PEMBERDAYAAN UMKM SEBAGAI PENGGERAK PEMULIHAN EKONOMI NASIONAL MELALUI OPTIMALISASI INDUSTRI DIGITAL 4.0

Dengan adanya pandemic Covid-19 membuat berbagai sektor terkena dampak, seperti halnya pada sektor ekonomi yaitu Usaha Mikro Kecil Menengah. UMKM merupakan kontribusi terbesar terhadap perekonomian Indonesia dibidang Produk Domestik Bruto dan penyerap tenaga kerja. Dengan adanya pandemic Covid-19, pemerintah mengeluakan kebijakan social distancing yang membatasi seseorang untuk keluar rumah. Hal ini memiliki dampak terhadap UMKM, yang artinya mengharuskan UMKM untuk melakukan digitalisasi yang sesuai dengan era 4.0 sehingga produk yang dihasilkan tetap dapat terjual. Penelitian ini bertujuan untuk mencari solusi pemberdayaan UMKM untuk adanya pemulihan ekonomi nasional ke ranah digitalisasi sehingga output yang dihasilkan dapat membuat masyarakat indonesia menjadi sejahtera. Penelitian ini menggunakan metode penelitian kualitatif dengan menggunakan data sekunder. Hasil penelitian ini menunjukkan bahwa UMKM merupakan sektor ekonomi yang sangat potensial namun mengalami masalah ditengah krisis dan juga sulit menghadapi adaptasi kebiasaan baru yang berbasis Digital. Ekonomi Digital merupakan solusi menyesuaikan tantangan ditengah New Normal, namun belum sepenuhnya menyasar pada ranah informal yang dipegang oleh UMKM mengingat keterbatasan mereka terhadap literasi Digital, sehingga perlu ada perhatian khusus terhadap mereka agar mampu menyesuaikan akan Prospek pasar yang lebih baru guna memulihkan kembali kehidupan mereka agar menjadi lebih sejahtera

UPAYA PEMERINTAH MEWUJUDKAN OPEN GOVERNMENT MELALUI LAYANAN PENGADUAN MASYARAKAT BERBASIS ELEKTRONIK

Penanganan pengaduan masyarakat adalah isu menarik dalam mengkaji pemerintahan demokratis sesuai dengan agenda reformasi. Demokratisasi dan open government hadir adalah konsep yang menekankan upaya membangun partisipasi masyarakat dalam rangka kestabilan politik di Indonesia saat ini. Inovasi dan teknologi di era globalisasi sangat mendukung upaya negara dalam membangun ruang yang terbuka terhadap kehendak masyarakat. Kehendak masyarakat merupakan kunci mewujudkan sebuah pemerintahan yang berkualitas di era demokrasi saat ini, tidak terkecuali pada konteks institusi seperti Kementerian Sekretariat Negara sebagai unsur pendukung berjalannya pemerintahan terlebih di masa pandemi. Penelitian ini menggunakan metode kualitatif deskriptif dengan dibedah oleh teori kebijakan publik Grindle melalui variabel konten dan konteks. Hasil penelitian menunjukkan bahwa kebijakan open government belum terlaksana sesuai harapan mengingat relasi kuasa yang terbatas dalam mendorong implementasi kebijakan ditengah ketidakpastian akibat pandemi. Sehingga perlu sebuah penataan baik manusia, teknologi maupun regulasi demi membangun kapabilitas negara menghadapi situasi krisis terutama Covid-19 ini

Sustainability’s Coming Home: Preliminary Design Principles for the Sustainable Smart District

Consumer trends like local consumption, sharing of property, and environmental awareness change our habits and thereby our surroundings. These trends have their origin in our direct environment, in the districts of our city or community, where we live and socialize. Cities and districts are changing to “smart cities” and “smart districts” as a part of the ongoing digitalization. These changes offer the possibility to entrench the idea of sustainability and build a platform-based ecosystem for a sustainable smart district. This research aims to identify guidelines in form of preliminary design principles for sustainable smart districts. To achieve this, we conduct a structured literature review. On this basis, we derive and develop preliminary design principles with the help of semistructured interviews and a non-representative sample of the German population. The resulting nine preliminary design principles describe a first insight into the design of sustainable smart districts

Nitrogen deficiency in Arabidopsis affects galactolipid composition and gene expression and results in accumulation of fatty acid phytyl esters

Nitrogen is an essential nutrient for plants because it represents a major constituent of numerous cellular compounds, including proteins, amino acids, nucleic acids and lipids. While N deprivation is known to have severe consequences for primary carbon metabolism, the effect on chloroplast lipid metabolism has not been analysed in higher plants. Nitrogen limitation in Arabidopsis led to a decrease in the chloroplast galactolipid monogalactosyldiacylglycerol (MGDG) and a concomitant increase in digalactosyldiacylglycerol (DGDG), which correlated with an elevated expression of the DGDG synthase genes DGD1 and DGD2. The amounts of triacylglycerol and free fatty acids increased during N deprivation. Furthermore, phytyl esters accumulated containing medium-chain fatty acids (12:0, 14:0) and a large amount of hexadecatrienoic acid (16:3). Fatty acid phytyl esters were localized to chloroplasts, in particular to thylakoids and plastoglobules. Different polyunsaturated acyl groups were found in phytyl esters accumulating in Arabidopsis lipid mutants and in other plants, including 16:3 and 18:3 species. Therefore N deficiency in higher plants results in a co-ordinated breakdown of galactolipids and chlorophyll with deposition of specific fatty acid phytyl esters in thylakoids and plastoglobules of chloroplasts

