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This study investigates the application of Machine Learning (ML) algorithms to classify human physical activities and detect different types of falls using smartphone sensor data. Smartphones equipped with various sensors offer new opportunities for healthcare and human activity monitoring, which are crucial for health and well-being, aligning with the United Nations' sustainable development goals (SDG). The study used the "Sensor Data Collector" Android application to collect smartphone sensor data. The data collection experiments involve ten healthy participants engaged in diverse physical activities and different fall events, utilizing accelerometers and gyroscope sensors. Different types of fall detection include forward, backward, left lateral, and right lateral fall, which are important from a seriousness of health point of view. Participants placed their smartphones in the front pocket of their trousers to ensure a fixed position during the data collection process. The collected datasets are preprocessed using a moving average filter to denoise and smoothen the data. Different statistical features and extracted and ML algorithms, namely Support Vector Machine (SVM), Random Forest (RF), Naive Bayes (NB), and K-Nearest Neighbors (KNN), are employed to create robust classifiers. SVM and RF performed exceptionally well in classifying normal physical activities, achieving a 99.09% accuracy. SVM excelled in daily walking activity classification with a 99.59% accuracy, while the K-NN model performed best for crucial different types of fall classification, achieving an accuracy of 85.71%. This research emphasizes the potential of ML models for accurate physical activity and various types of fall classification, expanding the horizons of smartphone-based healthcare applications and aligning with sustainable development goals. [ABSTRACT FROM AUTHOR]

In the present era, it is challenging for people to extract crucial information due to the ongoing evolution of textual data on the internet as well as in online resources. Thus, only a procedure known as Text Summarization (TS) can be used to acquire the required information. Therefore, the most common and practical method of summary is known as extractive text summarization, which involves selecting the most pertinent sentences from the original text material. In a relatively short period of time, it can gather the most priceless information. In order to extract the phrases that serve as a document's summary, this study applies scoring-based optimisation models employing Ant Colony Optimisation (ACO), Butterfly Optimisation (BO), and Particle Swarm Optimisation (PSO). The model is simulated on the DUC 2006 dataset, and the TOPSIS approach is used to validate the results for various DUC documents. The PSO-based summarizer, however, performs noticeably better than the other two summarizers based on rank. [ABSTRACT FROM AUTHOR]

Non-contact ultrasonic sensors are generally used for range measurement and object detection. In addition to the shape and size of the target object, the identification of the material types plays a vital role in robotic navigation and autonomous vehicle applications. Ultrasonic echo signals contain a significant amount of information and can be used to recognize and categorize different materials. Echo signals can help robots detect the obstacle's material on the path and comply with its behavior accordingly. The emergence of deep neural networks has shown great promise, offering cutting-edge performance for a wide range of signal-processing tasks. This work uses the non-contact ultrasonic echo signal from a set of materials (glass, wood, metal plate, sponge, and cloth) for classification. The main idea is to classify the materials using the embedded information of reflected echo signals. Hilbert transform is used to get the envelope from the raw echo ultrasonic signal. In this paper, a novel architecture for one-dimensional convolutional neural network (1D-CNN) has been proposed to accomplish the classification task. The CNN model takes raw echo signals as input to detect and classify materials accurately. The performance of the classifier model is evaluated using accuracy, precision, recall, and F1-score. The proposed 1D-CNN deep learning-based multi-class classifier model can classify the different types of materials with an accuracy of 96%, precision of 95%, recall of 95%, and F1-score of 95%. [ABSTRACT FROM AUTHOR]

Gesture recognition using WiFi sensing is an emerging and innovative approach that leverages the variations in WiFi signals caused by human hand movements to enable non-contact and intuitive human-computer interaction. The identification of the hand used to perform a gesture significantly impacts the channel state information (CSI) characteristics. It plays a crucial role in data analysis and interpretation. This paper presents a model for classifying the gesture and the hand with which it is performed. We use an Intel 5300 network interface card as a receiver and a commodity WiFi router to collect the CSI values. The CSI values are collected for six left-hand and six right-hand gestures (push left, push right, increase, decrease, stop, and next). The collected CSI values are pre-processed to find the CSI ratio among the sub-carriers. Then four different methods including proposed method are used for classifying the hand and the gesture. The four methods are (1) use of the Hampel filter, (2) use of CSI ratio only, (3) use of correlation matrix along with CSI ratio, and (4) proposed CSI ratio and interquartile distance based method. Then various machine learning techniques such as KNN, Decision trees, and SVM are used to classify the hand (right or left) used for signaling the gestures and the type of gestures. It is found that using the top 30 inter-quartile distance of the CSI-ratios corresponding to the CSI values of the sub-carriers while preserving their positions as the feature vector, the KNN machine learning model can classify the hand and gesture with approximately 99% accuracy for test data. Similar performance is also observed for other performance evaluation parameters like precision and recall. [ABSTRACT FROM AUTHOR]

Necrotizing fasciitis (NF) is a life-threatening infection and a surgical emergency. Not all clinicians have the experience or resources to detect NF in its early stages. To develop a diagnostic algorithm for primary care and emergency physicians to identify patients with possible NF, including an initial approach to triaging such individuals. Medline was searched to identify studies of validated algorithms for NF diagnosis and/or cohort or case series providing clinical and diagnostic features of NF. Candidate algorithms were validated via application to 3 published cases of initially misdiagnosed NF. We retrospectively reviewed NF cases between 2011 and 2022 at our center to validate our algorithm. The search yielded 540 articles; 109 were included following a review of abstracts. No published validated diagnostic algorithm was identified. Using the reported clinical and diagnostic features of NF, we generated an algorithm of the " 3Ds" of NF : D isproportionate pain, D ermatological findings, and D isorganized physiology. A larger number of Ds indicated a greater level of suspicion for NF and prioritization for urgent surgical consultation. In 3 published cases of missed NF, the 3Ds algorithm successfully identified all as having possible NF. On reviewing our cases, we identified 56 patients with NF during an 11 year period. 66% of whom had the 3Ds at their initial presentation. The 3Ds algorithm, a simple and easy-to-remember tool can be easily applied in a primary or emergency care setting, and may improve the early diagnosis of NF. Retrospective analysis of NF cases allows for validation of this algorithm. However, this algorithm requires prospective validation. [ABSTRACT FROM AUTHOR]

