Acetabular morphometry and prevalence of hip dysplasia in the South Asian population

We carried out a cross-sectional study to measure the association of the seven acetabular parameters with pelvic morphometry and prevalence of hip dysplasia in our population. Convenience sampling was carried out and 250 consecutive patients who came to AKUH for intravenous pyelogram and had no complaints in the region of the hip joint were enrolled in the study. Post-micturition standardized plain antero-posterior pelvic radiographs of 250 asymptomatic adults (500 hip joints) was studied. There were 136 males (54.4%) and 114 females (45.6%). Mean age of our study population was 38 years (15-78 years). The average center edge angle was 35.5±6.6° standard deviation (SD), acetabular angle was 37.76±4.37°, depth to width ratio was 0.31±4.6°, roof obliquity was 10.6±6.2°, extrusion index was 0.1±5.8, lateral subluxation 8.9±2.7 mm, and peak to edge distance 17±3.98 mm. There was significant influence (p\u3c0.05) of age in all angles except depth to width ratio. A total of seven hip joints (1.4%) were dysplastic with CE angle \u3c25° while four of the seven hips were severely dysplastic with CE angle \u3c20°. In the dysplastic group there was significant correlation (p\u3c0.05) of CE angle with acetabular angle, depth to width ratio, extrusion index and peak to edge distance. Prevalence of hip dysplasia was found to be very low in our population. These results are consistent with the findings of studies carried out in other Asian countries

Morphology of the proximal femur in a Pakistani population

Purpose: To measure the morphology of the proximal femur in a Pakistani population. Methods: Standardised anteroposterior pelvic radiographs of 116 male and 20 female healthy volunteers aged 20 to 50 (mean, 33) years were taken. Morphologic dimensions of the proximal femur were measured, including canal flare index (CFI), morphological cortical index (MCI), femoral head offset, femoral head diameter, and femoral head position. Results: Based on the CFI, 67% of the subjects had normal canal shapes (CFI, 3.0-4.7), whereas 1% and 33% of the subjects had stovepipe shapes (CFI,2.7). Conclusions: Morphology of the proximal femur in our study population differed significantly from those in western populations, indicating regional variation. It could also be due to the younger age of our population

Parametric analysis of turning HSLA steel under minimum quantity lubrication (MQL) and nanofluids-based minimum quantity lubrication (NF-MQL) : a concept of one-step sustainable machining

Abstract: The requirement of cost-effective and ecological production systems is crucial in the competitive market. In this regard, the focus is shifted towards sustainable and cleaner machining processes. Besides the clean technologies, effective parametric control is required for machining materials (such as High Strength Low Alloy Steels) specifically designed for high strength applications having superior physio-chemical properties. Therefore, the machinability complexities require optimized solutions to reduce temperature elevation and tooling costs and improve machining of these materials. Complying to the market needs, this research examines the effectiveness of nanofluid on tool life, wear mechanisms, surface roughness (Ra), surface morphology, and material removal rate (MRR) in turning of 30CrMnSiA (HSLA) using minimum quantity lubrication (MQL) and SiO2-H2O nanofluids (NF-MQL). A systematic investigation based on physical phenomena involved is carried out considering four process parameters (cutting speed (VC), feed rate (Fr), depth of cut (DOC), and mode of lubrication for machining. Fr is found as the vital parameter for surface roughness while MRR is highly influenced by DOC regardless of lubrication approach. One-step sustainability technique is applied, in which process variables used for roughing conditions are analogous to attain surface comparable to finished machining without compromising process efficiency and demonstrate its feasibility through optimal settings under NF-MQL. Multi-response optimization proved the NF-MQL machining condition as the best alternative which result in 28.34% and 5.09% improvements for surface roughness and MRR, respectively. Moreover, the use of SiO2 is recommended over MQL due to lower energy consumption, low tool wear, and better surface integrity, sustainable liquid, and related costs

Revealing the microstructure and mechanical attributes of pre-heated conditions for Gas Tungsten Arc Welded AISI 1045 steel joints