From Research to Diagnostic Application of Raman Spectroscopy in Neurosciences: Past and Perspectives

In recent years, Raman spectroscopy has been more and more frequently applied to address research questions in neuroscience. As a non-destructive technique based on inelastic scattering of photons, it can be used for a wide spectrum of applications including neurooncological tumor diagnostics or analysis of misfolded protein aggregates involved in neurodegenerative diseases. Progress in the technical development of this method allows for an increasingly detailed analysis of biological samples and may therefore open new fields of applications. The goal of our review is to provide an introduction into Raman scattering, its practical usage and also commonly associated pitfalls. Furthermore, intraoperative assessment of tumor recurrence using Raman based histology images as well as the search for non-invasive ways of diagnosis in neurodegenerative diseases are discussed. Some of the applications mentioned here may serve as a basis and possibly set the course for a future use of the technique in clinical practice. Covering a broad range of content, this overview can serve not only as a quick and accessible reference tool but also provide more in-depth information on a specific subtopic of interest

The Quality-Diversity Transformer: Generating Behavior-Conditioned Trajectories with Decision Transformers

In the context of neuroevolution, Quality-Diversity algorithms have proven effective in generating repertoires of diverse and efficient policies by relying on the definition of a behavior space. A natural goal induced by the creation of such a repertoire is trying to achieve behaviors on demand, which can be done by running the corresponding policy from the repertoire. However, in uncertain environments, two problems arise. First, policies can lack robustness and repeatability, meaning that multiple episodes under slightly different conditions often result in very different behaviors. Second, due to the discrete nature of the repertoire, solutions vary discontinuously. Here we present a new approach to achieve behavior-conditioned trajectory generation based on two mechanisms: First, MAP-Elites Low-Spread (ME-LS), which constrains the selection of solutions to those that are the most consistent in the behavior space. Second, the Quality-Diversity Transformer (QDT), a Transformer-based model conditioned on continuous behavior descriptors, which trains on a dataset generated by policies from a ME-LS repertoire and learns to autoregressively generate sequences of actions that achieve target behaviors. Results show that ME-LS produces consistent and robust policies, and that its combination with the QDT yields a single policy capable of achieving diverse behaviors on demand with high accuracy.Comment: 10+7 page

Assessing Quality-Diversity Neuro-Evolution Algorithms Performance in Hard Exploration Problems

A fascinating aspect of nature lies in its ability to produce a collection of organisms that are all high-performing in their niche. Quality-Diversity (QD) methods are evolutionary algorithms inspired by this observation, that obtained great results in many applications, from wing design to robot adaptation. Recently, several works demonstrated that these methods could be applied to perform neuro-evolution to solve control problems in large search spaces. In such problems, diversity can be a target in itself. Diversity can also be a way to enhance exploration in tasks exhibiting deceptive reward signals. While the first aspect has been studied in depth in the QD community, the latter remains scarcer in the literature. Exploration is at the heart of several domains trying to solve control problems such as Reinforcement Learning and QD methods are promising candidates to overcome the challenges associated. Therefore, we believe that standardized benchmarks exhibiting control problems in high dimension with exploration difficulties are of interest to the QD community. In this paper, we highlight three candidate benchmarks and explain why they appear relevant for systematic evaluation of QD algorithms. We also provide open-source implementations in Jax allowing practitioners to run fast and numerous experiments on few compute resources.Comment: GECCO 2022 Workshop on Quality Diversity Algorithm Benchmark

Complementary Patents and Market Structure

Many high technology goods are based on standards that require several essential patents owned by different IP holders. This gives rise to a complements and a double mark-up problem. We compare the welfare effects of two different business strategies dealing with these problems. Vertical integration of an IP holder and a downstream producer solves the double mark-up problem between these firms. Nevertheless, it may raise royalty rates and reduce output as compared to non-integration. Horizontal integration of IP holders solves the complements problem but not the double mark-up problem. Vertical integration discourages entry and reduces innovation incentives, while horizontal integration always benefits from entry and innovatio

Safety, Immunogenicity, and Efficacy of Intramuscular and Oral Delivery of ERA-G333 Recombinant Rabies Virus Vaccine to Big Brown Bats (\u3ci\u3eEptesicus fuscus\u3c/i\u3e)

Attenuated strains of rabies virus (RABV) have been used for oral vaccination of wild carnivores in Europe and North America. However, some RABV vaccines caused clinical rabies in target animals. To improve the safety of attenuated RABV as an oral vaccine for field use, strategies using selection of escape mutants under monoclonal antibody neutralization pressure and reverse genetics–defined mutations have been used. We tested the safety, immunogenicity, and efficacy of one RABV construct, ERA-g333, developed with reverse genetics by intramuscular (IM) or oral (PO) routes in big brown bats (Eptesicus fuscus). Twenty-five bats received 5×106 mouse intracerebral median lethal doses (MICLD50) of ERA-g333 by IM route, 10 received 5×106 MICLD50 of ERA-g333 by PO route, and 22 bats served as unvaccinated controls. Twenty-one days after vaccination, 44 bats were infected by IM route with 102.9 MICLD50 of E. fuscus RABV. We report both the immunogenicity and efficacy of ERA-g333 delivered by the IM route; no induction of humoral immunity was detected in bats vaccinated by the PO route. Two subsets of bats vaccinated IM (n=5) and PO (n=3) were not challenged, and none developed clinical rabies from ERA-g333. Scarce reports exist on the evaluation of oral rabies vaccines in insectivorous bats, although the strategy evaluated here may be feasible for future application to these important RABV reservoirs