Predictive models for multibiometric systems

Recognizing a subject given a set of biometrics is a fundamental pattern recognition problem. This paper builds novel statistical models for multibiometric systems using geometric and multinomial distributions. These models are generic as they are only based on the similarity scores produced by a recognition system. They predict the bounds on the range of indices within which a test subject is likely to be present in a sorted set of similarity scores. These bounds are then used in the multibiometric recognition system to predict a smaller subset of subjects from the database as probable candidates for a given test subject. Experimental results show that the proposed models enhance the recognition rate beyond the underlying matching algorithms for multiple face views, fingerprints, palm prints, irises and their combinations

Spiking Neural Network for Augmenting Electroencephalographic Data for Brain Computer Interfaces

With the advent of advanced machine learning methods, the performance of brain-computer interfaces (BCIs) has improved unprecedentedly. However, electroencephalography (EEG), a commonly used brain imaging method for BCI, is characterized by a tedious experimental setup, frequent data loss due to artifacts, and is time consuming for bulk trial recordings to take advantage of the capabilities of deep learning classifiers. Some studies have tried to address this issue by generating artificial EEG signals. However, a few of these methods are limited in retaining the prominent features or biomarker of the signal. And, other deep learning-based generative methods require a huge number of samples for training, and a majority of these models can handle data augmentation of one category or class of data at any training session. Therefore, there exists a necessity for a generative model that can generate synthetic EEG samples with as few available trials as possible and generate multi-class while retaining the biomarker of the signal. Since EEG signal represents an accumulation of action potentials from neuronal populations beneath the scalp surface and as spiking neural network (SNN), a biologically closer artificial neural network, communicates via spiking behavior, we propose an SNN-based approach using surrogate-gradient descent learning to reconstruct and generate multi-class artificial EEG signals from just a few original samples. The network was employed for augmenting motor imagery (MI) and steady-state visually evoked potential (SSVEP) data. These artificial data are further validated through classification and correlation metrics to assess its resemblance with original data and in-turn enhanced the MI classification performance

Compatibility of entomopathogenic fungi with extracts of plants and commercial botanicals

The compatibility of some commercial botanicals (Biospark, Phytophrate, Exodos, Biodos and Neemgold) and of solvent extracts of Syndrella nodiflora, Premna tomentosa, Vitex negundo, Ipomea carnea, Pteridium aquilinum (leaves) and Annona squomosa (seeds) with Beauveria bassiana (Bals.) Vuil., Isaria (Paecilomyces) fumosorosea (Wize) Brown et Smith and Lecanicillium (Verticillium) lecanii Humber in vitro was studied using dual plate and liquid bioassays. The results showed that Biospark. Phytophrate and Exodos highly reduced the mycelial growth of B. bassiana, P. fumosorosea and V. lecanii, respectively. Irrespective of the fungi tested, A. squomosa ethanol and I. cornea water extracts had maximum and minimum growth inhibiting activity against three fungi, respectively. Hence, these extracts can be integrated along with these fungi in the biointensive integrated pest management (BIPM) programme.Key words: Compatibility, entomopathogenic fungi, plant-based biopesticides, plant extracts

Herbs and Rehabilitation after Stroke Study: A Multi-center, Double-blinded, Randomized Trial in Hong Kong

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KINERJA PENGAWAS DALAM PENINGKATAN MUTU PENDIDIKAN PADA MADRASAH ALIYAH NEGERI DI KOTA BANDAR LAMPUNG