Vasopressors are traditionally avoided in microsurgery due to concerns about their effect on free flap survival. We examine the impact of intraoperative vasopressors on microsurgical outcomes in a large series of DIEP flap breast reconstructions. A retrospective chart review was performed of patients who underwent DIEP breast reconstruction between January 2010 and May 2020. Intraoperative and postoperative microsurgical outcomes were compared in patients who received vasopressors and those who did not. The study included 1102 women who underwent 1729 DIEP. 878 patients (79.7%) received intraoperative phenylephrine, ephedrine, or a combination of both. There was no significant difference in overall complications, intraoperative microvascular events, takebacks for microvascular complications, or partial or total flap loss between groups. Outcomes were not affected by vasopressor type, dose, or timing of administration. The vasopressor group received significantly lower intraoperative fluid volumes. Multivariate logistic regression found a significant association between overall complications and excessive fluids (OR 2.03, 99% CI 0.98–5.18, p = 0.03) but not vasopressor use (OR 0.79, 99% CI 0.64–3.16, p = 0.7) This study demonstrates that vasopressors do not adversely affect clinical outcomes after DIEP breast reconstruction. Withholding vasopressors results in excessive intravenous fluid administration and increased postoperative complications. [ABSTRACT FROM AUTHOR]

To elicit a patient-prioritized agenda and preferences for upper extremity lymphedema (LE) research. Focus group sessions (FGs) were conducted with English-speaking, adult women (18 years and older) with breast cancer-related LE (BCRL) seeking conservative or surgical care at two tertiary cancer centers in Ontario, Canada. An interview guide was used; women were asked to describe health-related quality of life (HRQL) outcomes that mattered the most to them, followed by their preferences for research study design and for providing patient-reported outcomes measure (PROM) data. Inductive content analysis was used to identify themes and subthemes. A total of 16 women participated in 4 FG sessions (55 ± 9.5 years) and described the impact of LE on their appearance, physical, psychosocial, and sexual well-being. Women emphasized that psychosocial well-being was often not discussed in clinical care and that they were poorly informed of LE risk and care options. Most women said that they would not be willing to be randomized to surgical versus conservative management of LE. They also expressed a preference to complete PROM data electronically. All women emphasized the value of having an open text option alongside PROMs to expand on their concerns. Patient centeredness is key to generating meaningful data and ensuring ongoing engagement in clinical research. In LE, comprehensive PROMs that measure a range of HRQL concerns, especially psychosocial well-being, should be considered. Women with BCRL are reluctant to be randomized to conservative care when a surgical option is available, resulting in implications for planning trial sample size and recruitment. [ABSTRACT FROM AUTHOR]

The acoustic and prosodic characteristics of speech exhibit alterations when individuals are affected by different health conditions. The field of biomedical engineering holds significant potential in the advancement of non-invasive diagnostic systems that utilize voice as a modality. The common cold is an infectious sickness that affects a large number of people all over the world each year. This paper presents the utilization of various spectral features and a transformer-based model with focal loss function for classifying cold-affected and healthy speech signals. A spectral feature consisting of Mel frequency cepstral coefficients (MFCC), Mel-spectrogram, chromagram, spectral contrast, spectral centroid, spectral bandwidth, spectral flatness, and spectral roll-off features. The efficacy of the proposed methodology is assessed using the URTIC database. The findings indicate that the proposed framework has better results compared to existing state-of-the-art approaches. We have achieved the UAR of 69.55% on the develop set and 70.48% on the test set of the URTIC database. These preliminary findings exhibit significant potential for future investigation in this domain. • A non-invasive diagnostic methodology for detecting the common cold through the analysis of speech signals. • The fusion of various spectral features for depicting distinct speech patterns observed in people suffering from a common cold. • Development of the state-of-the-art deep neural network-based transformer model for cold speech classification. • The optimization of transformer architecture using focal loss function to address the issue of imbalanced classes. • The proposed framework achieved the UAR of 69.55% on the develop set and 70.48% on the test set of the URTIC database. [ABSTRACT FROM AUTHOR]

Automated speech emotion recognition (SER) has been gaining popularity among researchers for three decades because of its vast number of applications in the real world. It is helpful to improve the relationship between humans and machines, online marketing and education, customer relations, medical treatment, safe driving, online search, etc. Researchers adopt various methods to improve emotion recognition performance from speech signals, like using different combinations of features (acoustic, non-acoustic, or both), classifiers (machine learning, deep learning, or both). Our study tried to improve emotion classification performance using features based on the multi-resolution variational mode decomposition (MRVMD) method. We first decompose each signal frame into several sub-signals known as modes or intrinsic mode functions (IMFs) using the MRVMD method. Then the proposed features, multi-resolution variational mode mel-frequency cepstral coefficient (MRVMMFCC), multi-resolution variational mode approximate entropy (MRVMAE), and multi-resolution variational mode permutation entropy (MRVMPE), were extracted using the MRVMD-decomposed IMF signals. Finally, different combinations of the proposed features are used to classify the emotion using a deep neural network (DNN) classifier. From the experimental results, we found that combination of the proposed feature (MRVMMFCC + MRVMAE + MRVMPE) performs better than the other combination in recognizing emotion using speech signals. The proposed feature combination with a DNN classifier achieved an emotion classification accuracy of 83.4%, 85.01%, and 90.51% for the SAVEE, EMOVO, and EMO-DB datasets, respectively. We found that the proposed MRVMD method performed better than the state-of-the-art methods. • Decomposition of the speech signal into many frequency bands using the MRVMD method. • Proposal of MRVMD-based features such as MRVMMFCC, MRVMAE, and MRVMPE for SER. • Performance analysis of the proposed MRVMD-based features for SER using a DNN classifier. • The proposed method outperformed the state-of-the-art methods. • We obtained SER of 90.51%, 83.4%, and 85.01% for the EMODB, SAVEE, and EMOVO datasets. [ABSTRACT FROM AUTHOR]

Device-centric architecture is an important aspect for fifth generation (5G) networks. The current cellular systems are base station-centric where the base-station (BS) is responsible for resource allocation. The BS allocates resources to users based on their channel state information (CSI) and feedback. This resource allocation process increases load at the BS side resulting in more time consumption. This decreases the overall network throughput and increases delay in resource allocation. Therefore, in this article, a device-centric resource allocation scheme is proposed for D2D users. In this scheme, interested D2D pairs can allocate the resource to themselves using the following three steps. In first step, devices maintain their resource occupancy matrix by exchanging the neighbouring information. In second step, a resource block is selected based on resource allocation scenarios. In third steps, resource block is allocated based on the priority on the BS side. The proposed scheme is less dependent on the BS side, hence it reduces the load on BS side and it also reduces time consumption in resource allocation process. Additionally, the proposed scheme improves the overall network throughput. A comparison of the proposed scheme with the base-centric scheme shows that proposed scheme is up to 35% more effective in each experimental case. [ABSTRACT FROM AUTHOR]

