This paper presents an approach to the Timoshenko beam theory (TBT) using the finite difference method (FDM). The Timoshenko beam theory covers cases associated with small deflections based on shear deformation and rotary inertia considerations. The FDM is an approximate method for solving problems described with differential equations. It does not involve solving differential equations; equations are formulated with values at selected points of the structure. In addition, the boundary conditions and not the governing equations are applied at the beam’s ends. The model developed in this paper consisted of formulating differential equations with finite differences and introducing additional points at the beam’s ends and at positions of discontinuity (concentrated loads or moments, supports, hinges, springs, brutal change of stiffness, spring-mass system, etc.). The introduction of additional points allowed us to apply the governing equations at the beam’s ends. Moreover, grid points with variable spacing were considered, the grid being uniform within beam segments. First-order, second-order, and vibration analyses of structures were conducted with this model. Furthermore, tapered beams were analyzed (element stiffness matrix, second-order analysis, vibration analysis). Finally, a direct time integration method (DTIM) was presented; the FDM-based DTIM enabled the analysis of forced vibration of structures, with damping taken into account. The results obtained in this paper showed good agreement with those of other studies, and the accuracy was increased through a grid refinement. Especially in the first-order analysis of uniform beams, the results were exact for uniformly distributed and concentrated loads regardless of the grid.

The early embryonic heart is a multi-layered tube consisting of (1) an outer myocardial tube; (2) an inner endocardial tube; and (3) an extracellular matrix layer interposed between myocardium and endocardium, called “cardiac jelly” (CJ). During the past decades, research on CJ has mainly focused on its molecular and cell biological aspects. This review focuses on the morphological and biomechanical aspects of CJ. Special attention is given to (1) the spatial distribution and fiber architecture of CJ; (2) the morphological dynamics of CJ during the cardiac cycle; and (3) the removal/remodeling of CJ during advanced heart looping stages, which leads to the formation of ventricular trabeculations and endocardial cushions. CJ acts as a hydraulic skeleton displaying striking structural and functional similarities with the mesoglea of jellyfish. CJ not only represents a filler substance, facilitating end-systolic occlusion of the embryonic heart lumen. Its elastic components antagonize the systolic deformations of the heart wall and thereby power the refilling phase of the ventricular tube. Non-uniform spatial distribution of CJ generates non-circular cross sections of the opened endocardial tube (initially elliptic, later deltoid), which seem to be advantageous for valveless pumping. Endocardial cushions arise from non-removed remnants of the original CJ.

The performance in terms of minimal Bayes’ error probability for detection of a high-dimensional random tensor is a fundamental under-studied difficult problem. In this work, we consider two Signal to Noise Ratio (SNR)-based detection problems of interest. Under the alternative hypothesis, i.e., for a non-zero SNR, the observed signals are either a noisy rank-R tensor admitting a Q-order Canonical Polyadic Decomposition (CPD) with large factors of size Nq  R, i.e, for 1  q  Q, where R, Nq ! ¥ with R1/q/Nq converge towards a finite constant or a noisy tensor admitting TucKer Decomposition (TKD) of multilinear (M1, . . . ,MQ)-rank with large factors of size Nq  Mq, i.e, for 1  q  Q, where Nq,Mq ! ¥ with Mq/Nq converge towards a finite constant. The detection of the random entries (coefficients) of the core tensor in the CPD/TKD is hard to study since the exact derivation of the error probability is mathematically intractable. To circumvent this technical difficulty, the Chernoff Upper Bound (CUB) for larger SNR and the Fisher information at low SNR are derived and studied, based on information geometry theory. The tightest CUB is reached for the value minimizing the error exponent, denoted by s?. In general, due to the asymmetry of the s-divergence, the Bhattacharyya Upper Bound (BUB) (that is, the Chernoff Information calculated at s? = 1/2) can not solve this problem effectively. As a consequence, we rely on a costly numerical optimization strategy to find s?. However, thanks to powerful random matrix theory tools, a simple analytical expression of s? is provided with respect to the Signal to Noise Ratio (SNR) in the two schemes considered. A main conclusion of this work is that the BUB is the tightest bound at low SNRs. This property is, however, no longer true for higher SNRs.