ABSTRAK Kinerja Pengawas dalam Peningkatan Mutu Pendidikan pada Madrasah Aliyah Negeri di Kota Bandar Lampung Oleh : Sukron Pengawas madrasah bertugas membantu dan membina guru meningkatkan profesionalismenya agar dapat meningkatkan kualitas proses dan hasil belajar siswa. Pengawas madrasah juga bertugas membantu kepala madrasah dan seluruh staf madrasah agar dapat meningkatkan mutu penyelengaraan pendidikan pada madrasah yang dibinanya.Penelitian ini merupakan jenis penelitian field research (penelitian lapangan) dengan menggunakan pendekatan kualitatif. Sedangkan Teknik pengumpulan data dengan cara observasi, wawancara, dan dokumentasi. Lokasi penelitian adalah MAN 1 dan MAN 2 Kota Bandar Lampung. Perencanaan pengawasan pada Madrasah Aliyah Negeri Kota Bandar Lampung disusun berdasarkan analisis Program Tahunan, Program Semester, rencana kepengawasan manajerial (RKM) dan rencana kepengawasan akademik (RKA). Pelaksanaan kinerja pengawas pada Madrasah Aliyah Negeri Kota Bandar Lampung dilaksanakan dengan mengadakan kunjungan kelas dan observasi langsung terhadap proses pelaksanaan pembelajaran di kelas serta pembimbingan dan pelatihan melalui workshop, seminar, observasi, individual, Kelompok Kerja Guru (KKG), Musyawarah Guru Mata Pelajaran (MGMP) dan group conference. Evaluasi kinerja pengawas pada Madrasah Aliyah Negeri Kota Bandar Lampung bertujuan untuk pembinaan dan pemantauan kegiatan dan kinerja guru sekaligus membantu guru dalam mengembangkan kemampuan mengelola proses pembelajaran. Kata kunci : Kinerja, Pengawas, Madrasah Aliyah viiABSTRACT Supervisors Performance in Improving the Quality of Education at State Islamic high school in Bandar Lampung City By: Sukron supervisor Islamic high school are tasked with helping and fostering teachers to improve their professionalism in order to enhance the quality of the process and student learning outcomes. The Islamic high school supervisor is in charge of assisting the head of Islamic high school and all staff in order to improve the quality of education in the Islamic high school under his supervision. This research is a type of field research (field research) using a qualitative approach. While the technique of collecting data by means of observation, interviews, and documentation. The research locations are MAN 1 and MAN 2 Bandar Lampung City. Supervision planning at State Islamic high school Bandar Lampung City is compiled based on the analysis of the Annual Program, Semester Program, managerial supervision plan (RKM) and academic supervision plan (RKA). The performance of supervisors at State Islamic high school Bandar Lampung City is carried out by conducting class visits and direct observation of the process of implementing learning in class as well as mentoring and training through workshops, seminars, observations, individuals, Teacher Working Groups (KKG), Subject Teacher Deliberations (MGMP) and group conferences. Evaluation of the performance of supervisors at State Islamic high school Bandar Lampung City aims to guide and monitor teacher activities and performance as well as to assist teachers in developing the ability to manage the learning process. Keywords: Performance, Supervisor, Islamic high school viiiصخلم ايلعلا ةيموكلحا ةسردلما في ميلعتلا ةدوج نيسحت يف فيارشلإا ءادلأا جنوبملا ردنب ةنيدم في ركس ةدعاسبم نوفلكم ةسردلما فيرشمو ، ميلعتلا ىلع ينفرشم وأ ميلعتلا ىلع ينفرشمكةسردم لوؤسلما وه ةسردلما ىلع فرشلما . بلاطلا ملعت جئاتنو ةيلمعلا ةدوج زيزعت لجأ نم مهتينهم ينسحتلنيملعلما . هفارشإ تتح ةسردلما في ميلعتلا ةدوج ينستح لجأ نم ةسردلما يفظوم عيجمو ةسردلما سيئر ةدعاسم نع عجم ةينقت امنيب .يعون جهنم مادختسبا )نياديم ثبح( نياديلما ثحبلا نم عون وه ثحبلا اذه ةسردلما و 1 ايلعلا ةيموكلحا ةسردلما يه ثحبلا عقاوم .قيثوتلاو تلاباقلماو ةظحلالما قيرط نع تناايبلا 2 ايلعلا ةيموكلحا جمنابرلا ليلتح ىلع ًءانب جنوبملا ردنب ةنيدم في ايلعلا ةيموكلحا ةسردلما في في فارشلإا طيطتخ عيمتج تم (RKA). ييمداكلأا فارشلإا ةطخو (RKM) يرادلإا فارشلإا ةطخو يساردلا لصفلا جمناربو يونسلا ةيفص تارياز ءارجإ للاخ نم جنوبملا ردنب ةنيدم يرجين ايلع ةسردم في ينفرشلما ءادأ ذيفنت متي تاودنلاو لمعلا شرو للاخ نم بيردتلاو هيجوتلا لىإ ةفاضلإبا لصفلا في ملعتلا ذيفنت ةيلمعل ةرشابم ةبقارمو عوضولما سردم تلاوادم ، (KKG) ملعلما لمع تاعوممجو دارفلأاو تاظحلالماو . ةيعاملجا تارتدؤلماو (MGMP). ملعلما ةطشنأ ةبقارمو هيجوت لىإ جنوبملا ردنب ةنيدم يرجين ايلعلا ةسردلما في ينفرشلما ءادأ مييقت فدهي ملعتلا ةيلمع ةرادإ ىلع ةردقلا ريوطت في ينملعلما ةدعاسلم كلذكو هئادأو ةيلاع ةسردم ، فرشم ، ءادأ: ةيحاتفلما تاملكل

Spontaneous face- and eye-touching: Infection risk versus potential microbiome gain