Metals are micropollutants that cannot be degraded by microorganisms and are infiltrated into various environmental media, including both freshwater and marine water. Metals from polluted water are absorbed by many aquatic species, especially fish. Fish is a staple food in the diets of many regions in the world; hence, both the type and concentration of metals accumulated and transferred from contaminated water sources to fish must be determined and assessed. In this study, the heavy metal concentration was determined and assessed in fish collected from freshwater sources via published literature and Estimated Daily Intake (EDI), Target hazard quotient (THQ), and Carcinogenic Risk (CR) analyses, aiming to examine the metal pollution in freshwater fish. The fish was used as a bioindicator, and Geographic information system (GIS) was sued to map the polluted regions. The results confirmed that Pb was detected in fish sampled at 28 locations, Cr at 24 locations, Cu and Zn at 30 locations, with values Pb detected ranging from 0.0016 mg kg−1 to 44.3 mg kg−1, Cr detected ranging from 0.07 mg kg−1 to 27 mg kg−1, Cu detected ranging from 0.031 mg kg−1 to 35.54 mg kg-1, and Zn detected ranging from 0.242 mg kg−1 to 103.2 mg kg−1. The strongest positive associations were discovered between Cu–Zn (r = 0.74, p < 0.05) and Cr–Zn (r = 0.57, p < 0.05). Spatial distribution maps depicting the consumption of fish as food and its corresponding Pb and Cr intake revealed a higher incidence of both carcinogenic and non-carcinogenic health concerns attributed to Pb and Cr in the region with populations consuming the fish. [Display omitted] • Four heavy metals are abundantly found in five freshwater fish. • Lead and chromium levels are frequently above the acceptable threshold. • Non-carcinogenic and carcinogenic human health risk are assessed. • GIS mapping is used to examine cancer-causing and non-cancerous zones. [ABSTRACT FROM AUTHOR]

Pituicytoma is a rare low-grade glial neoplasm that originates in the distribution of the neurohypophysis, including the posterior pituitary lobe and infundibular stalk. The tumor cells resemble pituicytes, which are specialized glial cells of the neurohypophysis. Pituicytoma can be misdiagnosed pre-operatively as a pituitary adenoma due to overlapping clinical and neuroimaging features between these two entities. Pituicytoma can also mimic other neoplasms of the sellar and parasellar regions microscopically – meningioma, schwannoma and pilocytic astrocytoma – and shares immunohistochemical expression of TTF-1 with spindle cell oncocytoma and granular cell tumor of the sellar region, suggesting a common histogenesis. In this short review, we present the key features of pituicytoma, discuss commonalities and distinguishing features from other neoplasms of the sellar and parasellar regions and highlight the importance of recognizing this tumor entity for clinical and surgical management. [ABSTRACT FROM AUTHOR]

Developing speech signal-based non-invasive diagnosis techniques is an emerging research field in biomedical signal processing. Detecting the common cold and other illnesses with similar symptoms may be important to prevent the spread of these viral infections and remotely monitor patient health. This study aims to develop a method that achieves higher performance with fewer features to identify a subject with a common cold from their speech. The spectrum of cold and non-cold speech is distinct from one another. To capture these spectral variations, this study proposed three features: normalized harmonic peak with respect to the first harmonic peak (NHPF), normalized harmonic peak with respect to the maximum value of harmonic peak (NHPM), and successive harmonic peak ratio (SHPR). The NHPF and NHPM feature gives information about the relative magnitudes of all harmonics with respect to the first and maximum harmonics, respectively. The SHPR feature gives information on the relative harmonic magnitude with respect to the magnitude of its neighboring harmonic. The classifiers derive frame-level confidence scores for cold and non-cold classes. For utterance level categorization, confidence scores of all frames are summed, and a class with a higher confidence score is assigned to that utterance. The analysis shows that the proposed features effectively classify cold and non-cold speech. We achieved 69.16% and 66.90% UAR on the develop and test set of the URTIC database. The proposed features efficiently capture the spectral difference between cold and non-cold speech and can be utilized to automatically diagnose common cold and related disorders. • Proposal of NHPF, NHPM, and SHPR features to capture the spectral difference between cold and non-cold speech. • The proposed work is the first that utilized a sinusoidal model-based feature extraction method for diagnosing a common cold. • The effectiveness of the proposed NHPF, NHPM, and SHPR features has been revealed using a DNN and SVM classifier. • The NHPF feature achieves the highest UARs of 69.16% and 66.90% on the develop and test sets of the URTIC database. [ABSTRACT FROM AUTHOR]

Summary Introduction Microvascular complications can have devastating consequences in breast reconstruction. Because of the relatively low rate of complications, it can be difficult to identify significant predictors of failure. This study explores the importance of intraoperative microvascular problems in the development of postoperative complications and seeks to identify risk factors that may predict such events. Methods Three hundred and eighty-four patients undergoing 562 microvascular breast reconstructions were eligible for inclusion in this study. Bivariate and multivariate logistic regressions were performed to identify factors showing a significant association with intraoperative microvascular problems and postoperative microvascular complications. Results In multivariate logistic regression, intraoperative problems were an independent risk factor for the development of postoperative microvascular complications (odds ratio [OR] 2.7, 95% confidence interval [CI] 1.1–6.6, p = 0.02). Smoking was the only independent predictor of intraoperative events (OR 2.4, 95% CI 1.1–5.3, p = 0.03). While intraoperative problems are predisposed to postoperative microvascular complications in general, those that were thrombotic in nature could be corrected by early recognition and intraoperative revision in the majority of cases. Conclusions This study identifies intraoperative microvascular problems as significant predictors of postoperative complications in breast reconstruction. Smoking increases the rate of intraoperative problems, and although many can be corrected, preoperative smoking cessation may reduce the complexity of microsurgery and optimize postoperative outcomes. [ABSTRACT FROM AUTHOR]

The objective of the present research is to investigate the removal efficiency of As(V) from synthetic arsenic solution by Ce-Fe bimetal mixed oxide. The Ce-Fe bimetal mixed oxide is synthesized by solvothermal process and is characterized by using SEM, EDX, XRD, FTIR and BET. The analysis of SEM and BET analyser data of the material shows that particles are in the range of 290–300 nm, average pore size and surface area of the material is 4.42 nm and 127 m 2 /g respectively. Adsorption data are best fitted with the Langmuir isotherm with R 2 value of 0.9965. The maximum adsorption capacity is 32.12 mg/g at pH 3. Kinetics data revealed that the overall adsorption process followed pseudo-second-order kinetics. In the optimum conditions removal of As(V) using Ce-Fe bimetal mixed oxide is found to be 96%. The adsorption mechanism shows that the As(V) adsorption on the Ce-Fe bimetal mixed oxide is a complex mechanism including electrostatic attraction and the replacement of OH to form monodentate and bidentate complexes. The loaded adsorbent materials can be regenerated by using 0.5 M NaOH solution. [ABSTRACT FROM AUTHOR]