We discuss two queueing-inventory systems with catastrophes in the warehouse. Catastrophes occur according to Poisson process and upon arrival of a catastrophe all inventory in the system is instantly destroyed. But consumer customers in the system (in the server or in the buffer) continue still waiting for the replenishment of the stock. The arrivals of the consumer customers follow a Markovian Arrival Process (MAP) and they can be queued in an infinite buffer. Service time of a consumer customer follows a phase-type distribution. The system receives negative customers whose have Poisson flows to service facility and upon arrival of a negative customer one consumer customer is pushed out from the system, if any. One of two replenishment policies can be used in the system: either (s,S) or (s,Q). If upon arrival of the consumer customer, the inventory level is zero, then according to the Bernoulli scheme, this customer is either lost (lost sale scheme) or join the queue (backorder sale scheme). The system is formulated by a four-dimensional continuous-time Markov chain. Steady state distribution is obtained using the matrix-geometric method. A comprehensive numerical study is performed on the performance measures under various replenishment policies. Finally, an optimization study is presented.

Lately Silicon Carbide (SiC) and Galium Nitride (GaN) based high frequency power conversion has gained immense popularity which stems from relatively low switching energy, robustness to high temperature operation, wide-band gap and superior thermal limits. While this aspect inherently results in a high-density power stage design, the design of adjoining passive components, particularly magnetics, needs careful attention. This is especially true if the compatibility of core and winding options and their performance is limited with the use of higher switching frequency. In this regard, this paper presents a brief review of existent research conducted in materials, optimization and integration of magnetics for single and three phase applications, ranging from filters, resonant inductors to isolation transformers. Design knobs pertaining to medium voltage (MV) applications, low-voltage (LV) applications, e-mobility sector such as more electric aircrafts (MEAs) and electric vehicles (EVs) are discussed. Guidelines for magnetics design are summarized for each application with a projected roadmap on future trend for magnetics.

Examining the similarity of event environments or surroundings, more precisely settings, provides additional insight in analyzing event sequences as it provides information about the context and potential common factors that may have influenced them. This article proposes a new similarity measure for event setting sequences, which involve the space and time in which events occur. While similarity measures for spatiotemporal event sequences have been studied, the settings and setting sequences have not yet been studied. While modeling event setting sequences we consider spatial and temporal scales to define the bounds of the setting and incorporates dynamic variables alongside static variables. Using a matrix-based representation and an extended Jaccard index we developed new similarity measures that allow for the use of all variable data types. We successfully used these similarity measures coupled with other multivariate statistical analysis approaches in a case study involving setting sequences and pollution event sequences associated with the same monitoring stations, which validate the hypothesis that more similar spatial-temporal settings or setting sequences may generate more similar events or event sequences. In conclusion, these similarity measures have many potential real-world applications, and offer researchers a powerful tool for understanding different factors and their dynamics corresponding to occurrences of spatiotemporal event sequences.

This paper presents work done as part of a transformation effort towards a greener and more sustainable Aluminium manufacturing plant. The effort includes reducing the carbon footprint by minimising waste and increasing operational efficiency. The contribution of this work includes the reduction of waste through the implementation of autonomous, real-time quality measurement and classification at an Aluminium casthouse. Data is collected from the MV20/20 which uses ultrasound pulses to detect molten Aluminium inclusions, which degrade the quality of the metal and cause subsequent metal waste. The sensor measures cleanliness, inclusion counts and distributions from 20 - 160 microns. The contribution of this work is in the development of business analytics to implement condition-based monitoring through anomaly detection, and to classify inclusion types for samples that failed. For anomaly detection, multivariate K-Means and DBSCAN algorithms are compared as they have been proven to work in a wide range of datasets. For classification, a two-stage classifier is implemented. The first stage classifies the success or failure of the sample, while the second stage classifies the inclusion responsible for the failed sample. The algorithms considered include logistic regression, support vector machine, multi-layer perceptron and radial basis function network. The multi-layer perceptron offers the best performance using k-fold cross-validation, and is further tuned using grid search to explore the possibility of an even better performance. The results reveal that the model has achieved a global maximum in performance. Recommendations include the integration of additional sensor systems and the improvements in quality assurance practices.

