Miracle-dz/UniFAR-FTUs huggingface dataset:
Screening of high lipid content and productivity of microalgae under photoautotrophic cultivation for biodiesel production

Microalgae are globally accepted source of fatty acids (FA) due to their cell's potential to efficiently accumulate triacylglycerides which contain a significant amount of fatty acids for biodiesel production. This study aimed to screen nine (09) green microalgae strains in the laboratory for their high biomass and lipid productivity. Various microalgae strains were cultured at 30°C, with a light to dark ratio of 16:8 h (10–12 klux of light intensity) and aeration supplementation of 2% CO2 for longer period of time. The fatty acids of all microalgae species which showed growth potential under photoautotrophic cultivation had similar fatty acids found in palm oil. The selected strains of Ankistrodesmus sp. IFRPD 1061 and Chlorella sp. IFRPD 1092 were used due to their high lipid productivity content, were cultivated in 100 L NS III medium in an open raceway pond, aerated with 2% v/v CO2. The biomass concentration and productivity, lipid concentration and productivity of Ankistrodesmus sp. IFRPD 1061 (0.865 g/L, 76.250 mg/L/d, 0.167 g/L, and 14.685 mg/L/d, respectively) were found to be higher than those of Chlorella sp. IFRPD 1092 (0.433 g/L, 31.250 mg/L/d, 0.137 g/L, and 8.528 mg/L/d, respectively). Ankistrodesmus sp. IFRPD 1061 showed potential results of growing microalgae under photoautotrophic cultivation for biodiesel production.
Urea-Based Patches with Controlled Release for Potential Atopic Dermatitis Treatment

Skin diseases such as atopic dermatitis (AD) are widespread and affect people all over the world. Current treatments for dry and itchy skin are mostly focused on pharmaceutical solutions, while supportive therapies such as ointments bring immediate relief. Electrospun membranes are commonly used as a drug delivery system, as they have a high surface to volume area, resulting in high loading capacity. Within this study we present the manufacturing strategies of skin patches using polymer membranes with active substances for treating various skin problems. Here, we manufactured the skin patches using electrospun poly(vinyl butyral-co-vinyl alcohol-co-vinyl acetate) (PVB) fibers blended and electrosprayed with urea. The highest cumulative release of urea was obtained from the PVB patches manufactured via blend electrospinning with 5% of the urea incorporated in the fiber. The maximum concentration of released urea was acquired after 30 min, which was followed up by 6 h of constant release level. The simultaneous electrospinning and electrospraying limited the urea deposition and resulted in the lowest urea incorporation followed by the low release level. The urea-based patches, manufactured via blend electrospinning, exhibited a great potential as overnight treatment for various skin problems and their development can bring new trends to the textile-based therapies for AD.
Learning in Your “Pocket”: Secure Collaborative Deep Learning With Membership Privacy

Organizations tend to collaboratively train the deep learning model over their combined datasets for a common benefit (e.g., better-trained model or learning a complicated model). However, due to the consideration about privacy leakage, organizations cannot share their data directly, especially related to sensitive domains. In this article, a privacy-preserving collaborative deep learning mechanism, namely Sigma, is designed to allow participating organizations to train a collective model without exposing their local training data to the others. Specifically, a single-server-aided private collaborative architecture is introduced to achieve the private collaborative learning, which protects organizations’ data even if <inline-formula><tex-math notation="LaTeX">$n-1$</tex-math><alternatives><mml:math><mml:mrow><mml:mi>n</mml:mi><mml:mo>-</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:math><inline-graphic xlink:href="ma-ieq1-3192326.gif"/></alternatives></inline-formula> out of <inline-formula><tex-math notation="LaTeX">$n$</tex-math><alternatives><mml:math><mml:mi>n</mml:mi></mml:math><inline-graphic xlink:href="ma-ieq2-3192326.gif"/></alternatives></inline-formula> participants colluded. We also design a practical protocol to perform the secure model training, which can resist the typical inference attack through the sharing information. After that, we propose a fair model releasing mechanism for participants and introduce differential privacy to prevent model stealing and membership inference attack. Furthermore, we prove that Sigma can ensure participants’ privacy preservation and analyze the communication overhead in theory. To evaluate the effectiveness and efficiency of Sigma, we conduct an experiment over two real-world datasets and the simulation results demonstrate that Sigma can efficiently achieve the collaborative model training and effectively resist the membership inference attack.
Dance Movement Recognition Based on Multimodal Environmental Monitoring Data