Sodium-glucose co-transporter-2 inhibitors (SGLT-2i) are associated with diabetic ketoacidosis (DKA), however limited case series are published. We evaluated the characteristics of patients admitted with SGLT-2i associated DKA. Over 4 months, 22 patients were identified; 45.5% of DKA was not associated with concurrent illness. DKA is not uncommonly associated with SGLT2i with no clear patient factors associated with severity. • Sodium-glucose co-transporter-2 inhibitor (SGLT-2i) associated DKA was observed in 22 patients over 4-months. • No differences in age, diabetes duration, HbA1c or admission biochemistry were seen in those with concurrent illness. • Our results observed no clear association between patient characteristics or co-morbidity and SGLT-2i-associated DKA. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of equalization of channels in a digital communication system. In the literature, artificial neural network (ANN) has been increasingly used for the said problem. However, traditional methods of ANN training fall short of desired performance in the problem of equalization. In this paper, we propose a recently proposed training method for ANN for the problem. This training uses directed search optimization (DSO) as a trainer to neural networks. Then, we apply the same to the problem of nonlinear channel equalization and in that way, this paper introduces a novel strategy for equalization of nonlinear channels. Proposed method of channel equalization performs better than contemporary equalization methods used in the literature, as evident from extensive simulation results presented in this paper. [ABSTRACT FROM AUTHOR]

The development of clonally related hematologic neoplasms in the setting of primary mediastinal germ cell tumors (PMGCTs) has been recognized previously and is associated with a dismal prognosis. However, the presentation of hematologic neoplasms as chronic myelomonocytic leukemia (CMML) and hemophagocytic lymphohistiocytosis (HLH) has been rarely reported. Here we report two patients with PMGCTs and hematologic neoplasms. The PMGCT was composed mostly of yolk sac tumor whereas the hematologic neoplasms had morphologic features that resembled CMML and HLH. The hematologic neoplasms from both patients harbored isochromosome 12p [i(12p)] and TP53 mutations, supporting a clonal relationship between these tumors. This association represents a unique clinical syndrome that likely contributes to the poor clinical outcome of these patients. • We report two patients with a primary mediastinal germ cell tumor (PMGCT) and a clonal related hematologic neoplasm. • The PMGCT was composed mostly of yolk sac tumor whereas the hematologic neoplasms resembling CMML) or HLH. • The molecular profile of the hematologic neoplasms was unlike their de novo counterparts, instead related to the PMGCT. • Patients with PMGCT and a hematologic neoplasm have a poor prognosis, likely related to TP53 mutation. [ABSTRACT FROM AUTHOR]

The present study highlights a multi response optimization approach to determine the optimal process parameters in wire electrical discharge machining process during taper cutting operation. Experiments have been conducted using six process parameters such as part thickness, taper angle, pulse duration, discharge current, wire speed and wire tension each at three levels for obtaining the responses like angular error, surface roughness, and cutting speed. Taguchi's L 27 orthogonal array is used to gather information regarding the process with less number of experimental runs. Traditional Taguchi approach is insufficient to solve a multi response optimization problem. In order to overcome this limitation, utility theory has been implemented, to convert multi-responses into single equivalent response called overall utility index. The weight for each criterion (response) is obtained by analytical hierarchy process (AHP) instead of using intuition and judgement of the decision maker. ANOVA analysis is also carried out to find out the significant effect of the process parameters during taper cutting in WEDM process. Finally confirmation test has been carried out to verify the result. [ABSTRACT FROM AUTHOR]

This paper highlights the parametric appraisal for burr height and circularity in drilling of hole on AISI-304 stainless steel using Non-dominated sorting genetic algorithm (NSGA). The major problem arises in drilling operation is the formation of burr and taper which seriously affect the quality of holes in practical applications. The present paper investigates the influence of drilling parameters viz., spindle speed, feed rate, and drill bit diameter on burr height and circularity. A total of twenty numbers of experiments were performed based on face centered central composite design (FCCD) of response surface methodology. Generally, the response surface methodology is used for modeling and analyzing manufacturing problems to understand the parametric effect on process responses individually, but it is unable to handle the multi-response problems. To overcome this limitation, proposed NSGA II is used for evaluation of optimal parametric combination in this study. The NSGA II is an improved approach of genetic algorithm (GA) for multi-objective optimization of process responses where non-dominated solutions having high crowding distance are used to provide diversified Pareto-optimal solutions. Analysis of variance shows that spindle speed significantly influence for the circularity of the drilled hole whereas all the parameters like spindle speed, feed rate and drill diameter influence on burr height. The optimal non-dominated set of solutions obtained through the NSGA II gives the manufacturer more flexibility in decision making in manufacturing process. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of digital IIR filter design. Two novel modifications are proposed to Particle Swarm Optimization and validated through novel application for design of IIR filter. First modification is based on quantum mechanics and proved to yield a better performance. The second modification is to take care of time dependency character of the constriction factor. Extensive simulation results validate the superior performance of proposed algorithms. [ABSTRACT FROM AUTHOR]

Background Despite their wide use in surgical audit, the application of the Physiologic and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) and the Portsmouth predictor of mortality (p-POSSUM) in bariatric surgery has been limited. The aim of this study was to evaluate the usefulness of POSSUM and p-POSSUM in bariatric comparative audit. Methods Data were retrospectively collected on consecutive patients who underwent laparoscopic gastric by-pass (LRYGB) and sleeve gastrectomy (SG) at a teaching institute. POSSUM and p-POSSUM equations were applied. The observed to expected ratios for morbidity and mortality were calculated. A Student’s t test was performed to assess if a relationship could be found between the observed and the predicted outcomes. Results Between 2008 and 2013, 504 patients (370 female) with a mean (range) age of 46 (17–69) years underwent LRYGB (n = 383) and SG (n = 121). The operative morbidity was 10.9% and mortality was .2%. POSSUM overpredicted morbidity (30.56%), and no relationship between morbidity risk and the development of complications was found ( P = .152). There was a grouping of patients in the low-risk mortality groups for both POSSUM and p-POSSUM. Both equations overpredicted mortality (5.95% and 1.62%, respectively). Conclusion Both POSSUM and p-POSSUM equations overpredicted morbidity and mortality in this only study in the literature of modern bariatric practice that employed a large representative patient sample receiving the commonest procedures. A multicenter study is needed to address the low incidence of events and enable modification of those equations for use in bariatric surgical audit. [ABSTRACT FROM AUTHOR]