Introduction: A plethora of biological molecules regulate chondrogenesis in the epiphyseal growth plate. Disruptions of quantity and function of these molecules can manifest clinically as stature abnormalities of various etiologies. Traditionally, the growth hormone/insulin-like growth factor 1 (IGF1) axis represents the etiological center of final stature attainment. Of note, little is known about the molecular events that dominate the growth of the craniofacial complex and its correlation with somatic stature. Aim: Given the paucity of the relevant data, this review discusses available information regarding potential applications of lateral cephalometric radiography as a potential clinical indicator of genetic short stature in children. Materials and Methods: A literature search was conducted in the PubMed electronic database using the key words: cephalometric analysis and short stature; cephalometric analysis and achondroplasia; cephalometric analysis and hypochondroplasia; cephalometric analysis and skeletal abnormalities; cephalometr* and SHOX; cephalometr* and CNP; cephalometr* and ACAN; cephalometr* and CNVs; cephalometr* and IHH; cephalometr* and FGFR3; cephalometr* and Noonan syndrome; cephalometr* and “Turner syndrome”; cephalometr* and achondroplasia. Results: In individuals with genetic syndromes causing short stature, linear growth of the craniofacial complex is confined, following the pattern of somatic short stature regardless of its etiology. The angular cephalometric measurements differ from the average height normal individuals and are suggestive of a posterior placement of the jaws and a vertical growth pattern of the face. Conclusion: The greater part of the existing literature regarding cephalometric measurements in short statured children with genetic syndromes provides qualitative data. Furthermore, cephalometric data for individuals affected with specific rare genetic conditions causing short stature, should be the focus of future studies. These quantitative data are required to potentially establish cut-off values to refer for genetic testing based on craniofacial phenotypes.

We describe a new approach for integrating multiple views of data into a common latent space using non-negative tensor factorization (NTF). This approach, which we refer to as the "Integrated Sources Model" (ISM), consists of two main steps: embedding and analysis. In the embedding step, each view is transformed into a matrix with common non-negative components. In the analysis step, the transformed views are combined into a tensor and decomposed using NTF. Noteworthy, ISM can be extended to process multi-view data sets with missing views. We illustrate the new approach using two examples: the UCI digit dataset and a public cell type gene signatures dataset, to show that multi-view clustering of digits or marker genes by their respective cell type is better achieved with ISM than with other latent space approaches. We also show how the non-negativity and sparsity of the ISM model components enable straightforward interpretations, in contrast to latent factors of mixed signs. Finally, we present potential applications to single-cell multi-omics and spatial mapping, including spatial imaging and spatial transcriptomics, and computational biology, which are currently under evaluation. ISM relies on state-of-the-art algorithms invoked via a simple workflow implemented in a Jupyter Python notebook.

High-Level Synthesis (HLS) tools have revolutionized FPGA application development by providing a more efficient and streamlined approach, significantly impacting digital design methodologies. Despite the capability of FPGAs to customize numerical representations in data paths, most HLS projects have focused on fixed-point precision, while floating-point representations remain limited to vendor-provided single, double, and half-precision formats. This paper proposes a customized floating-point library compatible with HLS to address these limitations. This library allows programmers to define the number of exponent and mantissa bits at compile time, providing greater flexibility and enabling the use of mixed precision. Moreover, this library includes optimized implementations of common components such as vector summation (VSUM), dot-product (DP), and matrix-vector multiplication (MVM). Results demonstrate that the proposed library reduces latency and resource utilization compared to vendor IP blocks, particularly in VSUM, DP, and MVM operations. For example, the MVM operation involving a 32x32 matrix, using vendor IP requires 22 clock cycles, whereas CuFP completes the same task in just 7 clock cycles, using approximately 60% fewer DSPs, 10% fewer LUTs, and 60% fewer FFs.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI–TOF MS) is a commonly used technique for analyzing large biomolecules. However, the utilization of organic matrices limits the small-molecule analysis because of the interferences in the low-mass region and reproducibility issues. To overcome these limitations, a surface-assisted laser desorption/ionization (SALDI), which utilizes nanostructured metallic surfaces, has been developed. Herein, a novel approach for SALDI–MS was proposed using nanoengineered gold shell with nanogaps on the silica core (SiO2@Au NGS), which is an emerging material due to its excellent heat-generating capabilities. The gold shell thickness was controlled by adjusting the concentration of gold precursor for the growth of gold nanoparticles. SALDI-MS measurements were performed on a layer formed by drop-casting a mixture of SiO2@Au NGS and analytes. At the optimized process, the gold shell thickness was observed to be 17.2 nm, which showed the highest absorbance. The ion desorption efficiency was confirmed with a survival yield upon fragmentation. Based on the enhanced SALDI capability, SiO2@Au NGS was utilized to detect various small molecules including amino acids, sugars, and flavonoids. The limits of detection, reproducibility, and salt tolerance of SiO2@Au NGS demonstrate its potential as an effective and reliable SALDI material for small-molecule analyses.