Gas tungsten arc welding (GTAW) is considered a well-established process in the manufacturing industry. Despite, certain challenges associated with high hardness of heat affected zone and cold cracking susceptibility of joints, are the main barriers for this process to be implemented successfully within high integrity structure. By using a combined procedure of experiments and modelling (response surface methodology (RSM) and multi-objective optimization: multi-objective genetic algorithm (MOGA)) allows obtaining good enhancement over uniform heating, cooling and the heat-affected zone which enable major progress in obtaining high quality welded parts. Therefore, this research study combines the experiments and modelling in a systematic manner considering for the first type the pre-heated treatment and without- pre-heating conditions of GTAW manufacturing. It leads to optimizing the process parameters of GTAW when manufacturing AISI 1045 medium carbon steel. The effects of critical parameters i.e. welding current: WC, welding speed: WS, and gas flow rate: GFR on the mechanical properties (ultimate tensile strength (UTS) and hardness) were investigated and evaluated against the microstructure of weld fracture. The multi-objective genetic algorithm corroborated with experimental observation enables to obtain a maximum UTS of approx. 625 MPa and hardness of 80.19 HRB for preheat condition. The results highlight an improvement in UTS of 0.2% to 6.7% and a decrease in hardness of 0.1% to 21.5% by implementing the preheating conditio

Genetic dissection of Ni toxicity in a spring wheat diversity panel by using 90 K SNP array

Excess Ni intake has harmful implications on human health, which include chronic bronchitis, reduced lung function, and cancer of lung and nasal sinuses. Like other toxic metals, higher Ni accumulation in grains leads to excess intake by humans when the contaminated grains are consumed as food. There is little information about the genetic factors that regulate Ni uptake in plants. To investigate genetic architecture of Ni uptake in leaf and translocation to grain, we performed a genome-wide association study with genotyping from 90 K array in a historical bread wheat diversity panel from Pakistan. We observed that Ni toxicity caused more than 50 % reductions in biological yield and grain yield, other agronomic traits were also partly or severely affected. Genetic association study helped identify 23 SNP-trait associations involved in Ni uptake in leaf and translocation to grains. These 23 SNPs covered 15 genomic loci at chromosomes 1A, 2D, 3B, 4A and 4B of wheat. The favorable alleles of these SNPs were randomly distributed in subpopulations indicating no selection pressure for this trait during breeding improvement. These regions had 283 low-confidence and 248 high-confidence protein coding genes. Among these, 156 were annotated using databases of wheat and closely related grass species. Since there is no previous report on genetic information of Ni uptake and translocation, these results provide sufficient grounds for further research of candidate genes and varietal development.Peer reviewe

A Detailed Testing Procedure of Numerical Differential Protection Relay for EHV Auto Transformer

Abstract: In power systems, the programmable numerical differential relays are widely used for the protection of generators, bus bars, transformers, shunt reactors, and transmission lines. Retrofitting of relays is the need of the hour because lack of proper testing techniques and misunderstanding of vital procedures may result in under performance of the overall protection system. Lack of relay’s proper testing provokes an unpredictability in its behavior, that may prompt tripping of a healthy power system. Therefore, the main contribution of the paper is to prepare a step-by-step comprehensive procedural guideline for practical implementation of relay testing procedures and a detailed insight analysis of relay’s settings for the protection of an Extra High Voltage (EHV) auto transformer. The experimental results are scrutinized to document a detailed theoretical and technical analysis. Moreover, the paper also covers shortcomings of existing literature by documenting specialized literature that covers all aspects of protection relays, i.e., from basics of electromechanical domain to the technicalities of the numerical differential relay covering its detailed testing from different reputed manufacturers. A secondary injection relay test set is used for detailed testing of differential relay under test, and the S1 Agile software is used for protection relay settings, configuration modification, and detailed analysis

Intrusion Detection Framework for the Internet of Things Using a Dense Random Neural Network