Composite materials have been gaining immense importance in manufacturing industries, particularly in aerospace and automotive industries, due to their excellent properties as compared to other conventional metals. In manufacturing sector, drilling is a very common machining operation; whilst drilling of glass fiber reinforced polymer (GFRP) composite is substantially different from metallic materials due to delamination, fiber pull-out etc. In order to produce satisfactory product quality (GFRP drilled hole), investigations on machining and machinability aspects of GFRP composites are indeed essential. Understanding of the effect of process variables viz. drill speed, feed rate, drill diameter, plate thickness etc. is very important in order to select optimal machining condition towards improving overall machining performance. Therefore, this work focuses on the analysis of drill force (thrust), torque, surface roughness (R a ) and delamination behavior (of the drilled hole) as a function of drilling process parameters. The unified aim of this work is to determine an optimal machining environment based on the concept of the ‘Degree of Similarity Measure’ between each alternative and the ideal solution using alternative gradient and magnitude; TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and Deng's solution. [ABSTRACT FROM AUTHOR]

Drilling of glass fiber reinforced polymer (GFRP) composite material is substantially complicated from the metallic materials due to its high structural stiffness (of the composite) and low thermal conductivity of plastics. During drilling of GFRP composites, problems generally arise like fiber pull out, delamination, stress concentration, swelling, burr, splintering and micro cracking etc. which reduces overall machining performance. Now-a-days hybrid approaches have been received remarkable attention in order to model machining process behavior and to optimize machining performance towards subsequent improvement of both quality and productivity, simultaneously. In the present research, spindle speed, feed rate, plate thickness and drill bit diameter have been considered as input parameters; and the machining yield characteristics have been considered in terms of thrust and surface roughness (output responses) of the drilled composite product. The study illustrates the applicability of genetic programming with the help of GPTIPS as well as Adaptive Neuro Fuzzy Inference System (ANFIS) towards generating prediction models for better understanding of the process behavior and for improving process performances in drilling of GFRP composites. [ABSTRACT FROM AUTHOR]

This paper proposes an experimental investigation and optimization of the various machining parameters for the electrical discharge machining (EDM) processes on Inconel 718 super alloy using a multi objective particle swarm optimization (MOPSO) algorithm. A Box-Behnkin design of response surface methodology has been used to collect data for the study. The machining performances of the process are evaluated in terms of material removal rate (MRR) and surface quality which are functions of process variables such as open circuit voltage, discharge current, pulse-on-time, duty factor, flushing pressure and tool material. Mathematical model is developed relating responses with process variables. Finally, a MOPSO algorithm has been proposed for the multi objective optimization of the responses. [ABSTRACT FROM AUTHOR]

The efficacy of 1α,25-dihydroxyvitamin D3 (Vit-D) limits its topical use despite its profound effects on cellular differentiation, proliferation, and immunomodulation. Therefore, in search for a more effective analog of Vit-D, in this study we have evaluated the antiproliferative and proapoptotic effects of 1α,25-dihydroxyvitamin D3-3-bromoacetate (BE). Proliferation and apoptosis studies in normal human epidermal keratinocytes (NHEKs) were conducted by MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide), CFSE (carboxy fluorescein succinimidyl ester) dilution, and Annexin V assays. Western blot analysis and real-time PCR were performed to determine its effect on signal transduction. A reconstructed human epidermis (RHE) model was used to further validate the therapeutic role of BE in psoriasis. BE was significantly more potent than an equivalent concentration of Vit-D in inhibiting growth and survival of human keratinocytes. The antimitotic effect was found to be due to the inhibition of phosphorylation of serine/threonine protein kinase (AKT) and its downstream target, mammalian target of rapamycin (mTOR). In the RHE model, BE reversed IL-22-induced psoriasiform changes more effectively than Vit-D. Interestingly, BE inhibited the IL-22-induced gene expression of AKT1, MTOR, chemokines [IL-8 and RANTES (regulated upon activation, normal T-cell expressed and secreted)], and psoriasin (S100A7) more significantly than Vit-D. These results suggest the potential of BE as a prospective therapeutic agent for psoriasis. [ABSTRACT FROM AUTHOR]

Spectrum sensing is an important module in cognitive Radio (CR) technology. This paper presents a spectrum sensing technique based on entropy estimation of the received signal in frequency domain. This approach is extended for cooperative sensing using different fusion rules. Performance of the algorithm is analyzed using Monte-Carlo methods. The performance of proposed entropy based detection is compared with energy based detection technique. Simulation results reveal that, entropy based detection algorithm can detect signals of signal-to-noise ratio upto -24 dB using five nodes for detection probability Pd ≥ 0.9 and false alarm probability Pf ≤ 0.1. Sensing algorithm of single node is successfully implemented in Virtex4 FPGA. [ABSTRACT FROM AUTHOR]

Abstract: Fused deposition modelling (FDM) is gaining distinct advantage in manufacturing industries because of its ability to manufacture parts with complex shapes without any tooling requirement and human interface. The properties of FDM built parts exhibit high dependence on process parameters and can be improved by setting parameters at suitable levels. Anisotropic and brittle nature of build part makes it important to study the effect of process parameters to the resistance to compressive loading for enhancing service life of functional parts. Hence, the present work focuses on extensive study to understand the effect of five important parameters such as layer thickness, part build orientation, raster angle, raster width and air gap on the compressive stress of test specimen. The study not only provides insight into complex dependency of compressive stress on process parameters but also develops a statistically validated predictive equation. The equation is used to find optimal parameter setting through quantum-behaved particle swarm optimization (QPSO). As FDM process is a highly complex one and process parameters influence the responses in a non linear manner, compressive stress is predicted using artificial neural network (ANN) and is compared with predictive equation. [Copyright &y& Elsevier]

Abstract: This study proposes a novel Integrated Learning Particle Swarm Optimizer (ILPSO), for optimizing complex multimodal functions. The algorithm modifies the learning strategy of basic PSO to enhance the convergence and quality of solution. The ILPSO approach finds the diverged particles and accelerates them towards optimal solution. This novel study also introduces the particle’s updating strategy based on hyperspherical coordinates system. This is especially helpful in handling evenly distributed multiple minima. The proposed technique is integrated with comprehensive learning strategy to explore the solution effectively. The performance comparison is carried out against different high quality PSO variants on the set of standard benchmark functions with and without coordinate rotation and with asymmetric initialization. Proposed ILPSO algorithm is efficient in terms of convergence rate, solution accuracy, standard deviation, and computation time compared with other PSO variants. Friedman non-parametric statistical test followed by Dunn post analysis results indicate that the proposed ILPSO algorithm is an effective technique to optimize complex multimodal functions of higher dimension. [Copyright &y& Elsevier]