A model to predict the relative levels of respiratory and fecal-oral transmission potentials of coronaviruses (CoVs) by measuring the percentage of protein intrinsic disorder (PID) of the M (Membrane) and N (nucleoprotein) proteins in their outer and inner shells, respectively, was built before the MERS-CoV outbreak. Application of this model to the 2003 SARS-CoV indicated that this virus with M_PID = 8.6% and N_PID = 50.2% falls into group B, which consists of CoVs with intermediate levels of both fecal-oral and respiratory transmission potentials. Further validation of the model came with MERS-CoV (M_PID = 9%, N_PID = 44%) and SARS-CoV-2 (M_PID = 5.5%, N_PID = 48%) falling into the groups C and B, respectively. Group C contains CoVs with higher fecal-oral but lower respiratory transmission potentials. Unlike SARS-CoV, SARS-CoV-2 with M_PID = 5.5% has one of the hardest outer shells among CoVs. This shell hardness is believed to be responsible for high viral loads in the mucus and saliva making it more contagious than SARS-CoV. The hard shell is able to resist the anti-microbial enzymes in body fluids. Further searches have found that high rigidity of outer shell is characteristic for the CoVs of burrowing animals, such as rabbits (M_PID = 5.6%) and pangolins (M_PID = 5-6%), which are in contact with the buried feces. A closer inspection of pangolin-CoVs from 2017-19 reveals that these animals provided a unique window of opportunity for the entry of an attenuated SARS-CoV-2 precursor into the human population in 2017 or earlier, with the subsequent slow and silent spread as a mild cold that followed by its mutations into the current more virulent form. Evidence of this lies in the similarity of shell disorder and genetic proximity of the pangolin-CoVs to SARS-CoV-2 (~90%). A 2017 pangolin-CoV strain shows evidence of higher levels of attenuation and higher fecal-oral transmission associated with lower human infectivity via having lower N_PID (44.8%). Our shell disorder analysis also revealed that lower inner shell disorder is associated with the lesser virulence in a variety of viruses.

A model that predicts levels of coronavirus (CoV) respiratory/fecal-oral transmission potentials based on the outer shell hardness has been built using neural network (artificial intelligence, AI) analysis of the percentage of disorder (PID) in the nucleocapsid, N, and membrane, M, proteins of the inner and outer viral shells, respectively. Based mainly on the PID of N, SARS-CoV-2 is categorized as having intermediate levels of both respiratory and fecal oral transmission potential. Related to this, other studies have found strong positive correlations between virulence and inner shell disorder among numerous viruses, including Nipah, Ebola, and Dengue viruses. There is some evidence that this is also true for SARS-CoV-2 and SARS-CoV, which have N PIDs of 48% and 50%, and are characterized by case-fatality rates of 7.1% and 10.9%, respectively. The link between levels of respiratory transmission and virulence lies in viral load of body fluids and organ respectively. A virus can be infectious via respiratory modes only if the viral loads in saliva and mucus exceed certain minima. Likewise, a person may die, if the viral load is too high especially in viral organs. Inner shell proteins of viruses play important roles in the replication of viruses, and structural disorder enhances these roles by providing greater efficiency in protein-protein/DNA/RNA/lipid binding. This paper outlines a novel strategy in attenuating viruses involving comparison of disorder patterns of inner shells of related viruses to identify residues and regions that could be ideal for mutation. The M protein of SARS-CoV-2 has one of the lowest M PID values (6%) in its family, and therefore this virus has one of the hardest outer shells, which makes it resistant to antimicrobial enzymes in body fluid. While this is likely responsible for its contagiousness, the risks of creating an attenuated virus with a more disordered M are discussed.