Fine motion recognition is a challenging topic in computer vision, and it has been a trendy research direction in recent years. This study combines motion recognition technology with dance movements and the problems such as the high complexity of dance movements and fully considers the human body's self-occlusion. The excellent motion recognition content in the dance field was studied and analyzed. A compelling feature extraction method was proposed for the dance video dataset, segmented video, and accumulated edge feature operation. By extracting directional gradient histogram features, a set of directional gradient histogram feature vectors is used to characterize the shape features of the dance video movements. A dance movement recognition method is adopted based on the fusion direction gradient histogram feature, optical flow direction histogram feature, and audio signature feature. Three components are combined for dance movement recognition by a multicore learning method. Experimental results show that the cumulative edge feature algorithm proposed in this study outperforms traditional models in the recognition results of HOG features extracted from images. After adding edge features, the description of the dance movement shape is more effective. The algorithm can guarantee a specific recognition rate of complex dance movements. The results also verify the effectiveness of the movement recognition algorithm in this study for dance movement recognition.
Mental health in individuals with self-reported psychiatric symptoms during the COVID-19 pandemic: Baseline data from a swedish longitudinal cohort study

Objective Individuals with psychiatric disorders may be both vulnerable and sensitive to rapid societal changes that have occurred during the COVID-19 pandemic. To fully understand these impacts, repeated measurements of these individuals are warranted. The current longitudinal study set out to perform monthly assessment of individuals with common psychiatric disorders using established questionnaires with a possibility for them to self- rate their symptoms, over time. Methods Recruitment of individuals who identified themselves as struggling with mental health problems, living in Sweden between July 2020 and June 2021 using an online survey. The individuals answered questions on demographics, psychiatric history, current psychiatric symptoms (e.g., Patient Health Questionnaire, PHQ-9; General Anxiety Disorder, GAD-7), somatic health, health-care contacts and any changes therein during the pandemic. Monthly, longitudinal assessments are still ongoing (consenting participants provide data for 1 year), and here we present descriptive statistics from the baseline measurement. All measurements from baseline (>400 items), and follow-ups are presented in detail. Results A total of 6.095 participants (average age 35 years) submitted complete baseline data. Marital status (43% single) and number of years of education (48% highest degree being high school) were evenly distributed in this population. The most common lifetime psychiatric disorder in the sample was depressive disorder (80.5%) and generalized anxiety disorder (45.9%), with a substantial proportion having severe symptoms of depression. (30.5%) and anxiety (37.1%). Lifetime suicidal ideation (75.0%) and non-suicidal self-harm (57.7%) were prevalent in the group and 14.5% reported drug use during the pandemic. Allergies (36.8%) were the most common somatic condition, followed by irritable bowel syndrome (18.7%). For those having experienced a traumatic event, 39% showed symptoms during the pandemic indicating PTSD. Regarding contact with mental health services during the pandemic, 22% had established a new contact, and 20% reported to have increased their psychiatric medication compared to before the pandemic. Conclusion Baseline data collected during the pandemic from individuals in Sweden with pre-existing psychiatric disorders demonstrate that this sample represents a population suitable for an investigation on the long-term impact of the pandemic, as intended by the longitudinal investigation that is ongoing. Follow-up questionnaires over a 12-month period are being collected and will indicate how the health and well-being of this population was impacted during the changes and uncertainties that have been characteristic of the past 2 years.
A NOVEL COGNIZANCE OF RETICULATED CONTEMPORANEOUS THERMIONIC BALLOTING SYSTEMATIZATION WITH IOT

: The Election polling system is not a new concept. It is the right of people to choose leader who works for their bright futures. In this connection so many proposals are invented. The most traditional way of the voting system is based on papers. It requires lot of paper work. The man power is also largely required for it. It is a time taking process also. In this present situation conducting polling process with large number of working people is difficult task. Due to increase in the COVID-19 cases the entire world is under Lock-Down. In this pandemic situation every body is under self quarantine. So in this situation it is better to develop new schemes and new procedures. The concept behind this problem is the proposes new scheme of this paper. It is possible to conduct elections without large gathering of people at one place or the large working crew. So in this connection a framework related to IoT can solve the problem with desired functionality. By designing simple hardware system with modules like finger print scanner sensor, Arduino module, WiFi module, power supply along with dashboard display. This approach can greatly reduce the paper work and large working crew. In place of finger print scanner it is possible to use iris scanner also to increase security and genuine results. So in this connection the objective is to reduce paper work and working crew but here also people need to go for polling centre for voting. To avoid large gathering of people it is required to design a frame work so that every one can cast their vote from home. The possibilities are around IoT protocols. It is possible to cast their vote through mobile phone with the help of secure IoT frame work. So that no need to go to polling station and results will be displayed at that time of instant. To access this feature every can login with finger print scanning or iris scanner. So it avoids fraud while voting. Hence it easy to conduct polling process without any disturbances. So this process is simple, secure, efficient, accurate and fast than compared to traditional voting process.
Multilevel Information Security in multimedia environment using Frequency domain transformation