Objective: The aim of the study was to review the pathogenesis and the result of management of the intracranial complications of chronic middle ear suppuration. Methods: This was a retrospective review of charts of 32 cases with intracranial complications due to chronic middle ear infection managed between 1993 and 2007. The symptoms, clinical findings, and medical and surgical management were reviewed and analyzed. Results: There were 10 (31.2%) patients in the age group of 0 to 10 years, 9 (28.1%) patients in the age group of 11 to 18 years, and 13 (40.6%) patients older than 18 years. Males were involved twice as much as females. Among the 32 patients, 18 (56.3%) had a single intracranial complication, whereas 14 (43.7%) had multiple intracranial complications. Among all the intracranial complications in the 32 patients, otitic meningitis was the commonest intracranial complication and was seen in 14 (43.7%) patients; it was followed by lateral sinus thrombosis in 10 (31.2%), cerebellar abscess in 6 (18.7%), epidural abscess in 7 (21.8%), and perisinus abscess in 5 (15.6%). Other less common but serious intracranial complications encountered were cerebral abscess and interhemispheric abscess in 2 (6.2%) each, and subdural abscess, otitic hydrocephalus, and otogenic cavernous sinus thrombosis in 1 (3.1%) each. Upon admission, all patients received a combination of parenteral antibiotics. Canal wall down mastoidectomy was performed in all but 1 patient. In addition, lateral sinus was explored in 13 (40.6%) and cerebellar abscesses were drained in 5 (15.6%) patients. The overall mortality rate of 31.2% was found in our series. Conclusion: The prognosis was worse with delayed presentation because of overwhelming intracranial infection due to multiple pathways of extension from chronic otitis media. Infected thrombus in the dural venous sinus should be removed to prevent dissemination of septic emboli. [ABSTRACT FROM AUTHOR]

Abstract: Our investigation on macrophytes in Lake Qattieneh, a large, shallow reservoir in western Syria, is a first assessment of ecological status of this lake. We studied spatial distribution patterns of aquatic macrophyte vegetation and heavy metal concentrations to determine if they can be used as indicators of point sources of pollution. Industrial and municipal point sources at the lake shore increase nutrient load and contamination by heavy metals. Water analyses revealed high concentrations of some heavy metals at some littoral sites: Ni 88.7μgL−1, Cr 49.99μgL−1, Co 14.38μgL−1, and Cu 11.65μgL−1. Despite hypertrophic conditions and high heavy metal contamination, we recorded several submerged macrophyte species with heterogeneous spatial distribution patterns. Whereas Potamogeton pectinatus L. dominates in the eastern part of the lake, near industrial point sources, both Myriophyllum spicatum L. and Potamogeton lucens L. form extended patches in the western part of the lake. The shallow, littoral areas near villages are dominated by Ranunculus trichophyllus Chaix in Villars and Ceratophyllum demersum L. The west–east gradient in nutrient and heavy metal concentrations in waters and sediments are reflected by the spatial distribution of submersed species. While the heavy metal concentrations of the water body vary considerably in different seasons, the contents in submersed macrophytes integrate seasonal variations of longer time periods. Spatial distribution and tissue accumulation of littoral macrophyte species reflect the environmental conditions at respective sites such as heavy metal contents in water and sediment. [Copyright &y& Elsevier]

Abstract: Tumor necrosis factor α (TNF-α) inhibitors offer a targeted therapeutic strategy that contrasts with the nonspecific immunosuppressive agents traditionally used to treat most inflammatory diseases. These biologic agents have had a significant impact in ameliorating the signs and symptoms of inflammatory rheumatoid disease and improving patient function. From the onset of clinical trials, a central concern of cytokine blockade has been a potential increase in susceptibility to infections. Not surprisingly, a variety of infections have been reported in association with the use of TNF-α inhibitor agents. In particular, there is evidence suggesting an increased rate of granulomatous infections in patients treated with monoclonal TNF-α inhibitors. This review provides the incidence and nature of infections in patients treated with TNF-α inhibitor agents and reminds the clinician of the required vigilance in monitoring patients. [Copyright &y& Elsevier]

Abstract: In this paper the Modified Probabilistic Neural Network (MPNN) is used for dealing with the problem of channel equalization. Some improvements are suggested for the MPNN so that it is more suitable for the current problem. Firstly, the MPNN is extended to process complex signals. Secondly, a stochastic gradient adaptation technique is proposed, such that when the network is being employed to equalize a slowly varying channel, it can self-adapt to the changing environment. Simulations have shown that the MPNN is able to effectively equalize 4-QAM symbol sequences transmitted through a non-linear, slowly time-varying channel. Finally, methods that further reduce the size of the network are proposed. Simulations show that the proposed method is able to reduce the size of the network considerably. [Copyright &y& Elsevier]

The increasing use of social media and its ability to aid small and medium-sized enterprises (SMEs) to target large audiences at once has triggered to transformation in how SMEs perform their routine operations. Research on social media usage and SME performance is comparatively novel and patchy; yet, researchers, managers, and policymakers have limited interest in investigating the construct specifically in developing countries. This study explores the relationships between social media usage and innovation capabilities to improve sustainable SME performance. This study grounded the theoretical model building on a resource-based view. An online questionnaire was administered to gather data and was further analyzed quantitatively. The proposed interlinks were assessed using a sample of 549 employees of SMEs using SmartPLS techniques. The results show that social media usage has a positive and significant direct influence on innovation capabilities and sustainable SMEs performance, and innovation capabilities also have a positive and significant direct impact on sustainable SME performance. In addition, findings reveal that social media usage can enhance sustainable SME performance when mediated by innovation capabilities and moderated by digital leadership. This study offers several theoretical and practical implications. • The increasing use of social media's ability to lead SMEs to target large audiences has triggered to transformation in how SMEs perform their routine operations. • This study fills the limited interest in investigating the construct specifically in developing countries. • Social media usage can enhance sustainable SME performance when mediated by innovation capabilities and moderated by digital leadership. • This study offers several theoretical and practical implications for SMEs and relevant policy makers. [ABSTRACT FROM AUTHOR]

In psoriasis, CD28/B7 costimulatory molecules are well characterized. Here, using the severe combined immunodeficient (SCID) mouse-psoriasis xenograft model, we report therapeutic efficacy of a humanized anti-CD28 monoclonal antibody (FR255734; Astellas Pharmaceuticals Inc., Tokyo, Japan). Transplanted psoriasis plaques on the SCID mouse were treated weekly for 4 weeks with intraperitoneal injections of FR255734 at 10, 3, and 1-mg kg−1 doses. Groups treated with doses of 10 and 3 mg kg−1had significant thinning of the epidermis and reduced HLA-DR-positive lymphocytic infiltrates. The length of the rete pegs changed from 415.2±59.6 to 231.4±40.4 μm (P<0.005) in the 10-mg kg−1 group, and from 323.4±69.6 to 237.5±73.6 μm in the 3-mg kg−1 group (P=0.002). Positive controls treated with CTLA4-Ig and cyclosporine had significant histological improvement, whereas plaques treated with saline and isotype controls (human and mouse IgG2) remained unchanged. In vitro studies have shown that FR255734 effectively blocked T-cell proliferation and proinflammatory cytokine production. These observations warrant studies to evaluate the efficacy of FR255734 in human autoimmune diseases.Journal of Investigative Dermatology (2008) 128, 1969–1976; doi:10.1038/jid.2008.38; published online 13 March 2008 [ABSTRACT FROM AUTHOR]