As people grow a custom to effortless outdoor navigation there is a rising demand for similar possibility indoors as well. Unfortunately, indoor localization, being one of the necessary requirements for navigation, continues to be problem without a clear solution. In this article we are proposing a method for an indoor positioning system using a single image. This is made possible using small preprocessed database of images with known control points as the only preprocessing needed. Using feature detection with SIFT algorithm we can look through the database and find image which is the most similar to the image taken by user. Pair of images is then used to find coordinates of database image using PnP problem. Furthermore, projection and essential matrices are determined allowing for the user image localization ~ determining the position of the user in indoor environment. Benefits of this approach lies in the single image being the only input from user and no requirements for new onsite infrastructure and thus enables a simpler realization for the building management.

The classical Rotational Isomeric State (RIS) model, originally proposed by Flory, has been used to rationalize a wide range of physicochemical properties of neutral polymers. However, many weak polyelectrolytes of interest are able to regulate their charge depending on the conformational state of the bonds. Recently, it has been shown that the RIS model can be coupled with the Site Binding (SB) model, for which the ionizable sites can adopt two states: protonated or deprotonated. The resulting combined scheme, the SBRIS model, allows to analyse ionization and conformational equilibria on the same foot. In the present work this approach is extended to include pH-dependent electrostatic Long Range (LR) interactions, ubiquitous in weak polyelectrolytes at moderate and low ionic strengths. With this aim the original LR interactions are taken into account by defining effective Short Range (SR) and pH-dependent parameters, such as effective microscopic protonation constants and rotational bond energies. The new parameters are systematically calculated using variational methods. The machinery of statistical mechanics for SR interactions, including the powerful and fast transfer matrix methods, can then be applied. The resulting technique, to which we will refer as Local Effective Interaction Parameters (LEIP) method, is illustrated with a minimal model of a flexible linear polyelectrolyte containing only one type of rotating bonds. LEIP reproduces very well the pH dependence of the degree of protonation and bond probabilities obtained by semi-grand canonical Monte Carlo simulations, where LR interactions are taken explicitly into account. The reduction in the computational time in several orders of magnitude suggests that the LEIP technique could be useful in a range of areas involving linear weak polyelectrolytes, allowing direct fitting of the relevant physical parameters to the experimental quantities.

This paper presents an approach to the Euler-Bernoulli beam theory (EBBT) using the finite difference method (FDM). The EBBT covers the case of small deflections, and shear deformations are not considered. The FDM is an approximate method for solving problems described with differential equations. The FDM does not involve solving differential equations; equations are formulated with values at selected points of the structure. Generally, the finite difference approximations are derived based on fourth-order polynomial hypothesis (FOPH) and second-order polynomial hypothesis (SOPH) for the deflection curve; the FOPH is made for the fourth and third derivative of the deflection curve while the SOPH is made for its second and first derivative. In addition, the boundary conditions and not the governing equations are applied at the beam’s ends. In this paper, the FOPH was made for all of the derivatives of the deflection curve, and additional points were introduced at the beam’s ends and positions of discontinuity (concentrated loads or moments, supports, hinges, springs, etc.). The introduction of additional points allowed us to apply the governing equations at the beam’s ends and to satisfy the boundary and continuity conditions. Moreover, grid points with variable spacing were also considered, the grid being uniform within beam segments. First-order analysis, second-order analysis, and vibration analysis of structures were conducted with this model. Furthermore, tapered beams were analyzed (element stiffness matrix, second-order analysis). Finally, a direct time integration method (DTIM) was presented. The FDM-based DTIM enabled the analysis of forced vibration of structures, with damping taken into account. The results obtained in this paper showed good agreement with those of other studies, and the accuracy was increased through a grid refinement. Especially in the first-order analysis of uniform beams, the results were exact for uniformly distributed and concentrated loads regardless of the grid. Further research will be needed to investigate polynomial refinements (higher-order polynomials such as fifth-order, sixth-order…) of the deflection curve; the polynomial refinements aimed to increase the accuracy, whereby non-centered finite difference approximations at beam’s ends and positions of discontinuity would be used.

This study presents an exact solution to the free vibration analysis of a uniform Timoshenko beam, with a harmonic vibration being assumed. The Timoshenko beam theory covers cases associated with small deflections based on shear deformation and rotary inertia considerations. In this paper, a moment-shear force-circular frequency-curvature relationship was presented. The complete study was based on this relationship and closed-form expressions of efforts and deformations were derived. The free vibration response of single-span systems and spring-mass systems was analyzed; closed-form formulations of matrices expressing the boundary conditions were presented and the natural frequencies were determined by solving the eigenvalue problem. Systems with intermediate mass, spring, or spring-mass system were also analyzed. Furthermore, first-order dynamic stiffness matrices in local coordinates were derived. Finally, a second-order analysis of beams resting on an elastic Winkler foundation was conducted. The results obtained in this paper were in good agreement with those of other studies.