_________________________________ Abstract - Due to rapid advancement in communication Security has become real concern. Thus to fulfill this requirement the information should be protected in such a way so that its presence should not be felt by anyone except the receiver. Steganography restricts the access to the unauthorized users. This method considers any text, image, voice, video as cover image. This paper approaches towards securing information exchange over the internet using image processing. In this proposed method the technique wavelet transformation is used along with cryptography and Steganography, where information contained text file is hidden inside a video frame or image without causing any distortion in the quality of that. The frames are transformed by discrete wavelet transform, where both the frame with and without noise exist. The message is carefully hidden into the noisy channels of image. Reconstruction of the stego image is done by inverse DWT. After receiving the stego video it need to be transformed by DWT again for segregation. Lastly the extraction of secured information contained text file is done by the receiver. Due to multilevel encryption, the hidden information remains highly secured compared to other methods.
Long-Term Impact of a Faculty Development Program on Student Evaluations of Teaching

Although participation in faculty development programs has been linked to improvements in teaching and positiveoutcomes in student learning, prior research has yet to uncover how these outcomes might lead to increases in studentevaluation of teaching scores. Student evaluation of teaching scores are frequently used in tenure and promotion decisions,and prior research has found that these scores often decline over time. Thus, it is important to better understand howfaculty development programs might work to improve these scores. In this study, we examine whether student evaluationsof teaching scores do decline over time, and the potential impact of a faculty development program on these evaluations.
Openness to International Trade and Income Risk in Cemac

In this paper, the effects of international trade on income risk are investigated. Arguing that the interaction between international trade and his different channels (export share and import penetration) plays an important role in explaining labour income risk, we employ a sample of 6 central Africa’s countries covering the period 1993-2013, in aggregate level, to estimate time-varying individual income risk at the sector level. The relationship between trade and labour income risk is analyzed by combining our estimates of persistent labour income risk with measures of exposure to international trade. It is established that export share have a statistically significant association with labour income risk in the CEMAC countries. Our findings are robust to the econometric techniques used, to the inclusion of a wide range of control variables.
Cycle Time Reduction in Batch Processing by Upstream Rescheduling

Dynamic control policies utilize the expected future arrival times of the products and find a batching policy that minimizes typical performance measures such as waiting time of products in the queue. In this paper, the focus is on the batching control of semiconductor manufacturing with multiple product types. The production unit of interest consists of a serial process followed by a batch process where departures from the former become future arrivals to the latter. The scheduling decisions of the serial process are incorporated with the batch process scheduling. This setting allows the selection of the next arriving product type out of available types in the serial queue. The proposed look-ahead heuristic determines the part type to be processed next in the serial process as well as the starting epoch of the batch process and the product type to be batched in a rolling horizon. This upstream rescheduling reduces batch process queueing times compared to the benchmark models.
Performance Analysis of an Integrated Image Retrieval Technique for Minority Culture Protection and Inheritance

- It is very significant to know the different minority costumes which are vanishing now a day which is used for minority culture protection and inheritance. To get the exact results for image retrieval there is need of a novel image feature representation method which is used to show the rich information of minority costume image. In this implementation first image is divided into image sub-blocks and then from that image calculate both color histogram as well as edge orientation histogram separately. The final feature used for minority costume image retrieval is fusion or integration of both color histogram and edge orientation histogram. At last improved Canberra distance is calculated for the input query image and retrieved output image. For the performance analysis there is use of self-build minority costume image dataset. MATLAB analysis results show that integrated technique of image retrieval will give outperforming results for characteristics such as color, texture, shape and spatial information, in comparison to existing technique proposed work will give higher and stable retrieval accuracy.
RELEASE OF Stethorus gilvifrons (MULS.) (COLEOPTERA: COCCINELLIDAE) AS A BIOLOGICAL CONTROL AGENT OF THE TWO-SPOTTED RED SPIDER MITE, Tetranychus urticae KOCH ON SOYBEAN PLANTATIONS UNDER FIELD CAGE CONDITIONS.