Summary: Objectives: To investigate the brain inflammation and damage in subacute sclerosing panencephalitis (SSPE), the cerebrospinal fluid (CSF) concentrations of matrix metalloproteinase-9 (MMP-9) and tissue inhibitor of metalloproteinase-1 (TIMP-1) were determined in SSPE patients. Methods: CSF MMP-9 and TIMP-1 levels were measured in 23 patients with SSPE in Papua New Guinea by ELISA. Results: CSF MMP-9 levels and MMP-9/TIMP-1 ratios of SSPE patients were significantly higher than controls (p <0.001 and p =0.005, respectively). There were no significant differences in CSF TIMP-1 levels between SSPE patients and controls. Conclusions: Previous studies suggested that CSF MMP-9 levels reflect inflammatory damage to the brain. Our findings suggest that the MMP-9 level in CSF is an indicator of inflammatory damage to the brain in SSPE. [Copyright &y& Elsevier]

Summary: Objective: Sporadic acoustic neuroma, usually occur between the ages of 40 and 70 years, are very rare in children. We review the experiences of 10 cases of sporadic (non-NF2) acoustic neuromas in pediatric patients. Method: During last 26 years 2000 skull base procedures were performed in the Otorhinolaryngology Unit of the Ospedali Riuniti di Bergamo. Among these almost 900 cases were acoustic neuromas. Only 10 were at or under the age of 18 years. Results: The age of the youngest patient in our series was 12 years. Deafness were the commonest presentation and were seen in eight patients. It varied between 10 and 65dB sensorineural hearing loss. Among these eight cases, two patients have sudden onset of hearing loss. Two patients presented with dizziness. The duration of complaints were between 2 months and 5 years in these patients. The diameter of the tumors varied widely with minimum of 10mm to maximum up to 60mm. Five patients each underwent resection of the tumor by translabyrinthine and retrosigmoid approach, respectively. The minimum postoperative follow-up was 3 years and maximum was 22 years in our series. Postoperatively seven cases the facial nerve recovered to grade I, and one each to grade II and grade VI of House–Brackmann classification. All five cases who underwent retrosigmoid approach had moderate (40dB) to total sensorineural hearing loss postoperatively. The youngest patient with largest tumor diameter of 60mm developed transient hemiparesis in the immediate postoperative period and he recovered fully in due course. Conclusion: We found preservation of facial nerve function is more easier than hearing in this group of patients. [Copyright &y& Elsevier]

Laboratory and greenhouse experiments were conducted to evaluate the effects of farmyard manure (FYM), CaCO3 and single superphosphate (SSP) on retention and availability of Zn, Cu and Ni in sewage-irrigated soil. We also assessed the suitability of 0. 05M EDTA for predicting the effectiveness of these amendments in reducing the phytoavailability of metals. Results indicated that EDTA could successfully predict the phytoavailability of Zn and Ni in amended soil, whereas it failed in case of Cu. By and large, application of CaCO3, either alone or in combination with FYM had a positive effect on the retention of Zn, Cu and Ni in soil. Application of CaCO3 alone or in combination with FYM was equally effective in reducing the Zn content in lettuce, whereas sole application of CaCO3 significantly reduced Ni content. However, only SSP was found to be effective in reducing the Cu content in lettuce. [Copyright &y& Elsevier]

The peripheral nervous system, in addition to its sensory and motor functions, can induce a local inflammatory response known as neurogenic inflammation. This phenomenon plays a critical role in several inflammatory diseases, e.g., asthma, atopy, rheumatoid arthritis, psoriasis, and ulcerative colitis. Neurogenic inflammation and the role of nerve growth factor (NGF) have been extensively studied in psoriasis. There are increased levels of NGF in the keratinocytes and upregulation of NGF receptor (NGF-R) in the cutaneous nerves of psoriatic plaques. NGF can influence all the salient pathologic events noticed in psoriasis such as proliferation of keratinocytes, angiogenesis, T cell activation, expression of adhesion molecules, proliferation of cutaneous nerves, and upregulation of neuropeptides. In this double-blinded, placebo-controlled study, we addressed the role of NGF/NGF-R in psoriasis in an in vivo system using the severe combined immunodeficient (SCID) mouse–human skin model of psoriasis. The transplanted psoriatic plaques on the SCID mice (n=12) were treated with K252a, a high-affinity NGF receptor blocker. Psoriasis significantly improved following 2 wk of therapy. The length of the rete pegs changed from 308.57±98.72 to 164.64±46.78 μm (p<0.01, Student's t test). A similar improvement of psoriasis was observed by directly inhibiting NGF with NGF-neutralizing antibody. NGF-neutralizing antibody in normal saline at 10 ng (n=4) and 20 ng (n=4) per kilogram of body weight doses were used. Both doses of NGF-neutralizing antibody reduced rete peg lengths significantly, e.g., from 298.5±42.69 to 150.52±32.93 μm (p<0.05, Student's t test). This study provides evidence for the role of NGF and its high-affinity receptor in the pathogenesis of psoriasis and insights to develop novel therapeutic modalities. [ABSTRACT FROM AUTHOR]

In a wide range of contexts including military operations, environment monitoring, surveillance in border areas, health care, public safety [1, 2], disaster management, humanitarian relief and blood supply chain, a robust solution of the Covering Salesman Problem (CSP) is necessary. These applications require more than one facilities to cover a given customer (region of interest (ROI)). In this paper, we consider the coverage radius to be fixed and same for each node. Then we propose a multi-objective algorithm based on NSGA-II, in which minimization of tour length and maximization of number of nodes with 2-coverage are considered as the objectives. For implementing the algorithm, an individual chromosome is represented using a one-dimensional array with variable length, and developed a new crossover and a new mutation operator based on the problem and variable length chromosome representation. Numerical examples taken from TSP instances (TSPLIB [3]) with number of nodes ranging from 51 to 150 are solved using the algorithm. For each numerical example, the tour corresponding to the solution with 2-coverage of customer nodes is presented, which shows that the proposed algorithm is effective. Finally, a potential future research direction of this problem is discussed. [Display omitted] • Robust Covering Salesman Problem. • Modeled as multi-objective optimization problem (MOOP) and solved using NSGA-II. • Considered same radius for each node. • Minimizing tour length and maximizing 2-coverage are taken as the objectives. • Potential applications in military operations, environment monitoring, surveillance in border areas, health care, public safety. [ABSTRACT FROM AUTHOR]