A novel stationary phase for affinity separations is presented. This material is based on sintered borosilicate glass readily available as semi-finished filter plates with defined porosity and surface area. The material shows fast binding kinetics and excellent long-term stability under real application conditions due to lacking macropores and high mechanical rigidity. The glass surface can be easily modified with standard organosilane chemistry to immobilize selective binders or other molecules used for biointeraction. In this paper, the manufacturing of the columns and their respective column holders by 3D printing is shown in detail. The model system protein A/IgG was chosen as an example to examine the properties of such monolithic columns under realistic application conditions. Several specifications, such as (dynamic) IgG capacity, pressure stability, long-term performance, productivity, non-specific binding, and peak shape, are presented. It could be shown that due to the very high separation speed, 250 mg antibody per hour and column can be collected, which surpasses the productivity of most standard columns of the same size. The total IgG capacity of the shown columns is around 4 mg (5.5 mg/mL), which is sufficient for most tasks in research laboratories. The cycle time of an IgG separation can be less than 1 minute. Due to the glass material's excellent pressure resistance, these columns are compatible with standard HPLC systems. This is usually not the case with standard affinity columns, limited to manual use or application in low-pressure systems. The use of a standard HPLC system also improves the ability for automation, which enables the purification of hundreds of cell supernatants in one day. The sharp peak shape of the elution leads to an enrichment effect, which might increase the concentration of IgG by a factor of 3. The final concentration of IgG can be around 7.5 mg/mL without the need for an additional nanofiltration step. The purity of the IgG was > 95% in one step and nearly 99% with a second polishing run.

Fatty acids (FAs) represent an important class of metabolites, impacting on membrane building blocks and cellular regulatory networks. In nature, prokaryotes are characterized with the most impressing FA structural diversity and the highest relative contents of free fatty acids (FFAs). Thereby, nitrogen-fixing bacteria (order Rhizobiales), often found in symbiosis with legumes, attract a special interest. Indeed, FAs impact on the structure of rhizobial nodulation factors, required for successful infection of plant root. Although the FA patterns can be addressed by GC- and LC-MS, these methods are time-consuming and suffer from compromised sensitivity, low stability of derivatives and artifacts. In contrast, MALDI-TOF-MS represents an excellent platform for high-efficient metabolite fingerprinting, also applicable to FFAs. Therefore, here we propose a simple and straightforward protocol for high-throughput relative quantification of FFAs in rhizobia by the combination of Langmuir technology and MALDI-TOF-MS, which is featured with high sensitivity, accuracy and precision of quantification. Here we propose a step by step procedure comprising rhizobia culturing, pre-cleaning, extraction, sample preparation, mass spectrometric analysis, data processing and post-processing. To demonstrate the analytical potential of the protocol we illustrate it by a case study – comparison the FFA metabolomes of two rhizobia species - Rhizobium leguminosarum and Sinorhizobium meliloti.

Objectives: Multicentric Osteolysis, Nodulosis, and Arthropathy (MONA) syndrome is a rare genetic skeletal dysplasia. Its diagnosis can be deceptively similar to childhood-onset genetic skeletal dysplasias and juvenile idiopathic arthritis. We aimed to report the syndrome’s clinical and radiologic features with emphasis on skeletal manifestations. And establish relevant phenotype-genotype correlations. Methods: We evaluated two boys, 4-and-7-years-old with MONA syndrome. Both patients had consanguineous parents. We verified the diagnosis by correlating the outcomes of clinical, radiologic and molecular analysis. We specifically evaluated the craniofacial morphology and clinical and radiographic skeletal abnormalities. We contextualized the resultant phenotype-genotype correlations to publications on MONA and its differential diagnosis. Results: Skeletal manifestations were the presenting symptoms and mostly restricted to hands and feet in terms of fixed extension deformity of the metacarpophalangeal and flexion deformity of the interphalangeal joints with extension deformity of big toes. There were arthritic symptoms in the older patient especially of the wrists and minute pathologic fractures. The skeletal radiographs showed osteopenia/dysplastic changes of hands and feet. Both patients had variants in the matrix metalloproteinase2 gene which conformed to phenotype of previously reported literature in one patient while the other had a novel variant which conformed to MONA phenotype. Craniofacial abnormalities were present. However, minimal extra-skeletal manifestations. Conclusion: Overall, there is an emerging distinctive skeletal pattern of involvement in terms of both clinical and radiographic features. This includes age of onset and location of presenting skeletal manifestations, chronological order of joint affection, longitudinal disease progression, specifics of skeletal radiographic pathology and craniofacial features. Nevertheless, physicians are cautioned against differential diagnosis of similar genetic skeletal dysplasias and juvenile idiopathic arthritis.

