and horizontal deviation as captured at the coronal entry point and apical end-point between osteotomy site preparations using Student’s t-test statistical analysis. (2) Results: The paired t-test found statistically significant differences at the coronal entry-point deviations (p = 0.0104) and apical end-point deviations (p = 0.0104) between the TB and PUI study groups; however, no statistically significant differences were found in the angular deviations (p = 0.309) between the trephine bur and piezoelectric ultrasonic insert study groups. (3) Conclusions: The results showed that the TB is more accurate than the PUI for apical location.