B-prolymphocytic leukemia (B-PLL) is included as a distinct entity in the current World Health Organization classification of hematolymphoid neoplasms. However, the diagnosis of B-PLL has presented several challenges since its conception, and over the past decades investigations of B-PLL have revealed substantial biologic and molecular heterogeneity. These data have shown that many B-PLL cases present many similarities with other types of small B-cell lymphomas, and that small B-cell lymphomas can undergo prolymphocytoid transformation. As a result, the frequency of B-PLL has markedly decreased, and currently B-PLL is a very rare entity. Most recent studies focused on B-PLL cases have been conducted on limited cohorts, precluding robust conclusions. In this article, we provide a concise historical review of B-PLL and describe the diagnostic and clinical challenges associated with establishing this diagnosis. We also argue that cases currently classified as B-PLL are unlikely to be a unique biologic entity, but rather represent a state of morphologic transformation characterized by many prolymphocytes that is shared by various types of small B-cell lymphoma. • Many B-prolymphocytic leukemia (B-PLL) have similarities with other types of small B-cell lymphomas with prolymphocytoid transformation. • There is a substantial biologic and molecular heterogeneity of cases labeled as "B-PLL". • Cases currently classified as B-PLL likely represent a state of morphologic transformation shared by various types of small B-cell lymphomas. • The category of B-PLL would be better included in the chapters devoted to various types of small B-cell lymphomas as a form of disease transformation. [ABSTRACT FROM AUTHOR]

Abstract: Bayesian equalizer is known to be the optimum equalizer. This paper proposes a Hybrid Artificial Neural Network (Hybrid ANN) and an algorithm to modify Decision Feedback Equalizer (DFE) function of Bayesian equalizer while equalizing in presence of co-channel interference (CCI). A combination of Artificial Neural Network and Decision Feedback Equalizer (DFE) is termed as Neural-DFE (NDFE). The results show that the decision delay and training time requirement reduces significantly by use of NDFE. This creates an advantage specifically for a mobile environment where the CCI is varying in nature and the Bayesian equalizer requires a lot of training time. [Copyright &y& Elsevier]

Lymphoid enhancer binding factor 1 (LEF1) is consistently upregulated in chronic lymphocytic leukemia (CLL) and in a subset of large B cell lymphoma. Knowledge of LEF1 expression in Hodgkin lymphoma is limited. In this study, we used immunohistochemistry to survey LEF1 expression in various subsets of Hodgkin lymphoma, de novo classic Hodgkin lymphoma (CHL) (n = 43), Hodgkin lymphoma associated with Richter syndrome (HL-RS) (n = 20), and nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) (n = 9). LEF1 expression was significantly higher in HL-RS compared with de novo CHL (12/20, 60% vs. 12/43, 28%; p = 0.0248). Only a single case (1/9; 11%) of NLPHL showed LEF1 expression. Epstein-Barr virus encoded RNA (EBER) was detected in 17 (40%) cases of de novo CHL and 14 (70%) HL-RS. Notably, we identified a correlation between LEF1 expression and EBER positivity (p = 0.0488). We concluded that LEF1 is commonly positive in CHL but not in NLPHL, and such a distinction may be helpful in this differential diagnosis. The higher frequency of LEF1 upregulation in HL-RS relative to de novo CHL suggests that these neoplasms might have different underlying pathogenic mechanisms and warrants further investigation. • Lymphoid enhancer binding factor 1 (LEF1) is commonly expressed classic Hodgkin lymphoma (CHL). • LEF1 expression was higher in Hodgkin lymphoma associated with Richter syndrome compared with de novo CHL (60% vs. 28%; p =0.0248). • We identified a correlation between LEF1 expression and EBER positivity (p =0.0488). • Only 11% patients with nodular lymphocyte predominant Hodgkin lymphoma (NLPHL) showed LEF1 expression. • A difference in LEF1 expression in CHL and NLPHL may be helpful in the differential diagnosis. [ABSTRACT FROM AUTHOR]

• MP2.5/cc-pvtz successfully applied to reaction energies including halogenated hydrocarbons and open-shell systems. • No significant difference between UHF- and ROHF-reference of MP2.5. • Simple a priori diagnostics based on the analysis of the first few CCSD/cc-pvdz excitation amplitudes. • Favorable correlation between MP2.5 and CCSD(T) reaction energies. • Promising potential of MP2.5 for chemical reactivity of very large systems (e.g., clusters). The performance of the MP2.5 method (MP2 augmented by scaled MP3 correction) is tested for the set of atmospheric reactions including both closed- and open-shell species. The reactions include series of halogen substituted hydrocarbons CH n X 4-n (n = 1–3, X = Cl, Br, I) reacting with OH radical. Both the UHF and ROHF reference wave functions for the open-shell molecules are considered. MP2/cc-pVTZ optimized geometries were used for the calculation of the reaction energies. The accuracy of MP2.5 is discussed in terms of differences between MP2.5/cc-pVTZ and CCSD(T)/cc-pVTZ energies. Simple a priori diagnostic based on the analysis of the coupled-cluster excitation amplitudes calculated at lower CCSD/cc-pVDZ level is introduced. The method seems to be a promising extension of MP2.5 from the realm of intermolecular interactions to chemical reactivity. [ABSTRACT FROM AUTHOR]

Green outdoor environment (GOE) is a dynamic infrastructure to an urban area and part of the city's ecosystem. Although numerous studies have been carried out on GOE, there is still a lack of information on GOE and its relationship in term of usability by office employees. The objectives of the study are to investigate the usage and constraints associated with GOE at workplaces by office employees in the Kuala Lumpur CCZ. The survey was conducted in September 2018 until March 2019 where 326 respondents (N = 326) were involved in this study. The survey findings show that GOE in the Kuala Lumpur CCZ was widely used and enjoyed by diverse groups. Nevertheless, the study found variations in the use, preferences and constraints faced by office employees in CCZ using GOE. The respondents relate their concerns about the location of GOE at workplaces in the Kuala Lumpur CCZ, accessibility, quality of the environment and other personal issues like hectic working hours and health issues. By determining the function of GOE, we can identify any potential of GOE in Malaysian context despite its small size and maximise the use of GOE in the Kuala Lumpur CCZ as an urban space that can provide green, healthy, inclusive, open and public spaces for the citizen of Kuala Lumpur. [ABSTRACT FROM AUTHOR]