Formalism proofing general derivation, applying matrix properties operations, showing fundamental relationships with inner product to outer product has been advanced here. This general proof formalism has direct application with physics to quantify quantum density at micro scale level to time commutator at macro scale level. System of operator algebraic equations have been rigorously derived to obtain analytic solutions which are physically acceptable. Extended physics application will include metricizing towards unitarization to achieve gaging Hamiltonian mechanics to electromagnetic gravitational strong theory, towards grand unifying physics atomistic to astrophysics or vice versa via quantum relativistic general physics thereby patching to classical physics fields energy.

In the context of healthcare technology management (HTM) in Saudi Arabia and the Gulf region, this study addresses a significant gap by exploring both external and internal risk factors affecting HTM performance. Previous research has primarily focused on modeling or predicting failures in medical devices, mostly examining internal (endogenous) factors that impact device performance and the development of optimal service strategies. However, a comprehensive investigation of external (exogenous) factors has been notably absent. This research introduces a novel hierarchical risk management framework, designed to accommodate the broad array of healthcare technologies, not limited to medical devices. It significantly advances the field by thoroughly investigating and validating a comprehensive set of 53 risk factors and assessing their influence on HTM. Additionally, this study embraces the perspective of enterprise risk management (ERM) and expands it to identify and incorporate a wider range of risk factors, offering a more holistic and strategic approach to risk assessment in healthcare technology management. The findings reveal that several external and internal factors previously underexplored significantly impact HTM performance. Notably, the Fuzzy AHP survey identified “design risk” under facility and environmental risks as the highest risk for HTM in the region. Furthermore, the study reveals that three out of the top ten risks are related to “facility and internal environmental” factors, six are related to technological endogenous factors, and only one is related to managerial factors. This distribution underscores the critical areas for intervention and the need for robust facility and technology management strategies. In conclusion, this research not only fills a critical void by providing a robust framework for healthcare technology risk assessment but also broadens the scope of risk analysis to include a wider array of technologies, thereby enhancing the efficacy and safety of healthcare interventions in the region. Additionally, the proposed hierarchy provides insights into the underlying risk factors for healthcare technology management, with potential applications extending beyond the regional context to a global scale. Moreover, the equation we propose offers a novel perspective on the key risk factors involved in healthcare technology management, presenting insights with far-reaching implications applicable not only regionally but also on a global level. This framework also supports sustainability goals by encouraging the efficient and responsible utilization and management of healthcare technologies, essential for ensuring the long-term economic and environmental sustainability of medical technology use.

Prostate cancer (PC) is the second most diagnosed cancer among men. It was observed that early diagnosis of disease is highly beneficial for survival of cancer patients. Therefore, extension and increasing quality of life of PC patients can be achieved by broadening the Cancer Screening programs that are aimed at the identification of cancer manifestation in patients at earlier stages before they demonstrate well-understood signs of the disease. Therefore, there is an urgent need in standard, sensitive, robust, and commonly available screening and diagnosis tools for identification of early signs of cancer pathologies. In this respect, “Holy Grail” of cancer researchers and bioengineers for decades have been molecular sensing probes that would allow diagnosis, prognosis, and monitoring of cancer diseases by their interaction with cell-secreted and cellassociated PC biomarkers, e.g. PSA and PSMA correspondinly. At present, most PSA tests are performed at centralized laboratories using high throughput Total PSA immune analyzers which are suitable for dedicated laboratories and are not readily available for the broad health screening. Therefore, the current trend in detection of PC is developments of the portable biosensors for mobile laboratories and individual use. Phage display since its conception by George Smith in 1985 has emerged as a premier tool in molecular biology with widespread applications. This review describes how the paradigm of molecular evolution and phage display revolutionized the methods of early diagnosis and monitoring of PC.