The Internet of Things (IoT) devices, networks, and applications have become an integral part of modern societies. Despite their social, economic, and industrial benefits, these devices and networks are frequently targeted by cybercriminals. Hence, IoT applications and networks demand lightweight, fast, and flexible security solutions to overcome these challenges. In this regard, artificial-intelligence-based solutions with Big Data analytics can produce promising results in the field of cybersecurity. This article proposes a lightweight dense random neural network (DnRaNN) for intrusion detection in the IoT. The proposed scheme is well suited for implementation in resource-constrained IoT networks due to its inherent improved generalization capabilities and distributed nature. The suggested model was evaluated by conducting extensive experiments on a new generation IoT security dataset ToN_IoT. All the experiments were conducted under different hyperparameters and the efficiency of the proposed DnRaNN was evaluated through multiple performance metrics. The findings of the proposed study provide recommendations and insights in binary class and multiclass scenarios. The proposed DnRaNN model attained attack detection accuracy of 99.14% and 99.05% for binary class and multiclass classifications, respectively

Skeletal Plasmacytoma: Progression of disease and impact of local treatment; an analysis of SEER database

<p>Abstract</p> <p>Background</p> <p>Previous reports suggest an as yet unidentifiable subset of patients with plasmacytoma will progress to myeloma. The current study sought to establish the risk of developing myeloma and determine the prognostic factors affecting the progression of disease.</p> <p>Methods</p> <p>Patients with plasmacytoma diagnosed between 1973 and 2005 were identified in the SEER database(1164 patients). Patient demographics and clinical characteristics, treatment(s), cause of death, and survival were extracted. Kaplan-Meier, log-rank, and Cox regression were used to analyze prognostic factors.</p> <p>Results</p> <p>The five year survival among patients initially diagnosed with plasmacytoma that later progressed to multiple myeloma and those initially diagnosed with multiple myeloma were almost identical (25% and 23%; respectively). Five year survival for patients with plasmacytoma that did not progress to multiple myeloma was significantly better (72%). Age > 60 years was the only factor that correlated with progression of disease (p = 0.027).</p> <p>Discussion</p> <p>Plasmacytoma consists of two cohorts of patients with different overall survival; those patients that do not progress to systemic disease and those that develop myeloma. Age > 60 years is associated with disease progression. Identifying patients with systemic disease early in the treatment will permit aggressive and novel treatment strategies to be implemented.</p

Matrix Metalloproteinase 1: Role in Sarcoma Biology

In carcinomas stromal cells participate in cancer progression by producing proteases such as MMPs. The expression MMP1 is a prognostic factor in human chondrosarcoma, however the role in tumor progression is unknown. Laser capture microdissection and In Situ hybridization were used to determine cellular origin of MMP1 in human sarcomas. A xenogenic model of tumor progression was then used and mice were divided in two groups: each harboring either the control or a stably MMP1 silenced cell line. Animals were sacrificed; the neovascularization, primary tumor volumes, and metastatic burden were assessed. LCM and RNA-ISH analysis revealed MMP1 expression was predominantly localized to the tumor cells in all samples of sarcoma (p = 0.05). The percentage lung metastatic volume at 5 weeks (p = 0.08) and number of spontaneous deaths secondary to systemic tumor burden were lower in MMP1 silenced cell bearing mice. Interestingly, this group also demonstrated a larger primary tumor size (p<0.04) and increased angiogenesis (p<0.01). These findings were found to be consistent when experiment was repeated using a second independent MMP1 silencing sequence. Prior clinical trials employing MMP1 inhibitors failed because of a poor understanding of the role of MMPs in tumor progression. The current findings indicating tumor cell production of MMP1 by sarcoma cells is novel and highlights the fundamental differences in MMP biology between carcinomas and sarcomas. The results also emphasize the complex roles of MMP in tumor progression of sarcomas. Not only does metastasis seem to be affected by MMP1 silencing, but also local tumor growth and angiogenesis are affected inversely