This study was outlined to declare the effect of releases of Stethorus gilvifrons (Muls.) adults at different predator: prey ratios (P: p) to control the two-spotted red spider mite, Tetranychus urticae Koch on soybean plants under field cage conditions during summer season of 2007. Effective control of T. urticae was gained after nine day from introducing the adult of the coccinellid predator when the P: p ratio was 1:10 or 1:20. Meanwhile at higher ratios (1:40 and 1: 50), the two-spotted red spider mite numbers were decreased after 12 days from the release. The numbers of the two-spotted red spider mite were decreased by 85 and 79.75% at 1:10 and 1:20 P: p ratios, respectively when adults of the coccinelld released. The number of the two-spotted red spider mite remained zero for a period of 12 days after the release. At the predator: prey ratio of 1:40, the reduction percentage of the two-spotted red spider mite was 10.13 and 40.37% after one and three days. Whereas, at the higher ratios 1:50 the reduction percentage was 8.5 and 32.0, 51.4, 67.2 and 86.70% after one , three, six, nine and 12 days from the release, respectively. After nine days from release P: p of 1:10, 1:20, 1:30, 1:40 and 1:50, the reduction percentage was 85.0, 79.75, 76.87, 76.33 and 67.20 %. After 12 days where as the reduction percentages were 100,100, 92.33, 91.75 and 86.7, respectively. The reduction rate was increased with lower P: p ratios and vice versa.
Adversarial Disentanglement Using Latent Classiﬁer for Pose-Independent Representation

—The large pose discrepancy is one of the critical challenges in face recognition during video surveillance. Due to the entanglement of pose attributes with identity information, the conventional approaches for pose-independent representation lack in providing quality results in recognizing largely posed faces. In this paper, we propose a practical approach to disentangle the pose attribute from the identity information followed by synthesis of a face using a classiﬁer network in latent space. The proposed approach employs a modiﬁed generative adversarial network framework consisting of an encoder-decoder structure embedded with a classiﬁer in manifold space for carrying out factorization on the latent encoding. It can be further generalized to other face and non-face attributes for real-life video frames containing faces with signiﬁcant attribute variations. Experimental results and comparison with state of the art in the ﬁeld prove that the learned representation of the proposed approach synthesizes more compelling perceptual images through a combination of adversarial and classiﬁcation losses.
Protein and MHC Class II Molecules Expression of a Complex of an Intact Lysosomal Intracellular Formation and Cell Surface

The generation of invariant chain-free MHC class II molecules and their association with endocytically generated peptides are thought to occur in specialized lysosome-like compartments called MIICs (MHC class II compartments). A number of in vitro studies have shown that large denatured proteins can bind to class II molecules, and that class II association can protect the bound segment of protein from proteolytic degradation. In this work, we present what we believe is the ﬁrst example of an intact endogenous protein (IP30) binding in an allele-dependent fashion to class II molecules in vivo. IP30 is an IFN- g -inducible 35-kDa glycoprotein that localizes in MIICs. In this study, we show that intact IP30 binds to certain HLA-DR alleles via an N-terminal prosequence. The association takes place in the endocytic pathway following removal of invariant chain from class II molecules and before their cell surface expression. We also show that DR-IP30 complexes are SDS stable. The potential precursor-product relationship between DR-IP30 complexes and the DR-peptide complex is discussed. The Journal of Immunology, 1998, 160:
Towards the Standardization of Industrial Scientific and Engineering Workflows with QVT Transformations

— Nowadays, design activities in engineering and many other applied science fields require the execution of computational models in order to simulate experiments. This step is usually automated through the execution of the so-called scientific workflows. A large number of different graphic and execution formats are currently in use today, with no clear signs of convergence into a standard format. Things are different in the area of business processes, where many standards have been defined for both the graphical and the execution representation of business process workflows. Significant efforts are currently being carried out to apply business workflow technology into engineering fields. Nevertheless, one of the main obstacles for the industrial adoption of standards is the large base of existing workflows used currently by industry, which cannot be just thrown away. This paper presents a model-to-model transformation using QVT between a widely used industrial metamodel and the BPMN 2.0 standard metamodel. Legacy workflow support is an essential first step to allow the introduction of the use of a business process standard in scientific and engineering industrial applications.
Realisation of carved and iris groove gap waveguide filter and E-plane diplexer for V-band radio link application

The gap waveguide technology is a promising candidate as a cost-effective and low-loss platform for realizing microwave devices particularly at frequencies higher than 40GHz. In this study, two types of groove gap waveguide filters and also a diplexer are presented. Coupling mechanism of these filters is based on carving on the pin plate and iris between adjacent cavities. Two fifth-order Chebyshev filters are realised at 62.5GHz. The proposed diplexer consists of RX and TX iris groove gap waveguide filters at the centre frequency of 59.5 and 62.5GHz and an E-plane groove gap waveguide T-junction. The required transition of the groove gap waveguide to WR-15 is designed and used as an input port of the filters. Moreover, E-plane groove gap waveguide T-junction is designed as the connecting part of the groove gap waveguide filters to the WR-15 antenna port. Finally all parts are integrated. The proposed diplexer is manufactured in aluminium by sawing and milling and then silver plating is done. The RX and TX passbands of the diplexer is around 1.7 and 2.4% with the measured return loss better than 13.6dB and minimum insertion loss of 0.9 and 0.8dB, respectively.