The COVID-19 pandemic has piqued interest in spontaneous face-touch as a possible route of microbial infection, with eye-touch of particular importance since the ocular surface is a likely portal of human Coronavirus infection. Spontaneous face-touching is a poorly understood, ingrained habit for humans, who engage in this activity on average between 9 to 162 times per hour. Nearly half of spontaneous face-touches involve mucous membranes, and one third of those involve the eyes. The infective sequelae of self-touch are well documented in ophthalmological conditions such as infectious conjunctivitis, with risks for ocular surface disease beyond primary infection from pathogens such as human papillomavirus. Through tear film conveyance via the nasolacrimal duct, ocular surface pathogens may furthermore have access to the nasopharynx, oropharynx, and respiratory/gastrointestinal systems beyond. Ocular surface and face self-touch therefore represent a concerning possible method of not only local, but also systemic, self-inoculation. Conversely, microbial diversity in the mutualistic microbiome is being increasingly implicated as integral for developing immunity, and protecting against endocrinological and neurodegenerative disease, including those that affect the eye. Spontaneous face-touch brings the hands, the part of the body most in contact with the external world and with the highest temporal diversity, into direct contact with the body's multiple microbiomes. The authors hypothesise that spontaneous self-touch may represent an important mechanism by which the skin, ocular surface, gastrointestinal, and respiratory tracts maintains microbial diversity and prevents dysbiosis. It may be that whilst the eyes are at risk of infection through self-touch, they may paradoxically benefit through the acquisition of a mutualistic microbiome, protective not only for the eyes, but for the body as a whole

On the stability in phase-lag heat conduction with two temperatures

We investigate the well-posedness and the stability of the solutions for several Taylor approximations of the phase-lag two-temperature equations.We give conditions on the parameters which guarantee the existence and uniqueness of solutions as well as the stability and the instability of the solutions for each approximationPeer ReviewedPostprint (author's final draft

Field Evaluation of Three Entomopathogenic fungi on Groundnut Pest

Entomopathogenic fungi Beauveria bassiana (Balsamo) Vuillemin (Deuteromycotina: Hyphomycetes), Paecilomyces fumosoroseus (Wize) (Deuteromycotina: Hyphomycetes), Verticillium lecani Viegas (Deuteromycotina: Hyphomycetes) were tested against groundnut pests, Aphis craccivora (Koch) (Homoptera: Aphididae), Aproarema modicella (Deventer) (Lepidoptera: Gelechiidae), Mylabris pustulata Faust (Coleoptera: Meloidae) and Spodoptera litura (Fabricius) (Lepidoptera: Noctuidae) in field conditions. Among the tested fungi, V. lecanii suppressed 62% of A. craccivora population at 39 Days After Seedling Emergence (DASE). During the same period, B. bassiana reduced 72% of S. litura larval population (0.73 larvae). The infestation of S. litura and A. modicella were greatly reduced after the treatment of B. bassiana; subsequently the yield (1721.31 kg/ha-1) and cost benefit ratio (1: 1.93) were increased. P. fumosoroseus and V. lecanii were less effective than B. bassiana. The persistence of fungal pathogens was found to be higher in soil than the phyllosphere indicating that they can be naturally favored for the control of pests in groundnut

HPLC Method for Determination of Rifaximin in Human Plasma Using Tandem Mass Spectrometry Detection

The present study was aimed at developing a simple, sensitive, and specific liquid chromatography–tandem mass spectrometry method for the quantification of rifaximin in human plasma using rifaximin D6 as internal standard. Chromatographic separation was performed on Zorbax SB C18, 4.6 x 75 mm, 3.5 μm column with an isocratic mobile phase composed of 10 mM ammonium formate (pH 4.0) and acetonitrile in the ratio of (20:80 v/v), at a flow-rate of 0.3 mL/min. Rifaximin and rifaximin D6 were detected with proton adducts at m/z 786.4 → 754.4 and 792.5 → 760.5 in multiple reaction monitoring positive mode respectively. The acidified samples were subjected to liquid–liquid extraction using a mixture of methyl t-butyl ether - dichloromethane (75: 25) followed by centrifugation, nitrogen-aided evaporation and reconstitution. The method was validated over a linear concentration range of 20 - 20000 pg/mL with correlation coefficient of more than 0.9995. This method demonstrated intra and inter-day precision within 0.6 - 2.6% and 2.2 - 5.6%, and accuracy within 95.7 - 104.2% and 95.8 - 105.0% for rifaximin, respectively. Rifaximin was found to be stable throughout freeze–thawing cycles, bench top and postoperative stability studies. This method was applied successfully for the analysis of blood samples following oral administration of rifaximin (200 mg) in 17 healthy Indian male human volunteers under fasting conditions.Keywords: Bioequivalence, mass spectrometry, rifaximinEast and Central African Journal of Pharmaceutical Sciences Vol. 13 (2010) 78-8

Reward Based Hebbian Learning in Direct Feedback Alignment (Student Abstract)

Imparting biological realism during the learning process is gaining attention towards producing computationally efficient algorithms without compromising the performance. Feedback alignment and mirror neuron concept are two such approaches where the feedback weight remains static in the former and update via Hebbian learning in the later. Though these approaches have proven to work efficiently for supervised learning, it remained unknown if the same can be applicable to reinforcement learning applications. Therefore, this study introduces RHebb-DFA where the reward-based Hebbian learning is used to update feedback weights in direct feedback alignment mode. This approach is validated on various Atari games and obtained equivalent performance in comparison with DDQN